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Data integration needs to be collaborative and unified in order to improve collaboration and unification across the organization.\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Saves time and boosts efficiency</span></span>\r\nWhen a company takes measures to integrate its data properly, it cuts down significantly on the time it takes to prepare and analyze that data. The automation of unified views cuts out the need for manually gathering data, and employees no longer need to build connections from scratch whenever they need to run a report or build an application.\r\nAdditionally, using the right tools, rather than hand-coding the integration, returns even more time (and resources overall) to the dev team.\r\nAll the time saved on these tasks can be put to other, better uses, with more hours earmarked for analysis and execution to make an organization more productive and competitive.\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Reduces errors (and rework)</span></span>\r\nThere’s a lot to keep up with when it comes to a company’s data resources. To manually gather data, employees must know every location and account that they might need to explore — and have all necessary software installed before they begin — to ensure their data sets will be complete and accurate. If a data repository is added, and that employee is unaware, they will have an incomplete data set.\r\nAdditionally, without a data integration solution that synchronizes data, reporting must be periodically redone to account for any changes. With automated updates, however, reports can be run easily in real time, whenever they’re needed.\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Delivers more valuable data</span></span>\r\nData integration efforts actually improve the value of a business’ data over time. As data is integrated into a centralized system, quality issues are identified and necessary improvements are implemented, which ultimately results in more accurate data — the foundation for quality analysis.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Data_Integration_and_Access_Software.png"}],"characteristics":[],"concurentProducts":[],"jobRoles":[],"organizationalFeatures":[],"complementaryCategories":[],"solutions":[],"materials":[],"useCases":[],"best_practices":[],"values":[],"implementations":[]}],"countries":[{"id":180,"title":"Russia","name":"RUS"}],"startDate":"0000-00-00","endDate":"0000-00-00","dealDate":"0000-00-00","price":0,"status":"finished","statusLabel":"Finished","isImplementation":true,"isAgreement":false,"confirmed":1,"implementationDetails":{"businessObjectives":{"id":14,"title":"Business objectives","translationKey":"businessObjectives","options":[{"id":10,"title":"Ensure Compliance"},{"id":4,"title":"Reduce Costs"},{"id":6,"title":"Ensure Security and Business Continuity"}]},"businessProcesses":{"id":11,"title":"Business process","translationKey":"businessProcesses","options":[{"id":370,"title":"No automated business processes"}]}},"categories":[{"id":245,"title":"Data Integration and Access Software","alias":"data-integration-and-access-software","description":" Data integration involves combining data residing in different sources and providing users with a unified view of them. This process becomes significant in a variety of situations, which include both commercial (such as when two similar companies need to merge their databases) and scientific (combining research results from different bioinformatics repositories, for example) domains. Data integration appears with increasing frequency as the volume (that is, big data) and the need to share existing data explodes. It has become the focus of extensive theoretical work, and numerous open problems remain unsolved. Data integration encourages collaboration between internal as well as external users.\r\nData integration is the process of combining data from different sources into a single, unified view. Integration begins with the ingestion process, and includes steps such as cleansing, ETL mapping, and transformation. Data integration ultimately enables analytics tools to produce effective, actionable business intelligence.\r\nThere is no universal approach to data integration. However, data integration solutions typically involve a few common elements, including a network of data sources, a master server, and clients accessing data from the master server.\r\nIn a typical data integration process, the client sends a request to the master server for data. The master server then intakes the needed data from internal and external sources. The data is extracted from the sources, then consolidated into a single, cohesive data set. This is served back to the client for use.","materialsDescription":" <span style=\"font-weight: bold;\">Integration helps businesses succeed</span>\r\nEven if a company is receiving all the data it needs, that data often resides in a number of separate data sources. For example, for a typical customer 360 view use case, the data that must be combined may include data from their CRM systems, web traffic, marketing operations software, customer — facing applications, sales and customer success systems, and even partner data, just to name a few. Information from all of those different sources often needs to be pulled together for analytical needs or operational actions, and that can be no small task for data engineers or developers to bring them all together.