Business Intelligence Tools: A Pros and Cons Comparison Chart

Selecting a business intelligence tool for your organization is a daunting task. You know your company needs better analytics for decision-making, but you don’t want to choose a tool that will cause more problems than solutions.

Furthermore, your organization has realized the need to move away from the archaic model of calling IT for reporting needs. The paradigm shift to self-service BI is tantalizing.

The 2020 Gartner Magic Quadrant provides a detailed matrix with narratives on the feature sets of all major tools in the industry. Today we’ll focus on the top five BI platforms that are worth considering:

  • Microsoft’s Power BI
  • Tableau
  • Qlik Sense
  • ThoughtSpot
  • Looker

Platforms outside this group have not been able to keep up with the change of pace in the market and/or are not extensible enough to provide the nimbleness your organization needs. If you are using one of “those” (I’m looking at you Birst, Domo, SAP Business Objects, Microstrategy, etc.), I suggest re-evaluating. Why? Because the technical debt is not worth it.

You need business intelligence tools that allow you to be agile and successful. Let’s explore the importance of business intelligence tools and figure out which one will work best for you.

What Are Business Intelligence Tools?

Business intelligence (BI) is the combination of software and services that turn raw data from internal and external systems into actionable insights. These insights inform an organization’s strategic and day-to-day business decisions.

Business intelligence tools are software platforms used to investigate data sets and communicate insights through charts, graphs, maps, reports, and dashboards. These tools provide users with an understanding of the state of the business.

Self-service BI is the ability for non-technical users to ask questions via BI tools and trust that the data they are analyzing is correct…without the need for involvement from IT.

Business Intelligence Software in the Real World

In the real world…you buy business intelligence software that IT approves and the business thinks looks cool as a way to bridge the gap of communication that we run into when trying to figure out the current state of the business.

Data should be a universal language, but every department at your organization wants to look at a certain business process in their own way and with their own words. So, how in the hell can we do that? With BI tools.

Specifically, your data model is the common language that IT and business departments land on. Self-service BI means the marriage between IT and the rest of the business is going so well that the business intelligence software you have invested in allows you to actually understand each other.

Let me try and make this even simpler. “You,” in this case, is your organization:

  1. You have data coming from your CRM, ERP, HR, (basically out of every orifice and we have given it an acronym), and finance systems that don’t talk to each other. BOO!
  2. You buy a shiny BI tool that promises you the world. Yay!
  3. You realize the shiny BI tool comes with a set of vague instructions your IT-folk need to build and your business people need to know how to read. Oh sh*t!
  4. You stick IT and business people together in a room (hopefully with the help of consultants). Utter pandemonium happens. They build something called a data model with accompanying data visualizations. Nice!
  5. Business people use the BI tool to ask questions like the who, what, where, and when to figure out the why. Sometimes their friends called AI (Artificial Intelligence, not Al) help. Sweet!

You make smart decisions…and hopefully more money. Voila!

Pros and Cons of Popular Business Intelligence Tools

Down below we pulled together a business intelligence tools comparison chart that shows the capabilities of each BI tool. Before you take a look at the pros and cons of these five BI tools, here are some details on the features and benefits we compared.

Full-featured Free Version

Don’t give me trial periods or test-drive gimmicks. Just let me download the damn thing and get going.

Development Environment

Only your IT or BI analyst will care. Is this an application I download onto my Desktop? Or is it an application I access through my web browser (cloud) to build data visualizations? Do I really need an expensive implementation just to get started?

R and Python Supported

Can I use the languages I know like R or Python to work with this BI tool?

Dynamic Cross-Filtering

If I click something on this report, will everything else dynamically filter to tell me what I need to know about it without predetermined filters?

AI-Enabled Analytics

Does this tool have out-of-the-box ways to get the help of AI for building an insightful data visualization?

Search Analytics with NLP (Natural Language Processing)

If I type my business question into a search bar, will it return what I want?

Data Prep Tools

Can I connect to different data sources, transform data, and clean it?

Data Modeling Tools

Can I model my data by introducing relationships between tables or appending tables?

Preferred Data Model

What philosophy of BI is this tool designed to run best with? Flat means you have built a single table (view) of your data with every column of data you need imaginable. Star-schema means you have sorted your data into different tables based on dimensions like who, what, where, and when. Snowflake is similar to Star-schema, but means your dimensions have tables that branch off from each other as well.

Database Independent

Do you need a SQL-based database for your data to live in order for the BI tool to do its job best?

Built in Row Level Security

Can I create security roles directly in the BI tool so different job functions can view the same report but only see the data relevant to them?

Mixed Model Types

Do I connect to a data source either as a direct connection or import? What if I want to have real-time data for certain tables versus lower latency tables in the same report? Think of how expensive those cloud database costs could be…

Third-party Data Model Access

Can the BI tool allow for my data models to be extended like a data warehouse via third-party tools or languages, allowing for a single source of truth data model?

