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Our solution includes providing an autonomous physical presence, gathering data from the environment in real-time, and pushing anomalies to our user interface, the Knightscope Security Operations Center (KSOC), providing our clients across the U.S. a 24/7 force multiplier effect.\r\nSource: https://www.linkedin.com/company/knightscope-inc-/about/","companyTypes":["supplier","vendor"],"products":{},"vendoredProductsCount":1,"suppliedProductsCount":1,"supplierImplementations":[],"vendorImplementations":[],"userImplementations":[],"userImplementationsCount":0,"supplierImplementationsCount":0,"vendorImplementationsCount":0,"vendorPartnersCount":0,"supplierPartnersCount":0,"b4r":0,"categories":{"77":{"id":77,"title":"SOC - Situation Centre","description":"One of the most pressing tasks facing government bodies and commercial structures is to increase the efficiency of management activities. A modern tool for solving this problem is situational centers, which are complex hardware and software systems for collecting, analyzing and displaying information in a form convenient for making critical decisions.\r\nSituational centers are created for the heads of federal, regional and municipal government bodies, ministries and departments, and large companies. Their main task is to provide information and analytical support for procedures and processes that allow managers to make effective decisions on the current management of headed structures, formulating their development strategies, as well as preventing or eliminating crisis and emergency situations. The structure and composition of the situational site are determined by the specifics of the tasks being solved. As a rule, this is a complex technical complex that includes many subsystems.\r\nThere are many types of command centers. They include: data center management, business application management, civil management, emergency (crisis) management.","materialsDescription":" <span style=\"font-weight: bold;\">What is a Security Operations Center (SOC)?</span>\r\nA SOC is an outsourced office that is completely dedicated to analyzing traffic flow and monitoring for threats and attacks. In today’s world of cyberattacks and data breaches, companies of all sizes need to place an emphasis on securing their technology assets. But due to budget constraints and competing priorities, many organizations can’t afford to employ a full-time in-house IT security team. The smart solution to this problem is to look at partnering with a SOC or security operations center.\r\n<span style=\"font-weight: bold;\">How does a security operations center work?</span>\r\nUntil the recent rise of cloud computing, standard security practice was for a company to choose a traditional software as a product (SaaP) malware scanning solution either via download or, in ancient days, a CD-Rom that arrived via mail. They’d add to that a firewall installed at the edge of the network, and trust that those measures would keep their data and systems safe. Today’s reality is a far different environment, with threats being cast all across the net as hackers invent new ways to launch profitable and sophisticated attacks like ransomware.\r\nA SOC is an example of the software as a service (SaaS) software model in that it operates in the cloud as a subscription service. In this context, it provides a layer of rented expertise to a company’s cybersecurity strategy that operates 24/7 so that networks and endpoints are constantly being monitored. If a vulnerability is found or an incident is discovered, the SOC will engage with the on-site IT team to respond to the issue and investigate the root cause.\r\nIndividual SOC cybersecurity providers offer different suites of products and services. However, there is a core set of operational functions that a SOC must perform in order to add value to an organization.\r\n<ol><li><span style=\"font-weight: bold;\">Asset Survey:</span> In order for a SOC to help a company stay secure, they must have a complete understanding of what resources they need to protect. Otherwise, they may not be able to protect the full scope of the network. An asset survey should identify every server, router, firewall under enterprise control, as well as any other cybersecurity tools actively in use.</li><li><span style=\"font-weight: bold;\">Log Collection:</span> Data is the most important thing for a SOC to function properly and logs serve as the key source of information regarding network activity. The SOC should set up direct feeds from enterprise systems so that data is collected in real-time. Obviously, humans cannot digest such large amounts of information, which is why log scanning tools powered by artificial intelligence algorithms are so valuable for SOCs, though they do pose some interesting side effects that humanity is still trying to iron out.</li><li><span style=\"font-weight: bold;\">Preventative Maintenance:</span> In the best-case scenario, the SOC is able to prevent cyberattacks from occurring by being proactive with their processes. This includes installing security patches and adjusting firewall policies on a regular basis. Since some cyberattacks actually begin as insider threats, a SOC must also look within the organization for risks also.</li><li><span style=\"font-weight: bold;\">Continuous Monitoring:</span> In order to be ready to respond to a cybersecurity incident, the SOC must be vigilant in its monitoring practices. A few minutes can be the difference between blocking an attack and letting it take down an entire system or website. SOC tools run scans across the company’s network to identify potential threats and other suspicious activity.</li><li><span style=\"font-weight: bold;\">Alert Management:</span> Automated systems are great at finding patterns and following scripts. But the human element of a SOC proves it's worth it when it comes to analyzing automated alerts and ranking them based on their severity and priority. SOC staff must know what responses to take and how to verify that an alert is legitimate.</li><li><span style=\"font-weight: bold;\">Root Cause Analysis:</span> After an incident occurs and is resolved, the job of the SOC is just beginning. Cybersecurity experts will analyze the root cause of the problem and diagnose why it occurred in the first place. This feeds into a process of continuous improvement, with security tools and rules being modified to prevent future occurrences of the same incident.</li><li><span style=\"font-weight: bold;\">Compliance Audits:</span> Companies want to know that their data and systems are safe but also that they are being managed in a lawful manner. SOC providers must perform regular audits to confirm their compliance in the regions where they operate. What is a SOC report and what is a SOC audit? Anything that pulls data or records from cybersecurity functions of an organization. What is SOC 2? It’s a special auditing procedure related to information security and privacy.</li></ol>","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/SOC_-_Situation_Centre.png","alias":"soc-situation-centre"},"80":{"id":80,"title":"VMS - Video Management Solution","description":"Video management systems and video analytics are intellectual elements of a comprehensive security system for any organization and enterprise.\r\nVideo Management Systems (VMS) provide video camera management, video stream distribution and image display to security monitors, quick and effective incident response, access rights to control video cameras and video archive and prompt notification of security incidents.\r\nVideo analytics is a key element of any video surveillance system, as it allows you to automate the main tasks of protecting objects and territories, namely, the prediction and detection of potential risks, tracking and recognition of objects.\r\nThe images from video surveillance cameras are transmitted to the video content storage server, and using specialized software, they are automatically analyzed and processed, and the results are output to the administrator or head of the security system.","materialsDescription":"<span style=\"font-weight: bold;\">What is Video Management Software?</span>\r\nVideo management software (VMS) is a part of a video surveillance system that allows the user to access real-time videos, record, store and playback recorded videos and derive useful insights of the surveillance site.\r\n<span style=\"font-weight: bold;\">When to upgrade a Video Surveillance System?</span>\r\nCurrent Video Management Systems are capable of offering much more than just surveillance, hence, upgrading a VMS system becomes as important as upgrading the other assets of the business. A VMS system can be upgraded when an organization is:\r\n<ul><li>Using a traditional CCTV surveillance system (Old equipment and cameras)</li><li>Incurring increased maintenance costs of the existing surveillance system</li><li>Expanding from Single site to multiple sites (Small to medium to large-sized enterprises)</li><li>In the need of Intelligent Video Analytics for monitoring sites, employees or business processes</li><li>Requiring Video Analytics to improve the site operations to benefit the customers, VMS users or employees</li><li>In need of VMS system equipment standardization</li></ul>\r\n<span style=\"font-weight: bold;\">What are the factors to consider while selecting video surveillance cameras for the VMS System?</span>\r\nVideo surveillance cameras come in a wide range of sizes, shapes, features, and functions, which are designed to perform in diverse environmental conditions at surveillance sites. There are a few things that users must consider while selecting video surveillance cameras for their VMS system. Users must check:\r\n<ul><li>The camera resolution (image quality)</li><li>Indoor or outdoor camera compatibility</li><li>Wired or wireless cameras</li><li>Light sensitivity of the camera (ability of a surveillance camera to work in low light)</li><li>Shape of the camera (box type, bullet camera or dome camera)</li><li>Frame rate (more frames per second –fps defines video clarity)</li></ul>\r\n<span style=\"font-weight: bold;\">Why should enterprises switch from traditional CCTV systems to cloud-based Video Management Systems?</span>\r\nTraditional CCTV systems are just analog devices with limited functionality to monitor and track the events in the camera vicinity, whereas new age cloud-based video management systems are smart enough to record, store, playback, and analyze the captured events in real-time and later. Cloud-based Video Surveillance systems are equipped with high-quality IP cameras, which provide a high-quality image with better fps for the system network. Storage is never an issue with these systems as all the data is stored on the cloud and can be fetched whenever required. Cloud-based video management systems are easy to install as users can just plug-and-play these devices for small setups. These systems are easily customizable in terms of camera numbers, software features, types of video analytics, etc.