How to choose a BI tool: 9 criteria and a selection process

Choosing a BI tool often starts with vendor presentations: beautiful dashboards, animations, promises of "self-service analytics in a week". Six months later it turns out the tool cannot connect to the main accounting database, licenses cost more than planned and only three people use the reports.

To avoid this, choose based on your own tasks, data and constraints, not on the demo. Below is a selection process and nine criteria for comparing BI tools.

Tasks first, tool second

Before comparing tools, answer a few questions:

• Who will use the reports? Executives who need five key metrics on their phone and analysts building complex breakdowns are different audiences with different needs.
• Which business questions should BI answer? Write down 10–15 specific questions: "how is margin changing by category", "which branches are behind plan". These questions will later become the scenarios for the pilot.
• Where does the data come from? Accounting systems, CRM, POS, files, cloud services — and how ready this data is for analysis.
• Who will develop the reporting? Your own team, a contractor or business users themselves.

At this stage, it often turns out that the main problem is not the tool but the data: the numbers already disagree in the sources. Then you first need data marts or a data warehouse and shared metric definitions, and only then a BI tool.

9 selection criteria

1. Connection to your sources

Check whether there are ready-made connectors to your systems and databases, and how the tool works with data: whether it queries the source directly or loads a copy. A direct connection gives fresh data but loads the source; a copy is faster but refreshes on a schedule.

2. Where the data is stored

A cloud BI tool stores data and reports on the vendor's servers. The laws of a number of countries, including Russia and Saudi Arabia, restrict storing personal data and transferring it abroad. If your reports contain customer or employee data, find out where the servers are located and consider installing the tool on your own infrastructure.

3. Total cost of ownership

Compare not the license price but the cost over three years:

• licenses: per user, per server core or per data volume;
• infrastructure, if the tool runs on your own servers;
• report development and support;
• user training.

Per-user pricing works well when dozens of people use the reports and becomes expensive when there are hundreds. Open-source tools require no licenses but need more engineering work.

4. Ease of use for business users

Let future users work with the tool themselves: filter a report, find a number, export data. If they have to go to an analyst for every question, self-service BI will not happen, however powerful the tool is.

5. Shared metrics

A good BI tool lets you define a metric once — revenue or margin, for example — and use that definition in every report. If each report calculates a metric with its own formula, the discrepancies between departments will come back, this time inside BI.

6. Access control

Check whether you can restrict access not only to reports but to rows of data: a branch manager sees only their branch, a division head only their division. Single sign-on with corporate accounts and a user activity log also matter.

7. Performance on your volumes

A demo on a small dataset is fast for everyone. Test speed on your real volumes: how long a key report takes to open, how the filters behave, what happens when dozens of users open a report at the same time.

8. How reports reach people

Think about how users will get information: a mobile app, scheduled report delivery by email or messenger, alerts on deviations, dashboards embedded in an internal portal or CRM.

9. Availability and specialists

Some foreign services have restrictions on sales and support in certain countries. Make sure the tool can be legally bought and updated in your country. Also assess the talent market: how easy it is to find report developers for the chosen tool.

Types of BI tools

Type	Examples	When it fits
Enterprise platforms	Power BI, Tableau, Qlik	Many users, complex reporting, willingness to pay for licenses
Cloud services	Looker Studio, Yandex DataLens	Quick start, data already in the cloud, no requirement to keep it in-house
Open-source tools	Apache Superset, Metabase	Need to deploy on your own servers, engineers available for support

The split is approximate: many cloud services have self-hosted editions, and open-source tools offer paid cloud plans.

How to run the selection

1. Make a shortlist of 2–3 tools based on the criteria that are mandatory for you: data storage, sources, budget.
2. Run a pilot on your own data. Take 3–5 questions from your list and build reports for them in each tool. Two to four weeks of piloting tell you more than a dozen presentations.
3. Involve future users and ask them to rate the tools with the same questionnaire: ease of use, speed, clarity.
4. Calculate the three-year cost, taking into account growth in users and data volume.

Common mistakes

• Choosing by the vendor's demo rather than by your own data and scenarios.
• Moving the old chaos into the new tool. If the numbers disagree in the sources, BI will show the same discrepancies, just more beautifully.
• Building hundreds of reports at once. A dozen reports used every day beat a hundred nobody opens.
• Forgetting about support. Reports need to evolve: business questions, sources and company structure change.

Summary

A BI tool is chosen to fit the company's tasks, data and constraints, not the other way around. First, formulate the business questions and check whether the data is ready; then compare 2–3 tools on the criteria that matter to you and run a pilot on real data.

If you need help with selection or implementation, see our Analytics & BI service: we choose a tool that fits the task and budget, prepare the data and build reporting that people actually use.