BI Trends

Self-Service Analytics: This time, it’s Different

By Alvin Wong
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In the world of business intelligence, the demand for self-service BI is louder than ever. Business users are clamoring to access more data and information when they need it, without getting IT involved.

But haven’t we heard this before? After all, Online Analytical Processing (OLAP) had its heyday, followed by ad hoc queries soon after.

But don’t be lulled into a sense of complacency or ambivalence regarding self-service BI: It really is different this time around.

The evolution of self-service has transitioned over the years. SaaS business app such as were some of the first to embrace self-service, enabling many companies to stand up systems to support the business without getting IT involved. And if business applications cannot supply the necessary reporting on their own, business users often will continue their self-service journey and usually end up in Microsoft Excel. The downside for users is that Excel can be laborious to use. And once users get to pivot tables and need to pull data together from multiple sources, it can become quite a painful experience.

This was followed in recent years by, desktop data discovery tools, which are especially popular with data analysts. These tools have made it easy to do some of the things that spreadsheets have not excelled at, specifically in the area of data visualizations and visual analysis. These tools have embraced ease of use, speed of analysis, and engaging user experiences. It’s no wonder that the growth of data-discovery tools from a business-driven, or bottom-up, approach is now seen as stepping into the bounds of traditional IT-driven business intelligence, known as the top-down approach.

The state of self-service BI today is shifting mix of decentralized, business-driven approaches at the departmental level and centralized, IT-driven approaches delivered to the business. And it’s this collaboration that is helping to drive its success.

I recently explored this self-service evolution in Data Informed. In the article I dive further into the factors behind the transition, the challenges that business still face, and the path forward to self-service success. You can read the full article here.


Originally published February 16, 2016; updated on June 15th, 2018

About the Author

Alvin Wong has an extensive background in solution architecture and implementation of SaaS and business intelligence applications. Alvin earned his MS in Engineering Management from Stanford University and BS in Electrical Engineering from Cornell University.