\r\n<span style=\"font-weight: bold;\">What are different deployment types of Video Management Software?</span>\r\nVideo Management Software can be classified into three deployment types:\r\n<span style=\"font-style: italic;\">On-premise VMS.</span> On-premise VMS solutions are best suited for managing video surveillance at a single site. All the streaming, recording and management servers, storage devices and applications are installed locally on-site. This allows user to manage their security and connected device ecosystem from the site itself.\r\n<span style=\"font-style: italic;\">Cloud based VMS.</span> The cloud-based VMS, unlike the on-premise VMS, possesses higher flexibility and scalability. It allows the user to manage multiple sites, all at the same time – from any location and at any time.\r\n<span style=\"font-style: italic;\">Hybrid VMS.</span> A hybrid VMS solution is a flexible surveillance solution, which generally comes with the capability of managing both analog and IP video signals simultaneously. It allows the enterprises to have a traditional VMS solution coexist with the functionalities of cloud Video Surveillance.\r\n<span style=\"font-weight: bold;\">What are the benefits of microservice architecture in cloud video management software?</span>\r\nMicroservice architecture based cloud video management software overcomes the limitations of a traditionally designed VMS solution (monolithic architecture) and addresses the evolving security needs of the business. Let’s see how it benefits cloud video management software:\r\n<span style=\"font-style: italic;\">Modularity:</span> Micro-services allows video management software to be designed as a suite of various independent modules that remain integrated through APIs.\r\n<span style=\"font-style: italic;\">Scalability:</span> Cloud-based video management software on microservices is easily scalable, i.e., any of the new services can be added or existing services can be upgraded in the software without affecting the video surveillance.\r\n<span style=\"font-style: italic;\">Flexibility: </span>Through microservice based cloud video management software, users can opt for any new VMS services to be added or removed in their existing software according to their evolving business needs. This can be of great help to the users, as they can follow the pay per feature business model. It also allows developers to choose the programming languages for its development.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/VMS_-_Video_Management_Solution.png","alias":"vms-video-management-solution"},"204":{"id":204,"title":"Managed Detection and Response","description":" MDR, which stands for Managed Detection &amp; Response, is an all-encompassing threat detection system, which arose from the need for small/medium-sized organizations who lack resources to be able to monitor their network systems in-house. It provides a cost-effective alternative to SIEM (Security Information and Event Management).\r\nEveryday, the capabilities of attackers get more sophisticated and the volume of alerts becomes overwhelming and unmanageable. In-house teams might struggle to analyze and log data, which makes it harder than ever to determine if these threats are harmful. MDR can put a stop to attacks before they even happen. MDR technology monitors your systems and detects any unusual behavior, whilst our expert team responds to the threats detected within your business.\r\nMDR offers real-time threat intelligence, and is able to analyse behaviour which can be missed by traditional endpoint security technology. MDR also provides rapid identification of known threats, which in turn minimises overall attacks. Having remote incident investigation will minimise damage to your business, and will allow you to get back to work in no time. It’s important to note that using MDR services will allow third party access to your company's data. You need to consider working with a provider who understands and respects your data policy.","materialsDescription":" <span style=\"font-weight: bold;\">What is Managed Detection and Response?</span>\r\nManaged Detection and Response (MDR) is a managed cybersecurity service that provides intrusion detection of malware and malicious activity in your network, and assists in rapid incident response to eliminate those threats with succinct remediation actions. MDR typically combines a technology solution with outsourced security analysts that extend your technologies and team.\r\n<span style=\"font-weight: bold;\">Isn’t that What MSSPs or Managed SIEMs Do?</span>\r\nNo. Managed Security Service Providers (MSSPs) monitor network security controls and may send alerts when anomalies are identified. MSSPs typically do not investigate the anomalies to eliminate false positives, nor do they respond to real threats. This means that abnormalities in network usage are forwarded to your IT personnel who must then dig through the data to determine if there is a real threat and what to do about it.\r\n<span style=\"font-weight: bold;\">Doesn’t My Firewall Protect My Network?</span>\r\nFirewalls and other preventive forms of cybersecurity are very important and effective at preventing basic cyberattacks. However, over the past decade, it has become clear that preventive cybersecurity technologies are not enough to secure an organization’s network. Further, they are yet another source of alerts, log messages, and events that contribute to the “alert fatigue” being universally suffered today. Recent major hacks such as the Marriot Hack of 2018, the Anthem Hack of 2015, and the Target Hack of 2013 demonstrate how easily cybercriminals can breach networks at enterprise organizations to steal millions of credit card numbers, medical records, and other forms of PII/PHI.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Endpoint_Detection_and_Response.png","alias":"managed-detection-and-response"},"223":{"id":223,"title":"Data Access, Analysis, and Delivery Software","description":" Data access, analysis and delivery software are end-user oriented tools for ad hoc data access, analysis and reporting as well as production reporting. These products are most commonly used by information consumers or power users rather than professional programmers.\r\nThe processing and analysis of group data is a flexible, iterative method for processing and analyzing data to efficiently provide predictive analytics solutions and intelligent applications. This allows you to improve learning and teamwork. It contains selected recommendations and structures from Microsoft and other developers in the industry that ensure the successful implementation of data processing and analysis solutions. All this is to help companies take full advantage of their analytics software.","materialsDescription":"<span style=\"font-weight: bold; \">Data access</span>\r\nData access is a generic term referring to a process which has both an IT-specific meaning and other connotations involving access rights in a broader legal and/or political sense. In the former it typically refers to software and activities related to storing, retrieving, or acting on data housed in a database or other repository. Two fundamental types of data access exist:\r\n<ol><li>sequential access (as in magnetic tape, for example)</li><li>random access (as in indexed media)</li></ol>\r\nData access crucially involves authorization to access different data repositories. Data access can help distinguish the abilities of administrators and users. For example, administrators may have the ability to remove, edit and add data, while general users may not even have &quot;read&quot; rights if they lack access to particular information.\r\nHistorically, each repository (including each different database, file system, etc.), might require the use of different methods and languages, and many of these repositories stored their content in different and incompatible formats.\r\nOver the years standardized languages, methods, and formats, have developed to serve as interfaces between the often proprietary, and always idiosyncratic, specific languages and methods. Such standards include SQL (1974- ), ODBC (ca 1990- ), JDBC, XQJ, ADO.NET, XML, XQuery, XPath (1999- ), and Web Services.\r\nSome of these standards enable translation of data from unstructured (such as HTML or free-text files) to structured (such as XML or SQL).\r\nStructures such as connection strings and DBURLs[1] can attempt to standardise methods of connecting to databases.\r\n<span style=\"font-weight: bold; \">A program for data analysis</span>\r\nA data analysis program is a specially developed software that can analyze any information. This is usually a database program. It is within the database that you can store any information in any amount. A functional program allows incoming and stored data to analyze. Software development can be done for any tasks, which means that the program for data analysis can be customized for any activity. If, for example, you have a trade organization, then your data analysis program will analyze products, customers, funds, product balance, and more.\r\n<span style=\"font-weight: bold;\">On-demand software delivery</span>\r\nA type of software delivery service where the software is provided to the customer through a network (such as the Internet) as a service. On-demand software delivery is also called software on-demand. The terms on-demand software and Software as a Service (SaaS) are often used interchangeably.\r\nData access, analysis and delivery software are end-user oriented tools for ad hoc data access, analysis and reporting as well as production reporting.&nbsp; These products are most commonly used by information consumers or power users rather than professional programmers.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Data_Access__Analysis__and_Delivery_Software1.png","alias":"data-access-analysis-and-delivery-software"},"225":{"id":225,"title":"End-User Query, Reporting, and Analysis","description":" Class systems of Query &amp; Reporting are designed to form queries to information systems in user terms, as well as their execution, integration of data from different sources, viewing data with the possibilities of detailing and summarizing and building full-fledged reports, both on-screen and printed. Visualization of query results can be presented to the user in various forms - flat or multidimensional tables, graphs, charts, various specialized interfaces.