SYS-CON MEDIA Authors: Pat Romanski, Gary Arora, Zakia Bouachraoui, Yeshim Deniz, Liz McMillan

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The 10-Point Checklist for Choosing the Right Analytics Tool

Choosing the Right Business Intelligence tool

Picking a business intelligence (BI) tool is hard. According to Scott Brinker and his Marketing technology Landscape there are over two hundred BI and data visualization solutions. This is a lot of choices to review before you can make a decision. In this overview, we are putting six tools through a 10-point checklist for choosing the BI solution: Tableau, Looker, Mode Analytics, Chartio, Qlikview and Power BI. The goal of the checklist is to establish a vetted consideration set.

The 10-Point Checklist For BI Tools

When it come to make a choice, for any decision you need to have consistent set of criteria. For BI tools 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. These reviews are meant to be starting points to exploring options, not definitive answers, to determine what tools work best:

1. Tableau

2. Power BI

3. Mode Analytics

4. Chartio

5. Qlikview

6. Looker

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 is data pipeline?

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.

Making a choice

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.

More Stories By Thomas Spicer

Thomas Spicer is a Founder and CEO at Openbridge, a data delivery platform. With 20+ years of client delivery and management experience for teams like Digitas, Cramer, Studiocom, VML/WPP across all aspects of both digital and traditional marketing, he is now successfully helping teams and enterprises to solve challenges of collecting and managing data across multiple channels and deliver value faster.

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