Top 11 Functional Requirements for Your BI Tool Evaluation

Post by 
Reading time: 3 min

(This is a multipart series about how to evaluate and select the right BI tool for you and your team. To see the entire outline of the series and a framework for how to evaluate a BI tool, see How to Select the Best BI Tool for You.)

Like shopping for a car or a new electronic device, there are likely a lot of features that the average Jane won’t need. We aim to cover the breadth of features that the top tools and analysts in the market are talking about.

It’s important to focus on what’s right for you and your use case. We recommend buyers be careful to not let features creep onto their “Want to have” or “Mission critical” lists when doing your research. It can be really easy to learn about a cool feature and then think about all the cool and creative ways you could use it. Curiosity and creativity is to be human.

Remember: You started shopping to fill a specific need. Keep that front and center as you research while getting educated on other cool features and how you may use them after your initial set of requirements are delivered.


What do we mean by Functional Requirements?

Functional Requirements is a category of capabilities that tools have or do not have, or rather, it’s a categorization of what you’d like your users to be able to do.

This is likely the category of requirements that your Business Users are most interested in.

Top Functional Requirements to Evaluate

1. Advanced Analytics

Features that support highly statistical analysis like clustering, regressions, predictive modeling, sentiment analysis, and time series forecasting.

2. Augmented Analytics

Features that automate workflows and analysis like automated data prep, forecasting, model tuning, and natural language search. 

3. Dashboarding and Data Visualization

Features that are core to what most people have come to expect from a BI tool front end like dashboarding, auto-charting, embedded visualizations, and drill-down and drill-up. 

4. Data Management

Features that are core to what most people have come to expect from a BI tool front end like data blending, data modeling, metadata management, and even advanced data prep using Python or R.

5. Data Querying

Features core to a BI tool’s back end data management and how it calculates data used in dashboards and reports.

6. Embedded Analytics

Features core to software development and cross-platform data handoffs and interactions between web apps and an analytics platform.

7. Geospatial Visualizations and Analysis

Features that support visualizing data on maps or images.

8. Internet of Things (IoT) Analytics

Features that support data with a very high velocity, like streaming data.

9. Mobile BI

Features that allow users to interact with their dashboards and reports on mobile devices like native apps, offline mode, and mobile collaboration.

10. Platform Functions

Features like collaboration, globalization, and write-back functionality.

11. Reporting

Features like ad-hoc reporting, report scheduling, alerts, formatting, exporting and versioning.


Follow the links above to read more about core functional requirements of a BI and analytics tool.

Did we miss something? Drop us a line and we’ll see about getting it added.

Need help with your BI tool selection? Book a call with us and we’ll see if we can help. If we can point you in the right direction with a short phone call, great! If you’d like to hire us to do an evaluation and selection for you, contact us and we’ll make a selection together.

Join Our
Data Analytics

Expect to hear from us about once a month.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
THere's More

Post You Might Also Like

All Posts
Change Management

Change Management: Preparing for Change

1 of 3 in our series on preparing your organization for new data analytics capabilities. This post talks about ways to build in adoption from the beginning.
Change Management

Change Management: Managing Change

This is the second post in our series on increasing analytics adoption through change management. This post discusses how to manage change during project implementation.
Change Management

Change Management: Reinforcing Change

This is the third post in our three-part series on increasing user adoption through change management. This post discusses how to maintain new behaviors after project implementation.

5 Factors to Move Your Data and Analytics From Laggard to Leader

The past few years have seen a rapid rise in data analytics throughout industries. Business opportunities and technological innovations continue to raise the bar on the subject, allowing even smaller businesses with limited resources to get into the BI game.

Top 12 Dashboarding and Data Visualization Features of BI Tools

Here are the top dashboarding and data visualization features of BI Tools to consider as part of your evaluation.