\r\nEnd-user tools for querying and building reports are delivered in two ways:\r\n<ul><li>as part of OLAP-systems</li><li>in the form of specialized Query &amp; Reporting</li></ul>\r\nVirtually every OLAP class system is equipped with Query &amp; Reporting. These funds can be either embedded in the main product or separated into a separate product.\r\nThere are also specialized systems for generating and distributing reports. At the same time, these systems incorporate their own OLAP-means. Therefore, to draw a clear line between OLAP-systems and systems of class Query &amp; Reporting is almost impossible.","materialsDescription":" <span style=\"font-weight: bold; \">What are the reporting tools?</span>\r\nReporting tools are widely used to support decision making and to measure organizational and team performance. Companies use them for financial consolidation, for evaluation of strategies and policies and often just for plain reporting. Today most of these tools are integrated with Business Intelligence tools.\r\n<span style=\"font-weight: bold; \">What are the advantages of these tools for your organization?</span>\r\nReporting tools allow companies to create attractive reports easily. In tabular or graphical format. With data from Excel, a data warehouse or the organization’s ERP system. With the reports containing the right information, people are able to manage and improve the business processes more easily.\r\n<span style=\"font-weight: bold; \">Which reporting tools are available in the market?</span>\r\nThere are many Business Intelligence Reporting tools in the market available. This list of reporting tools shows you a complete overview of all the major tools currently available and thoroughly studied by our industry analysts. To name a few: Cognos Query and reporting, Oracle Enterprise Reporting, Crystal Reports, Microsoft Reporting Services (SSRS), etc.\r\n<span style=\"font-weight: bold; \">Is there a difference between reporting tools and BI tools?</span>\r\nAlmost every company, large or small, needs a reporting tool or they have already one in place. But, what is the difference between reporting software and Business Intelligence tools? They are not the same. In general reporting tools tell us where we have been but are not very good at analyzing data (at real time) and telling us where we are going (predictive).\r\n<span style=\"font-weight: bold;\">What is the difference between a query and a report?</span>\r\nA query is a way to create a list of accounts or journal entries that match your criteria. Requests serve as an advanced search engine that finds and groups accounts or journal entries and can only create a list.\r\nA report is a detailed report of a group of accounts or journal entries. Reports analyze data and are designed to calculate and present data in a more formal form.\r\nTypically, a query finds information in the database for you, and a report is a more powerful way to display and analyze information about the accounts or log entries you want to view.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/End-User_Query__Reporting__and_Analysis.png","alias":"end-user-query-reporting-and-analysis"},"227":{"id":227,"title":"Advanced Analytics Software","description":" <span style=\"font-weight: bold;\">Advanced analytics</span> is a part of data science that uses high-level methods and tools to focus on projecting future trends, events, and behaviors. This gives organizations the ability to perform advanced statistical models such as ‘what-if’ calculations, as well as future-proof various aspects of their operations.\r\nThe term is an umbrella for several sub-fields of analytics that work together in their predictive capabilities.\r\nThe major areas that make up advanced analytics are predictive data analytics, big data, and data mining. The process of advanced analytics includes all three areas at various times.\r\n<span style=\"font-weight: bold;\">Data mining</span> is a key aspect of advanced analytics, providing the raw data that will be used by both big data and predictive analytics. <span style=\"font-weight: bold;\">Big data analytics</span> are useful in finding existing insights and creating connections between data points and sets, as well as cleaning data.\r\nFinally, <span style=\"font-weight: bold;\">predictive analytics</span> can use these clean sets and existing insights to extrapolate and make predictions and projections about future activity, trends, and consumer behaviors.\r\nAdvanced analytics also include newer technologies such as machine learning and artificial intelligence, semantic analysis, visualizations, and even neural networks. Taken together, they help advanced analytics software create an accurate enough canvas to make reliable predictions and generate actionable BI insights on a deeper level.","materialsDescription":"<h1 class=\"align-center\">A list of tips on how to manage the process of building an advanced analytics program</h1>\r\n<ul><li>Start with a proof-of-concept project to demonstrate the potential business value of analytics applications.</li><li>Take training seriously. New data management and analytics skills likely will be needed, especially if big data platforms and tools like SAS advanced analytics tools are involved.</li><li>Develop processes to ensure that business units are ready to act on analytical findings so the work of data scientists and other analysts doesn't go to waste.</li><li>Monitor and assess advanced and predictive analytics software on a regular basis to make sure the data being analyzed is still relevant and the analytical models being run against it are still valid.</li></ul>\r\n<h1 class=\"align-center\">Advanced analytics tools</h1>\r\nThere are a variety of advanced analytics tools to choose from that offer different advantages based on the use case. They generally break down into two categories: open source and proprietary.\r\nOpen source tools have become a go-to option for many data scientists doing machine learning and prescriptive analytics. They include programming languages, as well as computing environments, including Hadoop and Spark. Users typically say they like open source advanced analytics tools because they are generally inexpensive to operate, offer strong functionality and are backed by a user community that continually innovates the tools.\r\nOn the proprietary side, vendors including Microsoft, IBM and the SAS Institute all offer advanced analytics tools. Most require a deep technical background and understanding of mathematical techniques.\r\nIn recent years, however, a crop of self-service analytics tools has matured to make functionality more accessible to business users. Tableau, in particular, has become a common tool. While its functionality is more limited than deeper technical tools, it does enable users to conduct cluster analyses and other advanced analyses.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Advanced_Analytics_Software.png","alias":"advanced-analytics-software"},"229":{"id":229,"title":"Spatial Information Management Software","description":" A spatial database is a database that is optimized for storing and querying data that represents objects defined in a geometric space. Most spatial databases allow the representation of simple geometric objects such as points, lines and polygons. Some spatial databases handle more complex structures such as 3D objects, topological coverages, linear networks, and TINs. While typical databases have developed to manage various numeric and character types of data, such databases require additional functionality to process spatial data types efficiently, and developers have often added geometry or feature data types. The Open Geospatial Consortium (OGC) developed the Simple Features specification (first released in 1997) and sets standards for adding spatial functionality to database systems. The SQL/MM Spatial ISO/IEC standard is a part the SQL/MM multimedia standard and extends the Simple Features standard with data types that support circular interpolations.\r\nA geodatabase (also geographical database and geospatial database) is a database of geographic data, such as countries, administrative divisions, cities, and related information. Such databases can be useful for websites that wish to identify the locations of their visitors for customization purposes.\r\nDatabase systems use indexes to quickly look up values; however, this way of indexing data is not optimal for spatial queries. Instead, spatial databases use a spatial index to speed up database operations.\r\nIn addition to typical SQL queries such as SELECT statements, spatial databases can perform a wide variety of spatial operations. The following operations and many more are specified by the Open Geospatial Consortium standard:\r\n<ul><li>Spatial Measurements: Computes line length, polygon area, the distance between geometries, etc.</li><li>Spatial Functions: Modify existing features to create new ones, for example by providing a buffer around them, intersecting features, etc.</li><li>Spatial Predicates: Allows true/false queries about spatial relationships between geometries. Examples include &quot;do two polygons overlap&quot; or 'is there a residence located within a mile of the area we are planning to build the landfill?'</li><li>Geometry Constructors: Creates new geometries, usually by specifying the vertices (points or nodes) which define the shape.</li><li>Observer Functions: Queries which return specific information about a feature such as the location of the center of a circle.</li></ul>\r\nSome databases support only simplified or modified sets of these operations, especially in cases of NoSQL systems like MongoDB and CouchDB.","materialsDescription":"<span style=\"font-weight: bold;\">What is the spatial index?</span>\r\nSpatial indices are used by spatial databases (databases which store information related to objects in space) to optimize spatial queries. Conventional index types do not efficiently handle spatial queries such as how far two points differ, or whether points fall within a spatial area of interest. Common spatial index methods include:\r\n<ul><li>Geohash</li><li>HHCode</li><li>Grid (spatial index)</li><li>Z-order (curve)</li><li>Quadtree</li><li>Octree</li><li>UB-tree</li><li>R-tree: Typically the preferred method for indexing spatial data.[citation needed] Objects (shapes, lines and points) are grouped using the minimum bounding rectangle (MBR). Objects are added to an MBR within the index that will lead to the smallest increase in its size.