If your organization is like many others, when you look back on past data analytics projects, you probably deem them unsuccessful. Sometimes the cause was expected: delays, cost overruns, and so on. But the most common reason is more fundamental: In many cases, an organization selected a data analytics tool that ultimately failed to meet users’ needs.
That is an issue that the increasingly popular self-service analytics piece aims to address. Rather than being limited to the information you are given, self-service tools allow you to create the analytics, reports, and dashboards you need.
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