Chapter 1. Search-Driven Business Analytics

We are all accustomed to instant results with the use of major web search engines. However, when we pull up a business intelligence (BI) product at work, the situation is quite different. In comparison to Internet services that we use every day, these products seem stiff and unresponsive. Business leaders are served with pre-built reports and dashboards put together by their BI teams, and they wait days or weeks to get reports on new inquiries about customers, products, or markets. Thus, when a business manager moves from Facebook,, or Google to her BI tool, it feels like time travel back to a different century.

This report examines what it takes to make business intelligence as simple and responsive as today’s consumer search engines, where the user gets answers and visualizations as quickly as questions come to mind.

We’ll look at:

  • The convergence of BI and search
  • What a search-driven user experience looks like
  • The intelligence required for analytical search
  • Data sources and their associated data modeling requirements
  • Turning on-the-fly calculations into visualizations
  • Applying enterprise scale and security to search

The techniques described here are general and draw on well-established practices in the field. The main reference platform for this report is the ThoughtSpot Analytical Search Appliance. The author will also incorporate information gleaned from discussions with technical staff from Microsoft’s Power BI service ...

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