</li><li>R+ tree</li><li>R* tree</li><li>Hilbert R-tree</li><li>X-tree</li><li>kd-tree</li><li>m-tree – an m-tree index can be used for the efficient resolution of similarity queries on complex objects as compared using an arbitrary metric.</li><li>Binary space partitioning (BSP-Tree): Subdividing space by hyperplanes.</li></ul>","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Spatial_Information_Management_Software.png","alias":"spatial-information-management-software"},"283":{"id":283,"title":"Content Analytics, Discovery, and Cognitive Software","description":"<span style=\"font-weight: bold; \">Content Analytics</span> comprises of range of search and reporting technologies which can provide identical levels of business intelligence and strategic value for unstructured data. Content analytics for unstructured information includes social media monitoring, reputation monitoring, and sentiment analysis. <span style=\"font-weight: bold; \">Content analytics software</span> uses natural language queries, trends analysis, predictive analytics and contextual discovery to reveal trends and patterns for the company's unstructured data.\r\n<span style=\"font-weight: bold; \">Discovery tools</span> are the search tools that analyse contents for its likely relevancy to a process, by linking names, time periods or terms used. Discovery tools can also extend to legal hold and partitioning of content for further scrutiny. Various types of discovery tools include search engines, auto-categorization, and information visualization tools.\r\n<span style=\"font-weight: bold;\">Cognitive computing software</span> makes context computable by identifying and extracting context features such as hour, location, task, history or profile in structured way for an individual or an application engaged in a specific process at definite time and place. Cognitive computing technologies and platforms includes expert assistance software.\r\n<span style=\"font-weight: bold;\">Content Analytics, Discovery and Cognitive Systems,</span> collectively covers the market and technologies that access, analyse, organize, and provides advisory services related to a range of unstructured data. Cognitive systems leverages large amounts of structured and unstructured data and content analytics tools, along with several infrastructure technologies to answer questions, provide recommendations and directions. ","materialsDescription":"<h1 class=\"align-center\">What are Content Analytics?</h1>\r\nContent analytics is one way that brands can measure the success of their digital content; it involves analyzing data from both inbound and outbound collateral to figure out what’s working and what’s not. After all, no one wants to spend hundreds or even thousands of dollars on content that isn’t resonating.\r\nIt should come as no surprise, then, that 75 percent of enterprises think content analytics can provide real business insight: What are your customers most interested in reading about? What format generates the most engagement? You can use answers to these questions to help you decide what content you should be producing, how to present it (quiz, paid ad, slideshow, blog post, etc.), and where/when to post it for the best results. If utilized correctly, content analytics can offer brands a way to build customer loyalty and boost revenue.\r\nAdvanced content analytics strategies should help you to look beyond the numbers and to focus on taking action. Content analytics is not a mirror reflecting how your company’s content is performing; rather, it is but one tool that can help steer you towards actionable solutions and more effective content choices.\r\nMetrics provided by content analytics, and the actions you take based off that data, can help you optimize conversion rates. In addition to tweaking your content strategy, you can also build a conversion optimization strategy by testing calls-to-action (CTAs), headlines, subscription forms, etc.\r\n<h1 class=\"align-center\"><span style=\"font-weight: bold; \">What are the features of a cognitive computing solution?</span></h1>\r\nWith the present state of cognitive function computing, basic solution can play an excellent role of an assistant or virtual advisor. Siri, Google assistant, Cortana, and Alexa are good examples of personal assistants. Virtual advisor such as Dr. AI by HealthTap is a cognitive solution. It relies on individual patients’ medical profiles and knowledge gleaned from 105,000 physicians. It compiles a prioritized list of the symptoms and connects to a doctor if required. Now, experts are working on implementing cognitive solutions in enterprise systems. Some use cases are fraud detection using machine learning, predictive analytics solution, predicting oil spills in Oil and Gas production cycle etc.\r\nThe purpose of cognitive computing is the creation of computing frameworks that can solve complicated problems without constant human intervention. In order to implement cognitive function computing in commercial and widespread applications, Cognitive Computing consortium has recommended the following features for the computing systems:\r\n<span style=\"font-weight: bold; \">Adaptive.</span>This is the first step in making a machine learning based cognitive system. The solutions should mimic the ability of the human brain to learn and adapt from the surroundings. The systems can’t be programmed for an isolated task. It needs to be dynamic in data gathering, understanding goals, and requirements.\r\n<span style=\"font-weight: bold; \">Interactive.</span>Similar to brain the cognitive solution must interact with all elements in the system – processor, devices, cloud services and user. Cognitive systems should interact bi-directionally. It should understand human input and provide relevant results using natural language processing and deep learning. Some skilled intelligent chatbots such as Mitsuku have already achieved this feature.\r\n<span style=\"font-weight: bold; \">Iterative and stateful.</span>The system should “remember” previous interactions in a process and return information that is suitable for the specific application at that point in time. It should be able to define the problem by asking questions or finding an additional source. This feature needs a careful application of the data quality and validation methodologies in order to ensure that the system is always provided with enough information and that the data sources it operates on to deliver reliable and up-to-date input.\r\n<span style=\"font-weight: bold; \">Contextual.</span>They must understand, identify, and extract contextual elements such as meaning, syntax, time, location, appropriate domain, regulations, user’s profile, process, task, and goal. They may draw on multiple sources of information, including both structured and unstructured digital information, as well as sensory inputs (visual, gestural, auditory, or sensor-provided). ","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Content_Analytics_Discovery_and_Cognitive_Software.png","alias":"content-analytics-discovery-and-cognitive-software"},"465":{"id":465,"title":"UEBA - User and Entity Behavior Analytics","description":"Developments in UBA technology led Gartner to evolve the category to user and entity behavior analytics (UEBA). In September 2015, Gartner published the Market Guide for User and Entity Analytics by Vice President and Distinguished Analyst, Avivah Litan, that provided a thorough definition and explanation. UEBA was referred to in earlier Gartner reports but not in much depth. Expanding the definition from UBA includes devices, applications, servers, data, or anything with an IP address. It moves beyond the fraud-oriented UBA focus to a broader one encompassing &quot;malicious and abusive behavior that otherwise went unnoticed by existing security monitoring systems, such as SIEM and DLP.&quot; The addition of &quot;entity&quot; reflects that devices may play a role in a network attack and may also be valuable in uncovering attack activity. &quot;When end users have been compromised, malware can lay dormant and go undetected for months. Rather than trying to find where the outsider entered, UEBAs allow for quicker detection by using algorithms to detect insider threats.&quot;\r\nParticularly in the computer security market, there are many vendors for UEBA applications. They can be &quot;differentiated by whether they are designed to monitor on-premises or cloud-based software as a service (SaaS) applications; the methods in which they obtain the source data; the type of analytics they use (i.e., packaged analytics, user-driven or vendor-written), and the service delivery method (i.e., on-premises or a cloud-based).&quot; According to the 2015 market guide released by Gartner, &quot;the UEBA market grew substantially in 2015; UEBA vendors grew their customer base, market consolidation began, and Gartner client interest in UEBA and security analytics increased.&quot; The report further projected, &quot;Over the next three years, leading UEBA platforms will become preferred systems for security operations and investigations at some of the organizations they serve. It will be—and in some cases already is—much easier to discover some security events and analyze individual offenders in UEBA than it is in many legacy security monitoring systems.&quot;","materialsDescription":"<span style=\"font-weight: bold;\">What is UEBA?</span>\r\nHackers can break into firewalls, send you e-mails with malicious and infected attachments, or even bribe an employee to gain access into your firewalls. Old tools and systems are quickly becoming obsolete, and there are several ways to get past them.\r\nUser and entity behavior analytics (UEBA) give you more comprehensive way of making sure that your organization has top-notch IT security, while also helping you detect users and entities that might compromise your entire system.\r\nUEBA is a type of cybersecurity process that takes note of the normal conduct of users. In turn, they detect any anomalous behavior or instances when there are deviations from these “normal” patterns. For example, if a particular user regularly downloads 10 MB of files every day but suddenly downloads gigabytes of files, the system would be able to detect this anomaly and alert them immediately.\r\nUEBA uses machine learning, algorithms, and statistical analyses to know when there is a deviation from established patterns, showing which of these anomalies could result in, potentially, a real threat. UEBA can also aggregate the data you have in your reports and logs, as well as analyze the file, flow, and packet information.