\r\nLet’s take a look at a typical analytical use case. Without unified data, a single report typically involves logging into multiple accounts, on multiple sites, accessing data within native apps, copying over the data, reformatting, and cleansing, all before analysis can happen.\r\nConducting all these operations as efficiently as possible highlights the importance of data integration. It also showcases the major benefits of a well thought-out approach to data integration:\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Improves collaboration and unification of systems</span></span>\r\nEmployees in every department — and sometimes in disparate physical locations — increasingly need access to the company's data for shared and individual projects. IT needs a secure solution for delivering data via self-service access across all lines of business.\r\nAdditionally, employees in almost every department are generating and improving data that the rest of the business needs. Data integration needs to be collaborative and unified in order to improve collaboration and unification across the organization.\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Saves time and boosts efficiency</span></span>\r\nWhen a company takes measures to integrate its data properly, it cuts down significantly on the time it takes to prepare and analyze that data. The automation of unified views cuts out the need for manually gathering data, and employees no longer need to build connections from scratch whenever they need to run a report or build an application.\r\nAdditionally, using the right tools, rather than hand-coding the integration, returns even more time (and resources overall) to the dev team.\r\nAll the time saved on these tasks can be put to other, better uses, with more hours earmarked for analysis and execution to make an organization more productive and competitive.\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Reduces errors (and rework)</span></span>\r\nThere’s a lot to keep up with when it comes to a company’s data resources. To manually gather data, employees must know every location and account that they might need to explore — and have all necessary software installed before they begin — to ensure their data sets will be complete and accurate. If a data repository is added, and that employee is unaware, they will have an incomplete data set.\r\nAdditionally, without a data integration solution that synchronizes data, reporting must be periodically redone to account for any changes. With automated updates, however, reports can be run easily in real time, whenever they’re needed.\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Delivers more valuable data</span></span>\r\nData integration efforts actually improve the value of a business’ data over time. As data is integrated into a centralized system, quality issues are identified and necessary improvements are implemented, which ultimately results in more accurate data — the foundation for quality analysis.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/Data_Integration_and_Access_Software.png"}],"additionalInfo":{"budgetNotExceeded":"","functionallyTaskAssignment":"","projectWasPut":"","price":0,"source":{"url":"https://www.ingos.ru/ru/company/news/detail/777196/","title":"End-user Web-site"}},"comments":[],"referencesCount":0}],"userImplementations":[],"userImplementationsCount":0,"supplierImplementationsCount":0,"vendorImplementationsCount":1,"vendorPartnersCount":0,"supplierPartnersCount":0,"b4r":0,"categories":{"1":{"id":1,"title":"Desktop virtualization","description":" Desktop virtualization is a virtualization technology that separates an individual's PC applications from his or her desktop. Virtualized desktops are generally hosted on a remote central server, rather than the hard drive of the personal computer. Because the client-server computing model is used in virtualizing desktops, desktop virtualization is also known as client virtualization.\r\nDesktop virtualization provides a way for users to maintain their individual desktops on a single, central server. The users may be connected to the central server through a LAN, WAN or over the Internet.\r\nDesktop virtualization has many benefits, including a lower total cost of ownership (TCO), increased security, reduced energy costs, reduced downtime and centralized management.\r\nLimitations of desktop virtualization include difficulty in maintenance and set up of printer drivers; increased downtime in case of network failures; complexity and costs involved in VDI deployment and security risks in the event of improper network management.<br /><br />","materialsDescription":" <span style=\"font-weight: bold; \">What are types of desktop virtualization technologies?</span>\r\nHost-based forms of desktop virtualization require that users view and interact with their virtual desktops over a network by using a remote display protocol. Because processing takes place in a data center, client devices can be traditional PCs, but also thin clients, zero clients, smartphones and tablets. Examples of host-based desktop virtualization technology include:\r\n<span style=\"font-weight: bold; \">Host-based virtual machines:</span> Each user connects to an individual VM that is hosted in a data center. The user may connect to the same VM every time, allowing for personalization (known as a persistent desktop), or be given a fresh VM at each login (a nonpersistent desktop).