july 28, 2025
6 common misconceptions when choosing a BI system
Selecting and implementing a BI system is not just a technical task — it’s a strategic one. Many companies approach it superficially, ultimately wasting money and ending up with a platform that no one actually uses.
Here are some common misconceptions businesses rely on when choosing a BI system — along with explanations of why they don’t work and what to do instead.
1. The most important thing is that the software is popular or highly ranked
Just because a piece of software appears at the top of a ranking doesn’t mean it’s mature enough or that the evaluations are unbiased. Some vendors publish their own rankings — where their product, unsurprisingly, always comes first.
The right approach is to assess the unique goals, challenges, and specific characteristics of your business, and choose BI software that aligns with those needs — relying on a well-rounded evaluation and proven practices from market leaders.
Conducting a pre-project audit of your data infrastructure can help you identify suitable BI tools and define a roadmap for implementation.
2. What matters most in BI is a user-friendly interface and beautiful visualisations
UX/UI and visualisation capabilities are indeed crucial for business users of BI systems. The more diverse, interactive, and visually appealing the charts, the easier it becomes to represent complex data in an understandable format.
A user-friendly interface simplifies interaction with the BI platform, shortens training time, and boosts user productivity.
However, attractive visuals and convenient filters ≠ system performance, reliability, and scalability — which will become critical issues as your business grows.
When choosing a BI solution, don’t rely solely on polished dashboard demos. Evaluate the architecture, OLAP capabilities, advanced analytics tools, and the system’s data integration and processing features. With a basic understanding of good data visualisation and by building visual literacy, you can create informative dashboards even with a minimal set of charts.
3. BI will automatically solve all problems and clean up the data — all you need is an out-of-the-box solution
Mature BI platforms are designed based on standard use cases and industry best practices, which allows basic tasks to be solved with the default functionality. Built-in tools can automate parts of the data preparation process. BI really does make it possible to generate visual reports in just a few clicks — especially when compared to the manual effort of compiling reports in Excel.
However, BI tools don’t fix data quality — they only display the data as it is. If your source data contains errors or duplicates, these will appear in dashboards too, and users will once again be forced to manually verify metrics. Poor-quality dashboards full of errors — combined with the need to learn a new system — can erode trust in the data. Users may abandon the BI system and revert to familiar Excel workflows.
Moreover, out-of-the-box BI solutions don’t account for your unique business processes, integration needs, custom reporting requirements, or growth plans. At some point, customisation and further development will be necessary.
Before implementing BI, it’s important to carry out a preliminary data audit, introduce regular data quality practices, and foster a strong data culture within the organisation. A well-designed DWH will help consolidate and structure your data in preparation for future analytics.
4. Self-service means anyone can use BI easily
Self-service tools empower users to create dashboards without needing support from IT specialists. Most platforms include built-in connectors for popular data sources, intuitive data models, recommended visualisations, and user-friendly drag-and-drop interfaces that make it possible to configure dashboards in just a few clicks.
But even the most accessible self-service tools are ineffective if the user is seeing BI for the first time. To build meaningful applications, users must understand the source systems, data structure, business logic, and the platform’s features. Without proper guidance and motivation, employees will eventually grow tired of struggling with joins and primary keys on their own — and return to familiar Excel workflows.
That’s why it’s crucial to provide practical BI training that equips staff with hands-on skills and supports a new, data-driven way of working.
5. BI can be selected and implemented without involving business users
IT and data specialists do indeed have a better understanding of which platform will integrate smoothly into the company’s IT landscape, provide the required performance, flexibility, and security, and be easier to support and maintain. Their technical input can speed up the system selection process.
However, without input from business users, it’s impossible to properly define implementation goals or reporting requirements. If the data architecture and dashboard logic aren’t built around actual business processes, the system won’t help solve real business challenges. Users who haven’t been involved in the project will view the BI system as a foreign, complex tool — and are more likely to resist using it.
BI systems exist to support effective decision-making. Therefore, decisions about which data to analyse and how it should be broken down must come from the business side. This requires conducting interviews with stakeholders, clarifying their goals and expectations from the system. When choosing a BI platform, it’s important to evaluate not just functionality and ease of deployment, but also user-facing benefits — such as interface usability, variety of visualisations, and ease of learning.
6. The cost of BI = the cost of licences
Some BI platforms are marketed as «free», allowing companies to save on licensing costs and reduce project expenses — at least on the surface.
But BI implementation isn’t just about installing software — it’s a full-fledged project that inevitably involves additional expenses for customisation, infrastructure, training, support, and expert involvement, especially when choosing an open-source BI solution. The hidden costs of implementing a BI platform can easily exceed the cost of proprietary licences.
When selecting a BI system, focus not on perceived affordability or ease of deployment, but on total cost of ownership (TCO) — weighing both the strengths and limitations of different products. It’s worth exploring existing case studies, testing multiple platforms, and starting with a pilot implementation in a single functional area (e.g. sales, marketing, or production). Then, once you’ve validated the approach, you can scale the most suitable solution to cover other business needs.
The larger and more complex your BI project, the higher the cost of mistakes made during the platform selection process. Even the most popular BI tool doesn’t guarantee automatic solutions to your data and analytics challenges.
To choose the right tool, you need to define your unique business goals and objectives, assess existing processes and infrastructure, and gather user requirements.