\r\nIn UEBA, you do not track security events or monitor devices; instead, you track all the users and entities in your system. As such, UEBA focuses on insider threats, such as employees who have gone rogue, employees who have already been compromised, and people who already have access to your system and then carry out targeted attacks and fraud attempts, as well as servers, applications, and devices that are working within your system.\r\n<span style=\"font-weight: bold;\">What are the benefits of UEBA?</span>\r\nIt is the unfortunate truth that today's cybersecurity tools are fast becoming obsolete, and more skilled hackers and cyber attackers are now able to bypass the perimeter defenses that are used by most companies. In the old days, you were secure if you had web gateways, firewalls, and intrusion prevention tools in place. This is no longer the case in today’s complex threat landscape, and it’s especially true for bigger corporations that are proven to have very porous IT perimeters that are also very difficult to manage and oversee.\r\nThe bottom line? Preventive measures are no longer enough. Your firewalls are not going to be 100% foolproof, and hackers and attackers will get into your system at one point or another. This is why detection is equally important: when hackers do successfully get into your system, you should be able to detect their presence quickly in order to minimize the damage.\r\n<span style=\"font-weight: bold;\">How Does UEBA Work?</span>\r\nThe premise of UEBA is actually very simple. You can easily steal an employee’s user name and password, but it is much harder to mimic the person’s normal behavior once inside the network.\r\nFor example, let’s say you steal Jane Doe’s password and user name. You would still not be able to act precisely like Jane Doe once in the system unless given extensive research and preparation. Therefore, when Jane Doe’s user name is logged in to the system, and her behavior is different than that of typical Jane Doe, that is when UEBA alerts start to sound.\r\nAnother relatable analogy would be if your credit card was stolen. A thief can pickpocket your wallet and go to a high-end shop and start spending thousands of dollars using your credit card. If your spending pattern on that card is different from the thief’s, the company’s fraud detection department will often recognize the abnormal spending and block suspicious purchases, issuing an alert to you or asking you to verify the authenticity of a transaction.\r\nAs such, UEBA is a very important component of IT security, allowing you to:\r\n1. Detect insider threats. It is not too far-fetched to imagine that an employee, or perhaps a group of employees, could go rogue, stealing data and information by using their own access. UEBA can help you detect data breaches, sabotage, privilege abuse and policy violations made by your own staff.\r\n2. Detect compromised accounts. Sometimes, user accounts are compromised. It could be that the user unwittingly installed malware on his or her machine, or sometimes a legitimate account is spoofed. UEBA can help you weed out spoofed and compromised users before they can do real harm.\r\n3. Detect brute-force attacks. Hackers sometimes target your cloud-based entities as well as third-party authentication systems. With UEBA, you are able to detect brute-force attempts, allowing you to block access to these entities.\r\n4. Detect changes in permissions and the creation of super users. Some attacks involve the use of super users. UEBA allows you to detect when super users are created, or if there are accounts that were granted unnecessary permissions.\r\n5. Detect breach of protected data. If you have protected data, it is not enough to just keep it secure. You should know when a user accesses this data when he or she does not have any legitimate business reason to access it.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/icon_User_and_Entity_Behavior_Analytics.png","alias":"ueba-user-and-entity-behavior-analytics"}},"companySizes":"101 to 500 Employees","companyUrl":"https://www.knightscope.com/","countryCodes":[],"certifications":[],"isSeller":true,"isSupplier":true,"isVendor":true,"presenterCodeLng":"","seo":{"title":"Knightscope","keywords":"","description":"<b>Knightscope’s</b> long-term ambition is to make the United States of America the safest country in the world, changing everything for everyone. Our vision is to develop a technology stack to predict and prevent crime utilizing autonomous robots, analytics a","og:title":"Knightscope","og:description":"<b>Knightscope’s</b> long-term ambition is to make the United States of America the safest country in the world, changing everything for everyone. 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Working together with human eyes, you’ll be better equipped to keep areas such as parking lots, corporate campuses and hospitals safe autonomously.\r\n<b>Features:</b>\r\n<b>360 Degree HD Video Streaming</b>\r\nThe K5 was able to provide eye-level high definition video of the entire incident, providing the key necessary information in a timely manner, transmitted the information to law enforcement, which was received in time to arrest the suspect.\r\n<b>People Detection</b>\r\nPerhaps at your sensitive facility, there literally should be no humans during certain times of the day, say 10pm - 5am. The K5 can be on the lookout for any people during those times and proactively make pre-recorded announcements to deter negative behavior.\r\n<b>Automatic License Plate Recognition</b>\r\nUtilizing the KSOC, clients can whitelist or blacklist license plates depending on the needs of your location. The user can also automatically check for dwell times of plates (i.e., a parking meter) to deter overnight parking or assist with BOLOs (Be On The Lookout).\r\n<b>Thermal Anomaly Detection</b>\r\n<ul> <li>Early Detection of Potential Fire Threat</li> <li>Unauthorized Individuals in Restricted Areas</li> <li>Suspicious Persons After Hours</li> <li>Running Vehicles</li> <li>Positive Identification Capture</li> </ul>\r\n<b>Automatic Signal Detection</b>\r\nCombining this capability with Automatic License Plate Recognition as well as BOLO mug shot upload capabilities allows for unprecedented new capabilities in deterring unwanted behavior at your location.\r\n<b>Two-Way Intercom</b>\r\nA Two-Way Intercom (human-to-human voice interaction) call can be initiated either by the KSOC user or a human presses the button on a machine. The button press can be configured to call a certain number to further assist your security team.\r\n<b>Live Audio Broadcast</b>\r\nLive Audio Broadcast, similar to public address system, allows a KSOC user to throw their voice through a machine or machines providing new alerting capabilities.\r\n<b>Pre-recorded Broadcast Messages</b>\r\nPre-Recorded Messages may be played manually by the KSOC user or set automatically to play randomly, by time, by location or by detection, further automating visitor, patron, or employee engagement.","shortDescription":"Access real-time data around the clock via our desktop or mobile apps, ensuring you’ll always have the power of our technology at your fingertips. Knightscope has you covered 24/7/365\r\n\r\n","type":null,"isRoiCalculatorAvaliable":false,"isConfiguratorAvaliable":false,"bonus":100,"usingCount":15,"sellingCount":13,"discontinued":0,"rebateForPoc":0,"rebate":0,"seo":{"title":"Knightscope K5","keywords":"","description":"The Knightscope K5 is primarily an outdoor machine which runs 24/7 on its own including autonomously recharging itself without any human intervention. It is best suited for securing large outdoor spaces. Working together with human eyes, you’ll be better equi","og:title":"Knightscope K5","og:description":"The Knightscope K5 is primarily an outdoor machine which runs 24/7 on its own including autonomously recharging itself without any human intervention. It is best suited for securing large outdoor spaces. 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It contains selected recommendations and structures from Microsoft and other developers in the industry that ensure the successful implementation of data processing and analysis solutions. All this is to help companies take full advantage of their analytics software.","materialsDescription":"<span style=\"font-weight: bold; \">Data access</span>\r\nData access is a generic term referring to a process which has both an IT-specific meaning and other connotations involving access rights in a broader legal and/or political sense. In the former it typically refers to software and activities related to storing, retrieving, or acting on data housed in a database or other repository. Two fundamental types of data access exist:\r\n<ol><li>sequential access (as in magnetic tape, for example)</li><li>random access (as in indexed media)</li></ol>\r\nData access crucially involves authorization to access different data repositories. Data access can help distinguish the abilities of administrators and users. For example, administrators may have the ability to remove, edit and add data, while general users may not even have &quot;read&quot; rights if they lack access to particular information.\r\nHistorically, each repository (including each different database, file system, etc.), might require the use of different methods and languages, and many of these repositories stored their content in different and incompatible formats.\r\nOver the years standardized languages, methods, and formats, have developed to serve as interfaces between the often proprietary, and always idiosyncratic, specific languages and methods. Such standards include SQL (1974- ), ODBC (ca 1990- ), JDBC, XQJ, ADO.NET, XML, XQuery, XPath (1999- ), and Web Services.\r\nSome of these standards enable translation of data from unstructured (such as HTML or free-text files) to structured (such as XML or SQL).\r\nStructures such as connection strings and DBURLs[1] can attempt to standardise methods of connecting to databases.\r\n<span style=\"font-weight: bold; \">A program for data analysis</span>\r\nA data analysis program is a specially developed software that can analyze any information. This is usually a database program. It is within the database that you can store any information in any amount. A functional program allows incoming and stored data to analyze. Software development can be done for any tasks, which means that the program for data analysis can be customized for any activity. If, for example, you have a trade organization, then your data analysis program will analyze products, customers, funds, product balance, and more.