\r\n<span style=\"font-weight: bold; \">Shared hosted:</span> Users connect to a shared desktop that runs on a server. Microsoft Remote Desktop Services, formerly Terminal Services, takes this client-server approach. Users may also connect to individual applications running on a server; this technology is an example of application virtualization.\r\n<span style=\"font-weight: bold; \">Host-based physical machines:</span> The operating system runs directly on another device's physical hardware.\r\nClient virtualization requires processing to occur on local hardware; the use of thin clients, zero clients and mobile devices is not possible. These types of desktop virtualization include:\r\n<span style=\"font-weight: bold; \">OS image streaming:</span> The operating system runs on local hardware, but it boots to a remote disk image across the network. This is useful for groups of desktops that use the same disk image. OS image streaming, also known as remote desktop virtualization, requires a constant network connection in order to function.\r\n<span style=\"font-weight: bold; \">Client-based virtual machines:</span> A VM runs on a fully functional PC, with a hypervisor in place. Client-based virtual machines can be managed by regularly syncing the disk image with a server, but a constant network connection is not necessary in order for them to function.\r\n<span style=\"font-weight: bold;\">Desktop virtualization vs. virtual desktop infrastructure</span>\r\nThe terms <span style=\"font-style: italic;\">desktop virtualization</span> and virtual desktop infrastructure (VDI) are often used interchangeably, but they are not the same. While VDI is a type of desktop virtualization, not all desktop virtualization uses VDI.\r\nVDI refers to the use of host-based VMs to deliver virtual desktops, which emerged in 2006 as an alternative to Terminal Services and Citrix's client-server approach to desktop virtualization technology. Other types of desktop virtualization -- including the shared hosted model, host-based physical machines and all methods of client virtualization -- are not examples of VDI.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/icon_Desktop_virtualization.png","alias":"desktop-virtualization"},"27":{"id":27,"title":"ODMS - Operational Database Management System","description":"Operational database management systems (also referred to as OLTP On-Line Transaction Processing databases) are used to update data in real-time. These types of databases allow users to do more than simply view archived data. Operational databases allow you to modify that data (add, change or delete data), doing it in real-time. OLTP databases provide transactions as the main abstraction to guarantee data consistency that guarantees the so-called ACID properties. Basically, the consistency of the data is guaranteed in the case of failures and/or concurrent access to the data.\r\nSince the early 90s, the operational database software market has been largely taken over by SQL engines. Today, the operational DBMS market (formerly OLTP) is evolving dramatically, with new, innovative entrants and incumbents supporting the growing use of unstructured data and NoSQL DBMS engines, as well as XML databases and NewSQL databases. NoSQL databases typically have focused on scalability and have renounced to data consistency by not providing transactions as OLTP systems do. Operational databases are increasingly supporting distributed database architecture that can leverage distribution to provide high availability and fault tolerance through replication and scale-out ability.\r\nThe growing role of operational databases in the IT industry is moving fast from legacy databases to real-time operational databases capable to handle distributed web and mobile demand and to address Big data challenges. Recognizing this, Gartner started to publish the Magic Quadrant for Operational Database Management Systems in October 2013.\r\nOperational databases are used to store, manage and track real-time business information. For example, a company might have an operational database used to track warehouse/stock quantities. As customers order products from an online web store, an operational database can be used to keep track of how many items have been sold and when the company will need to reorder stock. An operational database stores information about the activities of an organization, for example, customer relationship management transactions or financial operations, in a computer database.\r\nOperational databases allow a business to enter, gather, and retrieve large quantities of specific information, such as company legal data, financial data, call data records, personal employee information, sales data, customer data, data on assets and much other information. An important feature of storing information in an operational database is the ability to share information across the company and over the Internet. Operational databases can be used to manage mission-critical business data, to monitor activities, to audit suspicious transactions, or to review the history of dealings with a particular customer. They can also be part of the actual process of making and fulfilling a purchase, for example in e-commerce.","materialsDescription":" <span style=\"font-weight: bold;\">What is DBMS used for?