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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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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. 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