\r\n<span style=\"font-weight: bold;\">On-demand software delivery</span>\r\nA type of software delivery service where the software is provided to the customer through a network (such as the Internet) as a service. On-demand software delivery is also called software on-demand. The terms on-demand software and Software as a Service (SaaS) are often used interchangeably.\r\nData access, analysis and delivery software are end-user oriented tools for ad hoc data access, analysis and reporting as well as production reporting.&nbsp; These products are most commonly used by information consumers or power users rather than professional programmers.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Data_Access__Analysis__and_Delivery_Software1.png"},{"id":229,"title":"Spatial Information Management Software","alias":"spatial-information-management-software","description":" A spatial database is a database that is optimized for storing and querying data that represents objects defined in a geometric space. Most spatial databases allow the representation of simple geometric objects such as points, lines and polygons. Some spatial databases handle more complex structures such as 3D objects, topological coverages, linear networks, and TINs. While typical databases have developed to manage various numeric and character types of data, such databases require additional functionality to process spatial data types efficiently, and developers have often added geometry or feature data types. The Open Geospatial Consortium (OGC) developed the Simple Features specification (first released in 1997) and sets standards for adding spatial functionality to database systems. The SQL/MM Spatial ISO/IEC standard is a part the SQL/MM multimedia standard and extends the Simple Features standard with data types that support circular interpolations.\r\nA geodatabase (also geographical database and geospatial database) is a database of geographic data, such as countries, administrative divisions, cities, and related information. Such databases can be useful for websites that wish to identify the locations of their visitors for customization purposes.\r\nDatabase systems use indexes to quickly look up values; however, this way of indexing data is not optimal for spatial queries. Instead, spatial databases use a spatial index to speed up database operations.\r\nIn addition to typical SQL queries such as SELECT statements, spatial databases can perform a wide variety of spatial operations. The following operations and many more are specified by the Open Geospatial Consortium standard:\r\n<ul><li>Spatial Measurements: Computes line length, polygon area, the distance between geometries, etc.</li><li>Spatial Functions: Modify existing features to create new ones, for example by providing a buffer around them, intersecting features, etc.</li><li>Spatial Predicates: Allows true/false queries about spatial relationships between geometries. Examples include &quot;do two polygons overlap&quot; or 'is there a residence located within a mile of the area we are planning to build the landfill?'</li><li>Geometry Constructors: Creates new geometries, usually by specifying the vertices (points or nodes) which define the shape.</li><li>Observer Functions: Queries which return specific information about a feature such as the location of the center of a circle.</li></ul>\r\nSome databases support only simplified or modified sets of these operations, especially in cases of NoSQL systems like MongoDB and CouchDB.","materialsDescription":"<span style=\"font-weight: bold;\">What is the spatial index?</span>\r\nSpatial indices are used by spatial databases (databases which store information related to objects in space) to optimize spatial queries. Conventional index types do not efficiently handle spatial queries such as how far two points differ, or whether points fall within a spatial area of interest. Common spatial index methods include:\r\n<ul><li>Geohash</li><li>HHCode</li><li>Grid (spatial index)</li><li>Z-order (curve)</li><li>Quadtree</li><li>Octree</li><li>UB-tree</li><li>R-tree: Typically the preferred method for indexing spatial data.[citation needed] Objects (shapes, lines and points) are grouped using the minimum bounding rectangle (MBR). Objects are added to an MBR within the index that will lead to the smallest increase in its size.</li><li>R+ tree</li><li>R* tree</li><li>Hilbert R-tree</li><li>X-tree</li><li>kd-tree</li><li>m-tree – an m-tree index can be used for the efficient resolution of similarity queries on complex objects as compared using an arbitrary metric.</li><li>Binary space partitioning (BSP-Tree): Subdividing space by hyperplanes.</li></ul>","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Spatial_Information_Management_Software.png"},{"id":227,"title":"Advanced Analytics Software","alias":"advanced-analytics-software","description":" <span style=\"font-weight: bold;\">Advanced analytics</span> is a part of data science that uses high-level methods and tools to focus on projecting future trends, events, and behaviors. This gives organizations the ability to perform advanced statistical models such as ‘what-if’ calculations, as well as future-proof various aspects of their operations.\r\nThe term is an umbrella for several sub-fields of analytics that work together in their predictive capabilities.\r\nThe major areas that make up advanced analytics are predictive data analytics, big data, and data mining. The process of advanced analytics includes all three areas at various times.\r\n<span style=\"font-weight: bold;\">Data mining</span> is a key aspect of advanced analytics, providing the raw data that will be used by both big data and predictive analytics. <span style=\"font-weight: bold;\">Big data analytics</span> are useful in finding existing insights and creating connections between data points and sets, as well as cleaning data.\r\nFinally, <span style=\"font-weight: bold;\">predictive analytics</span> can use these clean sets and existing insights to extrapolate and make predictions and projections about future activity, trends, and consumer behaviors.\r\nAdvanced analytics also include newer technologies such as machine learning and artificial intelligence, semantic analysis, visualizations, and even neural networks. Taken together, they help advanced analytics software create an accurate enough canvas to make reliable predictions and generate actionable BI insights on a deeper level.","materialsDescription":"<h1 class=\"align-center\">A list of tips on how to manage the process of building an advanced analytics program</h1>\r\n<ul><li>Start with a proof-of-concept project to demonstrate the potential business value of analytics applications.</li><li>Take training seriously. New data management and analytics skills likely will be needed, especially if big data platforms and tools like SAS advanced analytics tools are involved.</li><li>Develop processes to ensure that business units are ready to act on analytical findings so the work of data scientists and other analysts doesn't go to waste.</li><li>Monitor and assess advanced and predictive analytics software on a regular basis to make sure the data being analyzed is still relevant and the analytical models being run against it are still valid.</li></ul>\r\n<h1 class=\"align-center\">Advanced analytics tools</h1>\r\nThere are a variety of advanced analytics tools to choose from that offer different advantages based on the use case. They generally break down into two categories: open source and proprietary.\r\nOpen source tools have become a go-to option for many data scientists doing machine learning and prescriptive analytics. They include programming languages, as well as computing environments, including Hadoop and Spark. Users typically say they like open source advanced analytics tools because they are generally inexpensive to operate, offer strong functionality and are backed by a user community that continually innovates the tools.\r\nOn the proprietary side, vendors including Microsoft, IBM and the SAS Institute all offer advanced analytics tools. Most require a deep technical background and understanding of mathematical techniques.\r\nIn recent years, however, a crop of self-service analytics tools has matured to make functionality more accessible to business users. Tableau, in particular, has become a common tool. While its functionality is more limited than deeper technical tools, it does enable users to conduct cluster analyses and other advanced analyses.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Advanced_Analytics_Software.png"},{"id":225,"title":"End-User Query, Reporting, and Analysis","alias":"end-user-query-reporting-and-analysis","description":" Class systems of Query &amp; Reporting are designed to form queries to information systems in user terms, as well as their execution, integration of data from different sources, viewing data with the possibilities of detailing and summarizing and building full-fledged reports, both on-screen and printed. Visualization of query results can be presented to the user in various forms - flat or multidimensional tables, graphs, charts, various specialized interfaces.\r\nEnd-user tools for querying and building reports are delivered in two ways:\r\n<ul><li>as part of OLAP-systems</li><li>in the form of specialized Query &amp; Reporting</li></ul>\r\nVirtually every OLAP class system is equipped with Query &amp; Reporting. These funds can be either embedded in the main product or separated into a separate product.\r\nThere are also specialized systems for generating and distributing reports. At the same time, these systems incorporate their own OLAP-means. Therefore, to draw a clear line between OLAP-systems and systems of class Query &amp; Reporting is almost impossible.","materialsDescription":" <span style=\"font-weight: bold; \">What are the reporting tools?</span>\r\nReporting tools are widely used to support decision making and to measure organizational and team performance. Companies use them for financial consolidation, for evaluation of strategies and policies and often just for plain reporting. Today most of these tools are integrated with Business Intelligence tools.\r\n<span style=\"font-weight: bold; \">What are the advantages of these tools for your organization?</span>\r\nReporting tools allow companies to create attractive reports easily. In tabular or graphical format. With data from Excel, a data warehouse or the organization’s ERP system. With the reports containing the right information, people are able to manage and improve the business processes more easily.\r\n<span style=\"font-weight: bold; \">Which reporting tools are available in the market?