Choosing the Right BI Tool for Your Business

Here are six questions to ask as you search for the best BI tool for your specific needs.

By Angshuman Guha, Founder and CEO, bipp Analytics

Photo by Christina Morillo from Pexels

If you believe the hype, data-driven decision-making is taking over businesses. As they try to speed up decisions, whether it's adjusting supply chains to deciding which product lines to focus on, it's clear that intuition is nothing without insight. In response, both large enterprises and midsize businesses want to take advantage of easier-to-use BI tools with self-service capabilities. But while this has accelerated the uptake of BI and analytics tools in companies of all sizes, BI buyers learn that one size does not fit all.

The reality is, there are more than 100 BI platforms are on the market (without starting to count embedded analytics capabilities in standalone apps and packages). Gartner’s 2020 review lists 151 companies and almost 13,0000 reviews. Each company has strengths. But in such a crowded market, choosing the right tool for your needs is no easy task.

The selection process starts with clarifying the business requirements you have and the use case where you’ll be applying it. This sounds obvious (spoiler - it is), but it is worth debating with your team. Measure twice, cut once, and all that. Think long and hard about what you and your teams want to measure, classify and decide. What are the KPIs? How many disparate data sources do you need to blend? And what decisions do you want your BI tool to inform? Also, carefully consider the constraints you’re operating in, such as financial resources, time limitations, and the expertise you have available.

The last point is critical. If you’re looking for a magical unicorn BI tool that can simply be pointed at your databases and then whispered to like Alexa for your insights, you’ll be waiting a while. The more complex and mission-critical your BI needs, the more you’ll need a BI analyst on your side (or a friendly start-up that can give you some demand…).

You get this. It’s a complicated process. So here are six questions to ask as you search for the best BI tool for your specific needs.


1. Why do you want a BI platform?

It’s critical to be clear on the specific problems you’ll use the BI tool to attack. Different companies, departments, and employees have different needs and requirements.

i) Will you be using it for analytics on a specific business-critical application?

While many vendors will offer a magical solution that offers BI on top of your preferred third-party or proprietary applications, the best solution is to use a layered approach and pick a platform for that layer. With cloud-based data warehouses, analytical and columnar databases becoming so common and powerful, it is best to invest in an ETL pipeline to bring your data to the data warehouse.

ii) Will users ‘go it alone,’ or will they need the support of dedicated data analysts?

DIY BI is standard in smaller startup teams, who’ve historically relied on in-application analytics or aggregating in a tool like Excel or Google Sheets. Alternatively, they may be using a cloud analytic tool that promises a quick time to value insights. It is a question of what people are expected to do with their data. Do they need a simple, static visualization or report? Or will they want to manage new queries by themselves?

iii) Do you have in-house data analysts to connect the database and build data models?

If you want to connect cloud-based apps and run canned visualizations, then a free BI platform may be all you need. But as companies grow, their data reporting and insight needs become more complex. Not rocket science, but you may need a BI analyst who can help your teams connect the dots between data and insight.

Or, you might need a tool that helps bridge the gap between the SQL-loving BI analyst and the business analyst who’s managing the connection between BI and business. A data-modeling tool like bippLang could help here, making it easier for data analysts or data explorers to interrogate datasets and build dashboards.

Again, possibly a case for finding a BI platform that meets the needs of the hard-core BI analysts, the part-time analysts, pure business analysts, and ultimately the end-users across your organization. And if you don’t have all of these needs today, you can bet that you’ll have them as your company grows.


2. Do you require an on-premise, SaaS, or custom cloud deployment?

If you read the headlines, you’d assume that corporate environments are abandoning on-premise en masse and that everyone now has their heads (well, their data, apps, storage, networking, and processing may be) in the cloud. The key is for companies to work out what data should go to the cloud, the edge, or stay on-prem.

Issues such as securing privacy and security on an extended network, workloads, and data volume combine to ensure on-premise will be around for some time. If this is how your company views the world, then obviously, on-prem support is a priority in your BI tool RFP.

Suppose you need a custom, flexible deployment across multiple clouds such as AWS, GCP, or Azure (perhaps spurred by widespread remote working, having to merge environments, and the lure of low-cost cloud providers). In this case, you’ll need a BI vendor that connects to more than one cloud computing service).

And if you’re hedging your bets or work in a hybrid world, then consider a vendor that can manage both deployments.


3. What level of self-service do your end users want?

The promise of self-service BI is to unlock the power of analytics to a much larger audience across an organization. It allows users to connect to the database and intuitively build reports, and support the vision of actual data-driven decision-making. The idea is great in theory, and it can work well once the data dictionaries have been vetted, cleaned up, and organized by data analysts.

