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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. 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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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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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