Also known as: Self-service analytics, self-service business intelligence

Self-service BI describes the tools and processes that enable regular business users within an organization to analyze data, deploy and query their own reports, and share insights using simplified interfaces that help them make data-led business decisions. These solutions are typically tailored for non-technical users, with minimal coding required to effectively use them.

Self-service BI makes it possible for everyone to identify, analyze and action specific analytical opportunities, without having to engage with analysts or IT for access to data or report creation and delivery. It brings the analytical workload to the user, and when applied correctly, allows for timelier decision-making, increased workplace productivity and accelerated discovery of insights by ensuring people are focused on the analytic process with which their skills are best aligned.

Best practice for self-service BI 

In the past, self-service BI was limited because it focused on one specific stage of the analytics life-cycle, such as dashboards or visualizations. Today, success with self-service BI is conditional on choosing a leading analytics platform that can deliver the full level of required capability across the complete analytic pipeline. Modern self-service BI tools leverage the latest technology and provide extensive tool sets that can enable users of all skill levels to access, explore, analyze and deliver both data and analytics when and where it’s needed using a number of capabilities, such as data storytelling, automated analytics and contextual insights.

Users care about using tools that help them do their job better, so it’s critical to choose the best solution that does this and that offers powerful tools that actively guide users when conducting their own BI. Otherwise, your self-service BI solution may be underutilized or undervalued.

Ultimately, successful usage of self-service analytics is tied to business objectives and outcomes. The key questions the organization is trying to answer must be established upfront, because only when you know what you are looking for will you be capable of identifying exactly what’s essential to have from an analytics solution (in terms of data and analysis) in order to deliver all your users measurable business benefits and improved decision-making.