But you may need a tool for a dedicated technical team who can manage the ‘engine room.’ They'll define the key metrics, KPIs, custom columns or dimensions, table join relationships, and so on. Also known as the data model. Once they’ve built this foundation, they can empower the non-technical business users to create their reports and queries, drill down into row-level detail and schedule their dashboards.

If you have business needs for agreed, consistent reports, and consistent KPIs, self-service can help reduce analyst time, and citizen analysts can access the data they want. It can also reduce the revisions and pressure on business analysts to interpret business needs and ‘translate’ for their internal clients. A third benefit is relieving stress on IT teams in smaller organizations, who may have inherited BI roles but be ill-suited for them.

If this is your need, your data team will benefit from a data modeling language, which allows the data team to create reusable, complex data models for their business communities(instead of rewriting the same SQL fragments repeatedly).

This blend of human expertise and powerful, enterprise-class technology will continue to be vital if you want a larger audience to pull ad hoc reports supporting their OKRs, understand taxonomies or monitor goals against targets.

So look for a BI tool that also prioritizes bringing fast, accurate insights to end-users. Consider features like interactive dashboards and other visualizations that enable users to absorb information and identify patterns so they can make quick, evidence-based decisions.


4. How will it help your team collaborate?

The right tool needs to support how your team works together — both the business users, analysts, and broader data community. Based on bipp’s research of more than 200 data analysts, one in five data analysts report that collaboration limitations and lack of real-time data are significant challenges of their business intelligence platforms.

The BI tool should support collaboration by helping you share reports, dashboards, and datasets very easily. Whereas simple tools stop here, premium platforms are rich in collaboration features and allow fine-grained permissions, groups, and roles. They help organize and group content such as dashboards, ad-hoc reports, and datasets based on your internal team structure. They also provide more powerful sharing options with custom roles and permissions. Another helpful feature is report or dashboard scheduling, which allows you to set up automatic report delivery via email.

On the data analyst side, modern collaboration is just not complete without Git-based version control, which goes beyond just letting analysts share their work in the background. It merges knowledge from various team members and saves a snapshot history of all the changes, which helps track changes. In-database analytics is another feature to look for since it allows analysts to process data within the database. Hence, everyone in the organization makes decisions based on the same data.


5. How much does it cost? And will you be there when I need help?

We cheated a little here as these are two questions. But you really can’t look at the price without considering the potential hidden costs of your brand new BI platform. In particular, how will your vendor help you get the most out of a tool that really should change your business?

According to, the price-performance ratio is a BI buyer’s second most important criteria when selecting their BI software. And this is only becoming more important as BI platforms evolve from experts in dark rooms to sitting on users’ desktops across a business.

As you go through your buying process, verify your BI tool makes it easy for you to get going without frustrating roadblocks or excessive fees. Consider:

  • Do they offer a free test drive with complete enterprise features? Or is it a gimmicky free trial that requires you to pay a minimum of $10,000 — $20,000 a year to keep using it?
  • How will they support your set-up and user onboarding?
  • Is there someone on-call if you or your users get stuck?
  • Do they have documentation designed for a range of use cases?
  • Is your vendor thinking ahead and considering how the deployment scales as you add more users?
  • Does your preferred vendor offer a convenient per-user pricing model that simplifies budgeting based on user need? Or is it flat cost, whether the user passively receives a report or is a full-time data scientist?
  • Are there additional costs for data management or extra API calls?

A lot to consider, but if your company’s vision is for your BI platform to be a growth and decision-making engine, then make sure you know what’s in the box (and outside of it).


6. Does your BI platform support real-time decision making?

Today’s enterprises involve more than business analysts and data analysts in the decision making process. Many forward-looking firms are re-envisioning data science, which sees data analysis as a critical tool for making faster, better-informed decisions throughout the organization based on real-time data.

While many users simply need weekly or monthly sales reports, or access to long-term trends based on month-over-month or year-over-year comparisons, an increasing number of organizations want their BI tools to provide up-to-the-minute data.

Industries such as retail, transportation and logistics, the military, and weather-dependent companies such as ski resorts need to make operational choices based on the most current data or information.

If you need real-time insights, you’ll need a BI tool that executes SQL queries directly against the database rather than relying on an exported cube/extract. Such a tool leverages modern database features such as column-oriented databases. These allow for fast retrieval of columns of data because they scale using distributed clusters of low-cost hardware to increase throughput.

There’s pressure on all businesses to make better use of data. Your BI platform decision shouldn’t be taken lightly. I hope these six questions help you on your quest to find a BI tool that meets your business’s unique needs. And that they keep you away from magical unicorns...

Bio: Angshuman Guha (@angshuman_guha) is Founder and CEO, bipp Analytics.