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There are many factors to consider before selecting an analytics tool to embed in your applications.
As data proliferates, organizations are eager to monetize their data assets by injecting outward-facing applications with reports, dashboards, and self-service analytics. Today, these data-driven applications can increase customer satisfaction and create new revenue streams. In the near future, they will be a requirement for doing business.
This report outlines key criteria for evaluating embedded analytics solutions. It discusses three types of analytics that can be embedded (i.e., components, tools, and platforms) and five approaches to embedding analytics, from bundling and coexisting {which were popular in the 1990s) to modular, in line, and infusion methods, which are prevalent today with Web computing. The report then describes 12 criteria for evaluating embedded analytics solutions, ranging from business considerations to product functionality and technical architectures.
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