The Definitive 10-Point Scorecard Before Choosing a BI Solution

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The Definitive 10-Point Scorecard Before Choosing a BI Solution

There are a ton of choices these days! In this overview, we are putting through a 10-point checklist for business intelligence platforms

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Picking a business intelligence (BI) tool is hard. It is not uncommon for those who shop for BI tools to struggle with the decision. There are a ton of choices these days! In this overview, we are putting through a 10-point checklist for business intelligence platforms:

The 10-Point Checklist For BI Tools 

We suggest framing each choice with a consistent set of criteria. This means using a set of objective benchmarks to narrow down the hundreds of options to a few that are worthy of a demo. This simple, easy to use 10 point checklist, can help frame your tools assessment endeavors:

1. Target Audience

Is this BI tool built for engineers or business users? Will we be happy with using this every day? Make sure you are aligning your use cases to the intended users internally. If the tool is not something people will enjoy using, it is a certainty it won’t be used at all.

2. Features

What is the tool great at? What areas of focus and emphasis do they have? How quickly can I be productive? What is my time-to-value? Also, what does the product roadmap look like? Does it mesh with my strategic vision for the work I need to get done? Does the tool include must-have features like supported data sources, filters, data visualizations, etc. that are easy to understand? For example, the BI analytics tool may stand out for its stunning visualizations like Tableau, its simple and easy-to-follow interface like Chartio, its great collaboration capabilities like Mode, or its data exploration capabilities like Looker. For features that are lacking, decide if you and your team can live without them. Ask yourself whether they nice to have or are critical to the mission.

3. Technology

On the technology side, you should look at what databases the BI analytics tool supports. Can it connect to your cloud data warehouse like Amazon Redshift, Amazon Athena, or Google BigQuery? Can it connect to on-premise systems? Do users interact via browser (cloud only) or is this a desktop app, server software? All of the above? Which operating systems the BI tool supports? Is it Windows? Mac? Linux? What are the hardware requirements needed to run? Does the technology align with your current or future state environments? 

4. Collaboration

How can people working together create and update outputs visualizations, models, and calculations? Does the tool help with knowledge and resource sharing? Can code snippets, templates or reports be packaged for use across a broader team?

5. Education

What kind of training and learning material is available? Some business intelligence and analytics tools are intuitive, some have short learning curves, but some will require deeper training. Make sure to define how much time you are ready to invest in learning. Are there videos or self-paced online classes? Does it provide free training or specific paid courses? Does it fit with the learning style of your company?

6. Community

Does it have robust online communities, forums, enthusiast blogs, passionate evangelist users, local meetups, or user groups? Is the community driven by the company or are users are forming an organic community? Both? You want to make sure that you can get answers and learn from experts when you hit a roadblock.

7. Customers

Customer reviews serve as proof points on what the tool is claiming to deliver. Look at who is using it: Coca-Cola? Apple? Starbucks? Big companies? Mostly small companies? Is it teams or individuals? Both? Would they purchase again? Don’t hesitate to reach out to a customer referenced by the company to validate their experiences.

8. Support

The provider of the tool knows best how to overcome issues. Find out how support is provided. Is it paid? Free? Contact online, call, chat? Does the support model work for your company?

9. Partners

Are there consultants, freelancers or people that can be hired or provide value-added services around the product? If yes, how robust is that partner ecosystem? If the tool is complex, you may consider third-party support to make kickstart your data analytics efforts.

10. Cost

How is the product priced? Does it fit budgets? What trade-offs are you willing to accept at different price points? Do they offer discounts at scale? For long-term commitments? Knowing how BI tool is priced can help set up budgets accordingly. Are you a growing company? Is your analytics team growing? Consider possible changes in your team.

6 Business Intelligence Tools Reviewed

For reference, we put the following six tools thru this checklist. The goal of the checklist is to establish a vetted consideration set. As such, these reviews are meant to be starting points to exploring options, not definitive answers, to determine what tools work best.

  1. Is Tableau Right For You? 10-Point Checklist to Make the Right Decision

  2. Is Microsoft Power BI Right for You? 10-Point Checklist to Make the Right Decision

  3. Looker: Embrace the Face of Business Intelligence Innovation While Avoiding Getting Tripped Up

  4. Mode Analytics — The Right Choice For You — Face the Opportunity With a 10-Point Checklist

  5. Chartio: The 10-Point Checklist to Pick Your Next Business Intelligence Tool

  6. Qlikview: Finding The Right Business Intelligence Platform Faces Risks in the Pursuit of Insights

Don’t Forget About The Data That Fuels BI Tools

An often overlooked aspect of BI efforts is the data. Sounds obvious, but it is anything but obvious. As a general rule data should never be locked away in a source system, analytics tool or data management platform. If it is locked away, then data is NOT a first class organizational asset. Unfortunately, when data is spread across different systems it is anything but that. All of the “dark data” represents a treasure trove of consumer insight that should be available and ready to be used by your team. You need to make sure “pipelines” exist to ensure the adequate flow of data to your tool(s). 

What are pipelines you ask? A pipeline solves the logistics of moving a resource from a place of low value to a place of high value.For example, pipelines move water from reservoirs (low value location) to homes (high value location). 

In the context of BI tools, a data pipeline solves the logistics between data sources (systems where data resides) and data consumers (those who need access to data) for processing, visualizations, transformations, routing, reporting or creating statistical models.

As you seek to implement BI solutions, don’t overlook the fact the data needed to fuel those tools may require further consideration. With the data pipelines in place you can mobilize data to your BI software.


Not all tools are perfect for all users, teams or companies. Once you have narrowed down your consideration set to a few candidates, then experiment with each before committing (i.e, purchasing) licenses or long term contracts. Most vendors offer free trials, so take advantage of those! Use a familiar datasets to explore how asking questions of your data works within the software. Try out different visualizations, reports, dashboards to asses your comfort level with the user interface. Validate your assessment from the checklist to meet (or exceed!) expectations.

Lastly, make sure you have an “evangelist” or “advocate” internally, someone who is passionate about the solution and adoption within the company. If you don’t have a person or team who is passionate about the solution you will find your BI software is just as productive as a gym membership 4 weeks after the New Years resolution that prompted it.

big data, business intelligence, data analytics, data visualization

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