</span>\r\nDBMS, commonly known as Database Management System, is an application system whose main purpose revolves around the data. This is a system that allows its users to store the data, define it, retrieve it and update the information about the data inside the database.\r\n<span style=\"font-weight: bold;\">What is meant by a Database?</span>\r\nIn simple terms, Database is a collection of data in some organized way to facilitate its user’s to easily access, manage and upload the data.\r\n<span style=\"font-weight: bold;\">Why is the use of DBMS recommended? Explain by listing some of its major advantages.</span>\r\nSome of the major advantages of DBMS are as follows:\r\n<ul><li><span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Controlled Redundancy:</span></span> DBMS supports a mechanism to control the redundancy of data inside the database by integrating all the data into a single database and as data is stored at only one place, the duplicity of data does not happen.</li><li><span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Data Sharing:</span></span> Sharing of data among multiple users simultaneously can also be done in DBMS as the same database will be shared among all the users and by different application programs.</li><li> Backup and Recovery Facility: DBMS minimizes the pain of creating the backup of data again and again by providing a feature of ‘backup and recovery’ which automatically creates the data backup and restores the data whenever required.</li><li><span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Enforcement of Integrity Constraints:</span></span> Integrity Constraints are very important to be enforced on the data so that the refined data after putting some constraints are stored in the database and this is followed by DBMS.</li><li><span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Independence of Data:</span></span> It simply means that you can change the structure of the data without affecting the structure of any of the application programs.</li></ul>\r\n<span style=\"font-weight: bold;\">What is the purpose of normalization in DBMS?</span>\r\nNormalization is the process of analyzing the relational schemas which are based on their respective functional dependencies and the primary keys in order to fulfill certain properties.\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">The properties include:</span></span>\r\n<ul><li>To minimize the redundancy of the Data.</li><li>To minimize the Insert, Delete and Update Anomalies.</li></ul>","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/icon_ODMS.png","alias":"odms-operational-database-management-system"},"53":{"id":53,"title":"DaaS - Desktop as a Service","description":"<span style=\"font-weight: bold; \">DaaS (Desktop as a service)</span> is a cloud computing offering in which a third party hosts the back end of a virtual desktop infrastructure (VDI) deployment.\r\nWith DaaS services, desktop operating systems run inside virtual machines on servers in a cloud provider's data center. All the necessary support infrastructure, including storage and network resources, also lives in the cloud. As with on-premises VDI, a DaaS providers stream virtual desktops over a network to a customer's endpoint devices, where end users may access them through client software or a web browser.\r\nThough it sounds a lot like VDI, there is a vital difference between DaaS and VDI. VDI refers to when virtual desktops are served through on-premise servers maintained by in-house IT teams. It’s the traditional way to deploy and manage virtual desktops. But since it’s on-premise, VDI technology technology must be maintained, managed, and upgraded in-house whenever necessary.\r\nDaaS service on the other hand, is a cloud-based virtual desktop solution that separates virtual desktops from on-premise servers, enabling brands to leverage a third-party hosting provider. It’s like VDI, but in the cloud instead of in the back of the office. \r\nHowever, it’s not necessary to choose one or the other. These two approaches can complement each other. Some users prefer to have a DaaS desktop overlay of their VDI deployment. For example, the Desktop as a Service providers allow the user to modernize legacy applications with zero code refactoring. Not all legacy Windows apps perform well in a DaaS environment, due to latency or hardware requirements. \r\nThe modern workplace requires agility, leading to many companies embracing mobile working and Bring Your Own Device (BYOD) policies against a backdrop of increased concern about security risk, compliance requirements and the ever-present need to reduce overheads. This is why, over a decade after analysts predicted the rise of remote desktop as a service, it is now finally being taken up in volume.\r\nBy adopting Desktop as a Service, companies can address the issues associated with end-user computing while giving their staff more freedom and increasing productivity. The pain associated with managing a multitude of devices, including those not supplied by the company, is eliminated. While remaining compliant, companies can greatly reduce risks. ","materialsDescription":"<h1 class=\"align-center\"><span style=\"font-weight: bold; \">How does desktop as a service work?