</span>\r\nThere are many Business Intelligence Reporting tools in the market available. This list of reporting tools shows you a complete overview of all the major tools currently available and thoroughly studied by our industry analysts. To name a few: Cognos Query and reporting, Oracle Enterprise Reporting, Crystal Reports, Microsoft Reporting Services (SSRS), etc.\r\n<span style=\"font-weight: bold; \">Is there a difference between reporting tools and BI tools?</span>\r\nAlmost every company, large or small, needs a reporting tool or they have already one in place. But, what is the difference between reporting software and Business Intelligence tools? They are not the same. In general reporting tools tell us where we have been but are not very good at analyzing data (at real time) and telling us where we are going (predictive).\r\n<span style=\"font-weight: bold;\">What is the difference between a query and a report?</span>\r\nA query is a way to create a list of accounts or journal entries that match your criteria. Requests serve as an advanced search engine that finds and groups accounts or journal entries and can only create a list.\r\nA report is a detailed report of a group of accounts or journal entries. Reports analyze data and are designed to calculate and present data in a more formal form.\r\nTypically, a query finds information in the database for you, and a report is a more powerful way to display and analyze information about the accounts or log entries you want to view.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/End-User_Query__Reporting__and_Analysis.png"}],"characteristics":[],"concurentProducts":[],"jobRoles":[],"organizationalFeatures":[],"complementaryCategories":[],"solutions":[],"materials":[],"useCases":[],"best_practices":[],"values":[],"implementations":[]}],"suppliedProducts":[{"id":3802,"logoURL":"https://old.roi4cio.com/fileadmin/user_upload/knightscope_01.png","logo":true,"scheme":false,"title":"Knightscope K5","vendorVerified":0,"rating":"0.00","implementationsCount":0,"suppliersCount":0,"supplierPartnersCount":0,"alias":"knightscope-k5","companyTitle":"Knightscope","companyTypes":["supplier","vendor"],"companyId":5976,"companyAlias":"knightscope","description":"The Knightscope K5 is primarily an outdoor machine which runs 24/7 on its own including autonomously recharging itself without any human intervention. It is best suited for securing large outdoor spaces. Working together with human eyes, you’ll be better equipped to keep areas such as parking lots, corporate campuses and hospitals safe autonomously.\r\n<b>Features:</b>\r\n<b>360 Degree HD Video Streaming</b>\r\nThe K5 was able to provide eye-level high definition video of the entire incident, providing the key necessary information in a timely manner, transmitted the information to law enforcement, which was received in time to arrest the suspect.\r\n<b>People Detection</b>\r\nPerhaps at your sensitive facility, there literally should be no humans during certain times of the day, say 10pm - 5am. The K5 can be on the lookout for any people during those times and proactively make pre-recorded announcements to deter negative behavior.\r\n<b>Automatic License Plate Recognition</b>\r\nUtilizing the KSOC, clients can whitelist or blacklist license plates depending on the needs of your location. The user can also automatically check for dwell times of plates (i.e., a parking meter) to deter overnight parking or assist with BOLOs (Be On The Lookout).\r\n<b>Thermal Anomaly Detection</b>\r\n<ul> <li>Early Detection of Potential Fire Threat</li> <li>Unauthorized Individuals in Restricted Areas</li> <li>Suspicious Persons After Hours</li> <li>Running Vehicles</li> <li>Positive Identification Capture</li> </ul>\r\n<b>Automatic Signal Detection</b>\r\nCombining this capability with Automatic License Plate Recognition as well as BOLO mug shot upload capabilities allows for unprecedented new capabilities in deterring unwanted behavior at your location.\r\n<b>Two-Way Intercom</b>\r\nA Two-Way Intercom (human-to-human voice interaction) call can be initiated either by the KSOC user or a human presses the button on a machine. The button press can be configured to call a certain number to further assist your security team.\r\n<b>Live Audio Broadcast</b>\r\nLive Audio Broadcast, similar to public address system, allows a KSOC user to throw their voice through a machine or machines providing new alerting capabilities.\r\n<b>Pre-recorded Broadcast Messages</b>\r\nPre-Recorded Messages may be played manually by the KSOC user or set automatically to play randomly, by time, by location or by detection, further automating visitor, patron, or employee engagement.","shortDescription":"Access real-time data around the clock via our desktop or mobile apps, ensuring you’ll always have the power of our technology at your fingertips. Knightscope has you covered 24/7/365\r\n\r\n","type":null,"isRoiCalculatorAvaliable":false,"isConfiguratorAvaliable":false,"bonus":100,"usingCount":15,"sellingCount":13,"discontinued":0,"rebateForPoc":0,"rebate":0,"seo":{"title":"Knightscope K5","keywords":"","description":"The Knightscope K5 is primarily an outdoor machine which runs 24/7 on its own including autonomously recharging itself without any human intervention. It is best suited for securing large outdoor spaces. Working together with human eyes, you’ll be better equi","og:title":"Knightscope K5","og:description":"The Knightscope K5 is primarily an outdoor machine which runs 24/7 on its own including autonomously recharging itself without any human intervention. It is best suited for securing large outdoor spaces. 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It contains selected recommendations and structures from Microsoft and other developers in the industry that ensure the successful implementation of data processing and analysis solutions. All this is to help companies take full advantage of their analytics software.","materialsDescription":"<span style=\"font-weight: bold; \">Data access</span>\r\nData access is a generic term referring to a process which has both an IT-specific meaning and other connotations involving access rights in a broader legal and/or political sense. In the former it typically refers to software and activities related to storing, retrieving, or acting on data housed in a database or other repository. Two fundamental types of data access exist:\r\n<ol><li>sequential access (as in magnetic tape, for example)</li><li>random access (as in indexed media)</li></ol>\r\nData access crucially involves authorization to access different data repositories. Data access can help distinguish the abilities of administrators and users. For example, administrators may have the ability to remove, edit and add data, while general users may not even have &quot;read&quot; rights if they lack access to particular information.\r\nHistorically, each repository (including each different database, file system, etc.), might require the use of different methods and languages, and many of these repositories stored their content in different and incompatible formats.\r\nOver the years standardized languages, methods, and formats, have developed to serve as interfaces between the often proprietary, and always idiosyncratic, specific languages and methods. Such standards include SQL (1974- ), ODBC (ca 1990- ), JDBC, XQJ, ADO.NET, XML, XQuery, XPath (1999- ), and Web Services.\r\nSome of these standards enable translation of data from unstructured (such as HTML or free-text files) to structured (such as XML or SQL).\r\nStructures such as connection strings and DBURLs[1] can attempt to standardise methods of connecting to databases.\r\n<span style=\"font-weight: bold; \">A program for data analysis</span>\r\nA data analysis program is a specially developed software that can analyze any information. This is usually a database program. It is within the database that you can store any information in any amount. A functional program allows incoming and stored data to analyze. Software development can be done for any tasks, which means that the program for data analysis can be customized for any activity. If, for example, you have a trade organization, then your data analysis program will analyze products, customers, funds, product balance, and more.\r\n<span style=\"font-weight: bold;\">On-demand software delivery</span>\r\nA type of software delivery service where the software is provided to the customer through a network (such as the Internet) as a service. On-demand software delivery is also called software on-demand. The terms on-demand software and Software as a Service (SaaS) are often used interchangeably.\r\nData access, analysis and delivery software are end-user oriented tools for ad hoc data access, analysis and reporting as well as production reporting.&nbsp; These products are most commonly used by information consumers or power users rather than professional programmers.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Data_Access__Analysis__and_Delivery_Software1.png"},{"id":229,"title":"Spatial Information Management Software","alias":"spatial-information-management-software","description":" A spatial database is a database that is optimized for storing and querying data that represents objects defined in a geometric space. Most spatial databases allow the representation of simple geometric objects such as points, lines and polygons. Some spatial databases handle more complex structures such as 3D objects, topological coverages, linear networks, and TINs. While typical databases have developed to manage various numeric and character types of data, such databases require additional functionality to process spatial data types efficiently, and developers have often added geometry or feature data types. The Open Geospatial Consortium (OGC) developed the Simple Features specification (first released in 1997) and sets standards for adding spatial functionality to database systems. The SQL/MM Spatial ISO/IEC standard is a part the SQL/MM multimedia standard and extends the Simple Features standard with data types that support circular interpolations.\r\nA geodatabase (also geographical database and geospatial database) is a database of geographic data, such as countries, administrative divisions, cities, and related information. Such databases can be useful for websites that wish to identify the locations of their visitors for customization purposes.\r\nDatabase systems use indexes to quickly look up values; however, this way of indexing data is not optimal for spatial queries. Instead, spatial databases use a spatial index to speed up database operations.