Making Self-Service Analytics Work: Organizational, Architectural, and Governance Issues 

Self-service analytics has been the holy grail of data analytics leaders for the past two decades. Although analytical tools have improved significantly, it is notoriously difficult to achieve the promise of self-service analytics. This session will explain how to empower business users to create their own reports and models without creating data chaos. Specifically, it examines seven factors for leading a successful BI program: right roles, right processes, right tools, right organization, right architecture, right governance, and right leadership. Ultimately, it will show how to build a self-sustaining analytical culture that balances speed and standards, agility and architecture, and self-service and governance.

You will learn:

  • Trends and business dynamics driving analytics adoption
  • The conundrum of self-service analytics
  • Success factors for leading a successful BI program
  • How to survive and thrive in the new world of big data analytics
  • How to increase user adoption and facilitate self service