</span></h1>\r\nDaaS architecture is multi-tenant, and organizations purchase the service through a subscription model -- typically based on the number of virtual desktop instances used per month.\r\nIn the desktop-as-a-service delivery model, the cloud computing provider manages the back-end responsibilities of data storage, backup, security and upgrades. While the provider handles all the back-end infrastructure costs and maintenance, customers usually manage their own virtual desktop images, applications and security, unless those desktop management services are part of the subscription.\r\nTypically, an end user's personal data is copied to and from their virtual desktop during logon and logoff, and access to the desktop is device-, location- and network-independent.\r\n<h1 class=\"align-center\">The benefits of Desktop as a Service</h1>\r\nMany organisations are undergoing digital transformation, and modernising the workplace is often a stream within the wider strategy. In order to manage remote and multi-device workforces using DaaS, you should think about the following seven benefits and how this will change, and hopefully improve, your currently way of working.\r\n<span style=\"font-weight: bold;\">The modern workplace.</span> Digital transformation is redefining what we think about the workplace. At the heart of this evolution is technology and the introduction of digital-first natives into the workplace. Allowing staff to work remotely, through DaaS in cloud and via their own devices is a surefire way to attract and retain the best talent.\r\n<span style=\"font-weight: bold;\">Cost.</span> As with many cloud initiatives, DaaS pricing moves from CAPEX to OPEX, leaving you more cash in the bank to spend on growing your business. Per desktop pricing enables you to know exactly what workforce expansion will cost the IT department, removing unforeseen infrastructure or hardware purchases as this is handled by the provider, who bundle everything in with the price of each desktop.Virtual machines use the compute power of the data centre rather than their local machines, placing less demand on the endpoint. <span style=\"font-weight: bold;\"></span>\r\n<span style=\"font-weight: bold;\">Scalability</span>. Due to the ‘...as a service’ delivery model, DaaS platform enables you to add user workstations fast and easily. This is particularly handy when your organisation utilises contract resource or temporary project teams, as there’s no hardware to procure, meaning you have the flexibility to create a desktop almost instantly and delete it when no longer required. This also puts you in control.\r\n<span style=\"font-weight: bold;\">Control.</span> DaaS helps you manage the risks that naturally come with giving your staff the freedom to work anywhere and on any device. It enables you to control the essentials such as data access and compliance without being overly restrictive. You no longer have to worry about what data is held on a user’s device as the data remains in the data centre at all times. This gives you control over all company assets because access can be revoked with the touch of a button.\r\n<span style=\"font-weight: bold;\">Management.</span> With an increasingly dispersed workforce, rolling out new applications or patching existing software has become more of a logistical problem than a technical one. Trying to coordinate people bringing in physical devices to be patched is a real issue for many companies, something which is eliminated completely with DaaS. You operate on one central image (or a small number of images based on persona), a change is made once, and everyone is on the latest version. It removes the need to standardise builds of end-user compute hardware as DaaS applications will run on almost any device no matter its configuration.\r\n<span style=\"font-weight: bold;\">Security.</span> DaaS moves the security risk from hundreds of end-user devices and put it all into the controlled and managed environment of a data centre. Lost or stolen laptops no longer provide a security risk. No data is on the local machine. As DaaS removes the need to create VPNs to access applications and data held by the company it also removes the problem of users trying to bypass the security in the belief that it will make their life easier. 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Virtual data is efficient, automatic, and can be provisioned and refreshed in minutes.\r\nEliminate multiple, redundant copies of data\r\nApplication projects generate concurrent demands for data — up to 90% of which is the same data. The Delphix Virtualization Engine stores a single, compressed copy of production data and creates virtual copies that represent the full production source, but occupy a fraction of the space of physical copies.\r\nCut storage costs and prevent data loss\r\nThe Delphix Virtualization Engine captures all incremental changes at the transaction level, essentially creating a time machine for your data. By intelligently storing only unique changes, Delphix dramatically reduces the intake of data. Administrators can retain a large amount of data in a small amount of space and quickly provision data as of any point in time. Delphix also keeps track of all changes made to virtual copies, giving end users the ability to version their data like code.