Self-service reporting is an analytics paradigm that places the emphasis for data analysis and report-building on individual users instead of highly trained statisticians or data scientists.
Self-service BI and analytics are built around the idea that users should have access to the data that informs their major business and operational decisions, even if they haven’t been heavily trained in analysis.
In practice, self-service reporting tools allow users to make queries, create reports and visualizations and more by offering a straightforward and easy to navigate interface that facilitates the analytics process. In many cases, users can replace the complex search queries and parameters most statistical analysis employs in favor of more natural questions.
Self-service analytics is defined by how easy it is for business users—not IT professionals—to access information. This consideration includes three main pillars: how easily users can connect to the data; how simple or complex their queries must be; and how self-sufficient users are in utilizing the data analytics tools.
The best self-service reporting systems let users have direct access to data and require little technical knowledge to get actionable BI insights and accurate reports. Most importantly, self-service reporting tools should be intuitive and interactive, letting users play with data as they need to find insights.
How Can I Use Self-Service Reporting?
One of self-service reporting and analytics major goals is expediting the process of data discovery and insight-gathering. A major use for self-service reporting tool is the creation of interactive and real-time dashboards that offer answers to questions as they occur.
See it in action:
This removes many barriers to implementing new solutions, as time becomes a non-factor when business users can directly view data.
Another major use for self-service analytics is in creating a foundation for deeper analysis down the line. Many times, users find important questions to ask, but lack the technical knowledge to find answers.
Self-service reporting allows users to create a background and understand the basics of their questions, and create better queries for data scientists on their team to find specific answers.
Finally, self-service reporting tools are useful for team members who are looking to create reports or dashboards. By having more open access to underlying data, they are able to create more accurate reports and visualizations and find better insights to apply to operations.