In recent years, the use of 'self-service business intelligence' (BI) in internal organisational processes has increased so rapidly that it has become an integral part of workers' roles.

Put simply, 'self-service BI' enables users to develop and create their own reports independently, without technical support.

As organisations strive to create data-driven environments as part of their business strategy, self-service BI tools have become essential for achieving these objectives.

In this article, we will explore how it works, its benefits and considerations for implementation.

Understanding Self-Service BI and Its Strategic Relevance

As mentioned above, self-service BI empowers workers in various business roles to analyse datasets and create reports to support decision-making processes. They can do this fully autonomously, without needing to consult the IT department.

In contrast, traditional BI tools require technical expertise to use, leading to high demand from business departments and significantly slowing the analysis process.

Examples of self-service BI tools praised by workers today include Microsoft Power BI, Tableau and Qlik.

As demand for faster processes and data-driven decision-making grows, self-service BI tools have developed in recent years. The expansion of the volume of data has made these tools essential for easing the workload on IT resources.

In this way, they reduce business teams' dependence on IT and consequently improve the organisation's agility.

Unlocking Data Potential: Features and Benefits of Self-Service BI

In addition to reducing the risk of IT bottlenecks, Self Service BI improves data literacy and provides faster insights. It also improves communication and transparency across departments.

Thanks to intuitive interfaces and user-friendly features such as drag-and-drop functionality and mobile access, these tools are tailored to the skill levels of business users, enabling them to customise dashboards and visualise data effectively.

The rise of generative AI also helps employees by supporting them with natural language chat while they fulfil their tasks. Copilot, for example, is an AI model developed by Microsoft that is directly integrated into Power BI.

Making Self-Service BI Work: Common Pitfalls and How to Avoid Them

Implementing self-service BI in your organisation can't be done without proper training and preparation.

One of the challenges is ensuring that integrating self-service BI tools does not compromise quality control or lead to data being misinterpreted, particularly when users lack formal training in data analysis.

The best way to solve this is to design a clear, objective-driven plan involving both IT and business users, alongside a robust governance framework.

It is important to choose the right tools that match your existing IT systems to guarantee compatibility and avoid overwhelming the IT department and causing conflicts with business teams.

Don't hesitate to offer training and support — your employees will appreciate it and feel more confident about adopting these new tools.

In conclusion, self-service BI tools are an important asset for your data strategy, fostering a data-driven framework and agile management compared to traditional business intelligence tools.