\r\nEmpower end users with self-service\r\nUnlike legacy solutions, the Delphix Virtualization Engine equips your teams with innovative, self-service control features — like the ability to quickly bookmark, reset, synchronize, and branch virtual datasets — all managed through a single, easy-to-use interface. Delphix also has a fully-exposed web REST API, enabling ready integration with existing DevOps tools and workflows.\r\n","shortDescription":"The Delphix Virtualization Engine is enterprise software that radically improves the delivery of data in databases, application files, and file systems on-premise or in the cloud. 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It has become the focus of extensive theoretical work, and numerous open problems remain unsolved. Data integration encourages collaboration between internal as well as external users.\r\nData integration is the process of combining data from different sources into a single, unified view. Integration begins with the ingestion process, and includes steps such as cleansing, ETL mapping, and transformation. Data integration ultimately enables analytics tools to produce effective, actionable business intelligence.\r\nThere is no universal approach to data integration. However, data integration solutions typically involve a few common elements, including a network of data sources, a master server, and clients accessing data from the master server.\r\nIn a typical data integration process, the client sends a request to the master server for data. The master server then intakes the needed data from internal and external sources. The data is extracted from the sources, then consolidated into a single, cohesive data set. This is served back to the client for use.","materialsDescription":" <span style=\"font-weight: bold;\">Integration helps businesses succeed</span>\r\nEven if a company is receiving all the data it needs, that data often resides in a number of separate data sources. For example, for a typical customer 360 view use case, the data that must be combined may include data from their CRM systems, web traffic, marketing operations software, customer — facing applications, sales and customer success systems, and even partner data, just to name a few. Information from all of those different sources often needs to be pulled together for analytical needs or operational actions, and that can be no small task for data engineers or developers to bring them all together.\r\nLet’s take a look at a typical analytical use case. Without unified data, a single report typically involves logging into multiple accounts, on multiple sites, accessing data within native apps, copying over the data, reformatting, and cleansing, all before analysis can happen.\r\nConducting all these operations as efficiently as possible highlights the importance of data integration. It also showcases the major benefits of a well thought-out approach to data integration:\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Improves collaboration and unification of systems</span></span>\r\nEmployees in every department — and sometimes in disparate physical locations — increasingly need access to the company's data for shared and individual projects. IT needs a secure solution for delivering data via self-service access across all lines of business.\r\nAdditionally, employees in almost every department are generating and improving data that the rest of the business needs. Data integration needs to be collaborative and unified in order to improve collaboration and unification across the organization.\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Saves time and boosts efficiency</span></span>\r\nWhen a company takes measures to integrate its data properly, it cuts down significantly on the time it takes to prepare and analyze that data. The automation of unified views cuts out the need for manually gathering data, and employees no longer need to build connections from scratch whenever they need to run a report or build an application.\r\nAdditionally, using the right tools, rather than hand-coding the integration, returns even more time (and resources overall) to the dev team.\r\nAll the time saved on these tasks can be put to other, better uses, with more hours earmarked for analysis and execution to make an organization more productive and competitive.\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Reduces errors (and rework)</span></span>\r\nThere’s a lot to keep up with when it comes to a company’s data resources. To manually gather data, employees must know every location and account that they might need to explore — and have all necessary software installed before they begin — to ensure their data sets will be complete and accurate. If a data repository is added, and that employee is unaware, they will have an incomplete data set.\r\nAdditionally, without a data integration solution that synchronizes data, reporting must be periodically redone to account for any changes. With automated updates, however, reports can be run easily in real time, whenever they’re needed.\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Delivers more valuable data</span></span>\r\nData integration efforts actually improve the value of a business’ data over time. 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