Why comparing BI software pays off
The market for business intelligence tools has evolved significantly in recent years. Where reporting used to be limited to static overviews in Excel or ERP systems, today interactive dashboards, self-service BI and advanced data analysis are available for every organization. From start-up to multinational: every organization works with data, but not every BI solution fits every type of company. That's why it's crucial to compare tools based on relevant criteria. This article provides an in-depth guide to help you make an informed choice.
What is business intelligence software?
Business intelligence (BI) software is a generic name for applications that collect, structure, analyze and visualize data to make better business decisions. Think dashboards, reports, data models and forecasts. Popular tools such as Power BI, Qlik Sense, InsightData, and Tableau translate raw data into clear insights. But how they do that varies considerably by platform.
Why choosing the right tool is essential
A wrong choice often leads to frustration, low adoption or inefficiency. You pay for licenses without results, users stick to Excel, and dashboards are not shared or maintained. The right tool, on the other hand, increases data skills in your organization, accelerates decisions and creates support for data-driven work.
Standard criteria for comparing BI tools
To compare tools objectively, it is best to use fixed assessment criteria. We explain the most important ones:
1. Usability
How intuitive is the interface? Can non-technical users build dashboards themselves? Is there a clear onboarding or do you need a lot of click steps?
2. Visualization options
Does the tool support interactive charts, drill downs, custom visuals, and responsive design? Are the visuals appealing, and how well do they perform on mobile devices?
3. Connectivity to data sources
Can you easily connect to your ERP (such as SAP, Microsoft Dynamics, Odoo), accounting, CRM, Excel files, or cloud services such as Google Analytics? Do you need to use additional software for this?
4. Data Modeling and Transformation
Does the tool offer opportunities to transform, combine or incorporate business logic? Does it support multiple tables, joins, and data types? Think DAX (Power BI) or the associative engine (Qlik).
5. Performance and scalability
Does the dashboard load fast? Will the tool remain effective with larger datasets or multiple users? Does it support caching, incremental loading, or live queries?
6. Licensing model and costs
Is there a free version? Do you pay per user, per capacity, or per month? Are there additional costs for collaboration, refresh, or premium features?
7. Security and Governance
Does the tool support per-user access rights, data masking, row-level security, audit logs, and central monitoring?
8. Community and Support
How active is the user community? Are there Dutch-language tutorials, official courses, support portals or consultancy partners?
Comparison of the most used BI tools
Below, we compare five of the most popular tools based on the criteria mentioned above.
Power BI
- Strengths: strong integration with Excel and the Microsoft environment, competitive price, powerful visuals, user-friendly for beginners
- Weaknesses: performance may decline with complex data models, less suitable for complex ETL without Power Query or Dataflows, requires Microsoft Fabric very quickly
- Best for: companies with strong IT support
Qlik Sense
- Strengths: unique associative data engine, self-service BI, high performance with large data sets, visual expressiveness
- Weaknesses: higher learning curve
- Ideal for: data-savvy organizations, users who want to explore a lot
InsightData
- Strengths: accessible, quick to deploy, standard apps for all types of business data
- Weaknesses: Not active globally
- Best for: SMEs with limited IT support
Tableau
- Strengths: superior graphics, flexible data exploration, strong community
- Weaknesses: more expensive, often requires more technical knowledge, fewer standard governance tools
- Ideal for: organizations that focus on storytelling and data visualization
Looker (Google Cloud)
- Strengths: cloud-native, strong integration with BigQuery and GCP, LookML for standardized modeling
- Weaknesses: complex at the start, requires more IT involvement
- Ideal for: companies that already work with Google Cloud or are taking a data warehouse-first approach
How do you make a good choice for your BI tool?
- Start with a needs analysis: which users should report and analyse, how many data sources, what frequency?
- Determine your budget and the desired scale level.
- Make a shortlist and request demos or a proof of concept project.
- Involve end users in the evaluation.
- Look beyond the tool: also pay attention to implementation partners, documentation, training and support.
Mistakes to avoid when choosing BI software
- Choose a tool based on popularity without internal analysis
- Outsource everything to IT without user input
- Don't take future growth or integrations into account
- Ignore poor data quality: a tool is only as good as your source data
Continue reading? Check out our specific comparisons:
See how Power BI compares to the pre-configured InsightData apps on Qlik Sense.
Find out if Qlik Sense or Tableau is a better fit for your data strategy.
Compare Power BI to Looker in terms of cloud functionality, governance, and scalability.
Learn when to switch from Excel to Power BI for more efficient reporting.
Discover the key differences between Power BI and Qlik Sense in analytics power and flexibility.
Conclusion
There is no universal “best” BI platform. But by comparing tools on relevant criteria, you are making the best choice for your organization. Take time to analyze needs, test tools, and engage users. Because a good tool is not only technically strong, but also supported by those who work with it.