\r\nIn addition to typical SQL queries such as SELECT statements, spatial databases can perform a wide variety of spatial operations. The following operations and many more are specified by the Open Geospatial Consortium standard:\r\n<ul><li>Spatial Measurements: Computes line length, polygon area, the distance between geometries, etc.</li><li>Spatial Functions: Modify existing features to create new ones, for example by providing a buffer around them, intersecting features, etc.</li><li>Spatial Predicates: Allows true/false queries about spatial relationships between geometries. Examples include &quot;do two polygons overlap&quot; or 'is there a residence located within a mile of the area we are planning to build the landfill?'</li><li>Geometry Constructors: Creates new geometries, usually by specifying the vertices (points or nodes) which define the shape.</li><li>Observer Functions: Queries which return specific information about a feature such as the location of the center of a circle.</li></ul>\r\nSome databases support only simplified or modified sets of these operations, especially in cases of NoSQL systems like MongoDB and CouchDB.","materialsDescription":"<span style=\"font-weight: bold;\">What is the spatial index?</span>\r\nSpatial indices are used by spatial databases (databases which store information related to objects in space) to optimize spatial queries. Conventional index types do not efficiently handle spatial queries such as how far two points differ, or whether points fall within a spatial area of interest. Common spatial index methods include:\r\n<ul><li>Geohash</li><li>HHCode</li><li>Grid (spatial index)</li><li>Z-order (curve)</li><li>Quadtree</li><li>Octree</li><li>UB-tree</li><li>R-tree: Typically the preferred method for indexing spatial data.[citation needed] Objects (shapes, lines and points) are grouped using the minimum bounding rectangle (MBR). Objects are added to an MBR within the index that will lead to the smallest increase in its size.</li><li>R+ tree</li><li>R* tree</li><li>Hilbert R-tree</li><li>X-tree</li><li>kd-tree</li><li>m-tree – an m-tree index can be used for the efficient resolution of similarity queries on complex objects as compared using an arbitrary metric.</li><li>Binary space partitioning (BSP-Tree): Subdividing space by hyperplanes.</li></ul>","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Spatial_Information_Management_Software.png"},{"id":227,"title":"Advanced Analytics Software","alias":"advanced-analytics-software","description":" <span style=\"font-weight: bold;\">Advanced analytics</span> is a part of data science that uses high-level methods and tools to focus on projecting future trends, events, and behaviors. This gives organizations the ability to perform advanced statistical models such as ‘what-if’ calculations, as well as future-proof various aspects of their operations.\r\nThe term is an umbrella for several sub-fields of analytics that work together in their predictive capabilities.\r\nThe major areas that make up advanced analytics are predictive data analytics, big data, and data mining. The process of advanced analytics includes all three areas at various times.\r\n<span style=\"font-weight: bold;\">Data mining</span> is a key aspect of advanced analytics, providing the raw data that will be used by both big data and predictive analytics. <span style=\"font-weight: bold;\">Big data analytics</span> are useful in finding existing insights and creating connections between data points and sets, as well as cleaning data.\r\nFinally, <span style=\"font-weight: bold;\">predictive analytics</span> can use these clean sets and existing insights to extrapolate and make predictions and projections about future activity, trends, and consumer behaviors.\r\nAdvanced analytics also include newer technologies such as machine learning and artificial intelligence, semantic analysis, visualizations, and even neural networks. Taken together, they help advanced analytics software create an accurate enough canvas to make reliable predictions and generate actionable BI insights on a deeper level.","materialsDescription":"<h1 class=\"align-center\">A list of tips on how to manage the process of building an advanced analytics program</h1>\r\n<ul><li>Start with a proof-of-concept project to demonstrate the potential business value of analytics applications.</li><li>Take training seriously. New data management and analytics skills likely will be needed, especially if big data platforms and tools like SAS advanced analytics tools are involved.</li><li>Develop processes to ensure that business units are ready to act on analytical findings so the work of data scientists and other analysts doesn't go to waste.</li><li>Monitor and assess advanced and predictive analytics software on a regular basis to make sure the data being analyzed is still relevant and the analytical models being run against it are still valid.</li></ul>\r\n<h1 class=\"align-center\">Advanced analytics tools</h1>\r\nThere are a variety of advanced analytics tools to choose from that offer different advantages based on the use case. They generally break down into two categories: open source and proprietary.\r\nOpen source tools have become a go-to option for many data scientists doing machine learning and prescriptive analytics. They include programming languages, as well as computing environments, including Hadoop and Spark. Users typically say they like open source advanced analytics tools because they are generally inexpensive to operate, offer strong functionality and are backed by a user community that continually innovates the tools.\r\nOn the proprietary side, vendors including Microsoft, IBM and the SAS Institute all offer advanced analytics tools. Most require a deep technical background and understanding of mathematical techniques.\r\nIn recent years, however, a crop of self-service analytics tools has matured to make functionality more accessible to business users. Tableau, in particular, has become a common tool. While its functionality is more limited than deeper technical tools, it does enable users to conduct cluster analyses and other advanced analyses.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Advanced_Analytics_Software.png"},{"id":225,"title":"End-User Query, Reporting, and Analysis","alias":"end-user-query-reporting-and-analysis","description":" Class systems of Query &amp; Reporting are designed to form queries to information systems in user terms, as well as their execution, integration of data from different sources, viewing data with the possibilities of detailing and summarizing and building full-fledged reports, both on-screen and printed. Visualization of query results can be presented to the user in various forms - flat or multidimensional tables, graphs, charts, various specialized interfaces.\r\nEnd-user tools for querying and building reports are delivered in two ways:\r\n<ul><li>as part of OLAP-systems</li><li>in the form of specialized Query &amp; Reporting</li></ul>\r\nVirtually every OLAP class system is equipped with Query &amp; Reporting. These funds can be either embedded in the main product or separated into a separate product.\r\nThere are also specialized systems for generating and distributing reports. At the same time, these systems incorporate their own OLAP-means. Therefore, to draw a clear line between OLAP-systems and systems of class Query &amp; Reporting is almost impossible.","materialsDescription":" <span style=\"font-weight: bold; \">What are the reporting tools?</span>\r\nReporting tools are widely used to support decision making and to measure organizational and team performance. Companies use them for financial consolidation, for evaluation of strategies and policies and often just for plain reporting. Today most of these tools are integrated with Business Intelligence tools.\r\n<span style=\"font-weight: bold; \">What are the advantages of these tools for your organization?</span>\r\nReporting tools allow companies to create attractive reports easily. In tabular or graphical format. With data from Excel, a data warehouse or the organization’s ERP system. With the reports containing the right information, people are able to manage and improve the business processes more easily.\r\n<span style=\"font-weight: bold; \">Which reporting tools are available in the market?</span>\r\nThere are many Business Intelligence Reporting tools in the market available. This list of reporting tools shows you a complete overview of all the major tools currently available and thoroughly studied by our industry analysts. To name a few: Cognos Query and reporting, Oracle Enterprise Reporting, Crystal Reports, Microsoft Reporting Services (SSRS), etc.\r\n<span style=\"font-weight: bold; \">Is there a difference between reporting tools and BI tools?</span>\r\nAlmost every company, large or small, needs a reporting tool or they have already one in place. But, what is the difference between reporting software and Business Intelligence tools? They are not the same. In general reporting tools tell us where we have been but are not very good at analyzing data (at real time) and telling us where we are going (predictive).\r\n<span style=\"font-weight: bold;\">What is the difference between a query and a report?</span>\r\nA query is a way to create a list of accounts or journal entries that match your criteria. Requests serve as an advanced search engine that finds and groups accounts or journal entries and can only create a list.\r\nA report is a detailed report of a group of accounts or journal entries. Reports analyze data and are designed to calculate and present data in a more formal form.\r\nTypically, a query finds information in the database for you, and a report is a more powerful way to display and analyze information about the accounts or log entries you want to view.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/End-User_Query__Reporting__and_Analysis.png"}],"characteristics":[],"concurentProducts":[],"jobRoles":[],"organizationalFeatures":[],"complementaryCategories":[],"solutions":[],"materials":[],"useCases":[],"best_practices":[],"values":[],"implementations":[]}],"partnershipProgramme":null}},"aliases":{},"links":{},"meta":{},"loading":false,"error":null},"implementations":{"implementationsByAlias":{},"aliases":{},"links":{},"meta":{},"loading":false,"error":null},"agreements":{"agreementById":{},"ids":{},"links":{},"meta":{},"loading":false,"error":null},"comparison":{"loading":false,"error":false,"templatesById":{},"comparisonByTemplateId":{},"products":[],"selectedTemplateId":null},"presentation":{"type":null,"company":{},"products":[],"partners":[],"formData":{},"dataLoading":false,"dataError":false,"loading":false,"error":false},"catalogsGlobal":{"subMenuItemTitle":""}}