Self-service business intelligence (BI) is an approach to data analytics that allows employees to access and work with corporate data, even if they do not have a background in statistical analysis. The goal of self-service BI is to democratize the use of data within an organization and drive
positive business outcomes.
The process for getting data from traditional BI tools used to be complicated. In the past, when an employee requested data to be made available, they had to build a business case and get the request approved as a project. Once the project was approved, the data could be extracted, transformed and loaded into an operational data warehouse, and someone on the data analytics team would produce a report that contained the requested data.
In contrast, a self-service BI architecture is designed for ad hoc data analysis by people who may not be tech-savvy. Enabling end users to make decisions based on their own queries and analyses frees up the organization's BI and IT teams from creating the majority of reports; they can focus on other tasks that will help the organization reach its
Proponents maintain that self-service BI software reduces the anxiety employees experience when plunged into a data-centric culture. Critics of self-service analytics maintain that only a trained data scientist can reliably understand the meaning of certain data correlations, and if the analysis process is mismanaged or the underlying data is of poor quality, it can lead to potentially damaging decisions. Continue reading...