Commenting & Collaboration

Can I take notes directly in the BI tool’s reports and make decisions on the fly?

Embedded Analytics

Wow this tool is sweet I want to embed it into my website, product, service offering, etc. so people outside my organization can do what I’m doing. With embedded analytics, I can even take this a step further and build my own white-labeled portal and monetize my data.

Open-source Custom Visualizations

What if the visualization choices that come out-of-the-box aren’t enough in this BI tool? Can I pick from an open source library or build my own custom visualizations?

Native Mobile App

Whether I am “Team iOS” or “Team Android,” can I download an app and get to my reports?

 

(tap or click to expand chart)

 

Power BI

Pros

  • Power BI can do everything. I don’t need to buy and learn different tools to get the self-service BI job done.
  • Data modeling is the core language both IT and business teams need to come to terms with. Power BI can be the bridge.
  • You don’t need a data engineer that knows SQL to mash up and clean data from your different systems, click through actions on a ribbon to make the magic happen.
  • Power BI’s AI visualizations and capabilities are robust, empowering business analysts and data scientists to work collaboratively across the organization.

Cons

  • This thing can do everything! Thus, it is complicated with many layers.
  • To make the most of Power BI’s advanced features you must learn their calculation language called DAX.
  • Your organization needs to have good data modeling expertise to make the most of this tool.
  • The more investment you have in Microsoft infrastructure, the easier it is to deploy.

Tableau

Pros

  • My god…the data visualizations are beautiful! Your creative design team would approve.
  • Because Tableau relies on flat models, it is less complicated to pick up and use for someone new to BI.
  • The AI-driven insights and statistical engine you get out-of-the-box are powerful.

Cons

  • Without a strong IT team of SQL developers and a fast database to run off, this thing is dead in the water.
  • Relies on using separate tools and services to get the job done.
  • I hope you have a big budget…cuz this puppy ain’t cheap.
  • Salesforce recently bought this tool, unknown what happens next.

Qlik Sense

Pros

  • The data processing engine is blazing fast and can handle more data from multiple data sources.
  • Ability to make relationships with different data sources on the fly.
  • Powerful data discovery capabilities with the unique ability to show missing or incorrect data on dimensions.
  • Working within a browser eliminates the need for installing a desktop tool.

Cons

  • It is easy to create data visualizations that are confusing to end-users.
  • Configuration is needed to extend the platform such as its integration for R and Python.
  • The free tool is soon to go away and does not have a community showcase, you cannot publish public reports.
  • No data prep tool is necessary but is often useful because this is not Qlik’s strong suit.

ThoughtSpot

Pros

  • The simplicity of using a search bar to get the answers for your data questions is a lovely concept.
  • No complicated report designer tools to mess with, just implementation.
  • The ease of collaboration takes the headache away from reconciling reports and communicating your data insights.
  • AI analysis is built into each visualization with simple feedback to improve results.

Cons

  • I hope you’re prepared for the time and technical investment it will take in order to reach the nirvana of business users finding their own insights.
  • What if you need to answer business questions on systems not currently implemented? You will have to figure it out on your own.
  • Thoughtspot is a newer tool, talent can be hard to find.

Looker

Pros

  • You mean I don’t need to buy an expensive computer to do all my BI work? Yes, since Looker runs on the cloud, you can access your reports and make changes wherever you are (internet sold separately).
  • The analysts in my org already know SQL, so they can pick up this SQL-based tool much easier.
  • If you are heavily invested in all cloud infrastructure, this makes a lot of sense.

Cons

  • The data visualizations are “meh” and you need to make a lot of clicks/filters happen.
  • I hope you love writing SQL and extensive code.
  • Not a lot of features included that you would expect from a BI tool.
  • Google recently bought this tool, it is unknown what is next.

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So, which is the best business intelligence tool in my opinion? It all depends! Make an informed decision based on your organization’s culture, strategic vision, and what you have invested in already. All the tools here deserve their fair shake.

We are Microsoft-centric and promote the use of Microsoft’s full technology stack (Power Platform, Azure, Snowflake, etc.), thus Power BI is the clear winner. There are reasons to go with or stick with other tools, but for us the best bang for your buck is Power BI. Just ask Gartner.

If you made the same decision and you are ready to embark on a self-service journey with Power BI, let’s ignite data victories together.

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Gregory Petrossian
Gregory Petrossian
gregp@csgpro.com

Gregory Petrossian is a Business Transformation Consultant who became a champion of data analytics after five years of consulting in the healthcare industry. Having mastered skills in business intelligence, embedded analytics, cost-efficient data warehouse implementations, and custom-tailored software solutions, Greg uses his diverse expertise to help business leaders achieve data-driven goals.



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