Self-service analytics removes the gap between data and business users. Tools like Power BI, Tableau, and Looker provide easy-to-use platforms that allow employees — without technical backgrounds — to generate reports and analyse key metrics. This improves efficiency and nurtures a data-driven mindset across the organisation. Modern data infrastructure, typically, enable this by offering robust, integrated solutions that centralise data access and streamline analytics processes. 

To get self-service data analytics right, follow these steps: 

• Select the Right Platform – Pick the tools that meet your needs, like Power BI or Tableau.
• Design User-Friendly Dashboards – Create accessible interfaces that deliver key insights instantly.
• Train Employees – Ensure your team knows how to make the most of these tools. 

We implemented self-service analytics for several companies, like Hudson, NetRefer, and Atlas Insurance. The integration, as reported by the companies, led them to faster decision-making, reduced IT workloads, and improved efficiency.  

Netrefer noted that the implementation of self-service analytics made insights accessible to non-technical users, which allows them to optimise their marketing strategy effectively. 

The next phase in self-service analytics is AI-powered chat agents. These tools interact directly with data, allowing users to ask questions and generate reports through natural language queries – no dashboard experience required. See the AI-powered chat agent in action at the screenshot of Eunoia model below.  

Self-service analytics is essential for thriving in a world where data volumes are growing exponentially. By empowering employees to analyse and interpret data independently, companies can drive innovation and make smarter strategic decisions.