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This post aims to help business people or technical leaders with no business intelligence (BI) expertise understand when to start thinking about BI and how much it may cost. Here, we will compare a variety of BI tools: Google Data Studio, Power BI, Tableau, Pentaho, and others.
There are tons of products already out there, and something new pops up every day, so understanding which one is right for your business might be tricky.
To help you get a better picture, we first need to answer some basic questions and go through a little historical retrospective. If you want, you can skip this intro and fast-forward directly to the section of the article where the available solutions are listed. So, here we go.
Business intelligence systems help decision-makers analyze data and stay on top of their business decisions.But when should you start thinking about BI?
Well, it’s when you need to get useful insights from your data. When you want to stay on top of what happens in your business and understand the trends. When you need quick turnaround on your decisions, which is essential in a fast-changing world. The better insights you have, the better decisions you can make. Getting insights takes having the right tools and solutions that will help you understand the data better.
From a technical perspective, the many BI components always evolved in parallel with data storage and processing systems, among the most important of which is RDBM (relational database management system). As the data volumes grew, the need for more sophisticated (and, consequently, more expensive) data transformation solutions arose. That’s why historically BI has never been cheap.
New technologies such as cloud computing as well as modern processing and data storage systems have changed things in BI.
Modern business intelligence systems cover a broad range of on-premise and cloud-based architectures, whether with or without ETL. Take a look at the stage stack for comparison:
As you can see, modern approaches have virtually no borders or split components. You can connect your business data to a BI dashboard directly and get some insights. It simplifies things a lot, but there are still some important factors to consider.
To pick the right BI tool, you basically need to ask the right questions, such as the following:
There are plenty of formal comparisons of BI tools. However, we at Broscorp decided to make our own shortlist based on the best practices established in our company.
We always start by checking if Google Data Studio might suit our problem. It’s free, it looks nice, and it has options for custom visualization development.
It’s free, so it’s always the first thing we suggest trying.
The solution that addresses most of the shortcomings of Google Data Studio is Power BI, so let’s look at it next.
It is the most comprehensive and feature-rich BI solution available on the market. It offers one of the best analytic engines out there, as well as built-in ETL. Suitable for self-service BI, it supports advanced use scenarios, e.g., row-level security and scheduled data refresh.
$10 per user monthly or ~$5,000 for a basic cloud instance of Power BI.
Looker offers pretty much the same feature set — check it out if you don’t need Azure — and Tableau is another strong competitor.
One of the oldest market players out there, Tableau offers a good set of features — enough for most use cases.
Tableau has mostly the same strengths and drawbacks as Power BI. Choosing between the two, we take into account the following:
One of the traditional BI tools, it has a rich toolset. It is open-source and extensible and has a free Community Edition. Compared to the other tools listed above, the development takes longer. Still, this one could be an excellent option for supporters of free software wanting to have full control over the infrastructure and code.
Community Edition is free. However, since there is no cloud offering, the basic infrastructure costs are comparable to a BI server installation, e.g., renting an EC2 instance 24/7 with minimal requirements will cost you $750 per month, or $370 per month with an upfront 1-year payment.
Another open-source beast is Apache Superset. A more recent solution than Pentaho, it is potentially more promising in the long term. But we will look at it in greater detail in our next post. Stay tuned 🙂
To sum-up of the post, check out the feature matrix we use at Broscorp while picking a BI tool for a project. This list is by no means full, and we might extend it in the future, but the bottom line is that tool selection is a crucial choice we always make first.
 — There are some big names in this field like IBM Cognos, Microstrategy and QlikView, that are worth mentioning. We will try to add in-depth analysis of their features later
 — Pentaho has a separate component called PDI (Pentaho Data Integration) responsible for ETL.
 — Here I refer to PowerBI premium feature with dedicated instances deployed on customer’s Azure instances.
 — I didn’t include hosting costs here because it depends very much on existing infrastructure.
 — Some features supported out of the box, some of them require additional development effort