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Organizations are embracing self-service analytics and business intelligence (bi) to bring these capabilities to business users of all levels. This trend is so pronounced that Gartner, Inc. predicts that by 2019, the analytics output of business users with self-service capabilities will surpass that of professional data scientists.
Compared to where IT was a few years ago, effective and easy-to-navigate self-service analytics has become much more difficult to achieve. Kelly Stirman explains why and what enterprises can do about.
Why Self-Service Analytics Has Gone Backward-and What To Do About It During the past decade, the assertion that the data warehouse is required to be the center of an enterprise data system started to break down in a variety of ways.
In this multi-part blog, Nick shares some areas where self-service analytics deployments fail and how Qlik’s analytic platform addresses them. Take it away Nick! Self Service Analytics . Have you ever try to do something thinking you knew how, but ended up failing in the end?
Neither of those companies are short of cash, or stock, to throw around to enhance their platforms, but the speed at which the self-service analytics market has just shrunk. the demand for tools to.
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Self-Service Analytics is a form of business intelligence in which line-of-business professionals are enabled and encouraged to perform queries and generate reports on their own, with nominal IT support. Self-service analytics is often characterized by simple-to-use BI tools with basic analytic capabilities and an underlying data model that has been simplified or scaled down for ease of understanding and straightforward data access.
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The impact of self-service analytics on the enterprise is profound in many ways. It considerably expedites access to data and analytic results, competitive tools can eliminate the previously dominant silo approach, and it puts greater amounts of data in the reaches of business personnel who actually use them.
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The bottom line? Business leaders are now free to focus on what they do with the data they collect, not how they go about getting it. A Cultural Shift: How You Make It Real. Of course you know the old adage "You can lead a horse to water.". It may be a bit clich, but it definitely applies when moving to a self-service analytics approach.