5 self-service BI best practices for larger organizations
Self-service analytics programs can streamline the BI process by allowing users access to data, but scaling out to thousands of users requires proper planning.
The idea behind self-service BI is fairly simple: Put analytical power into the hands of the business users who most need it to make timely decisions. When normal line-of-business users are empowered by organizations with established self-service BI best practices, they’re able to run queries, build reports and create visualizations that give them focused insight into the business trends most relevant to them — all with minimal input from IT or even the business analysts.
However, while the driver is simple, the execution of self-service analytics is far more complex. It’s all easier said than done when it comes to setting up a self-service BI program that can scale reliably across thousands of users.
“Organizations want to get the data in the hands of the people who are closest to it, without having to call IT,” said Brian Moffo, director of analytics delivery at Anexinet. “However, most organizations are not ready for it. Organizational readiness, data quality and governance are the biggest challenges. Simply turning on the data faucet in the enterprise could be dangerous. Exploratory data can become gospel and published as fact.”