Free and open source apps for the data loving product manager

Analysing data doesn't have to be expensive - check out these free and open source analysis tools to get you started.


5 minute read

data analysis for product managers

Being a data driven product manager doesn’t mean you need your company to invest a lot up front. You can get started with little to no outlay, other than the time for you to setup and learn these tools (which, is really an investment in your personal development).

This is list is a starting point for free or open source apps, services and resources to get you started. I’ve focused on tools that help you collect, store and analyse usage data.


A database is useful for storing usage data and consolidating all your available metrics into a single place. There are quite simply loads of databases which are either open source or free. Many commercial databases also have free versions, but I’ve focused on the leading open source databases below. When choosing a database, it’s always worth considering what platform your product is using - if you work in a company with developers who know a particular database, then working with that will probably give you an easier time, and help and pointers from your team if needed.


MySQL says it is “The worlds most popular open source database”. It is not too hard to install and setup and there is plenty of support, examples and tutorials to follow online. The MySQL Workbench app is a good interface for querying and maintaining your database and makes importing data pretty easy too.


PostgreSQL describes itself as “The world’s most advanced open source database”. PostgreSQL is a powerful, open source object-relational database system with over 30 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance. Generally it is pretty comparable to MySQL, although it has a few advanced features which you might find interesting.


SQLite is a simpler option for quickly setting up a local database - which is probably fine for your own personal analysis. You see, SQLite is a file based database, rather than the more complex client/server databases like MySQL and PostgreSQL. This means it can be much easier to get started. Check out DB Browser for SQLite for a simple GUI which makes importing from CSV etc. quick and painless.

Website / app analytics

If you need help collecting usage data, then these are the tools to check out.

Google Analytics

Google Analytics is the free analytics tool from Google. It is a great way to get started in learning about how you users use your service, with flow visualisations and more metrics and stats than you could even need. If your product is a mobile app, then check out Google Analytics for Firebase for a similar service from Google aimed at apps on Android or iOS.


Matomo is similar to Google Analytics, but it can be self hosted which might be important to you based on your data security policies. It works in a similar way - a small bit of JavaScript which is put into your site. You can then log into the dashboard and explore usage trends and info about your users and their devices.

Data analysis

Great, now we’ve got some data in a database, how are we going to do any analysis? I’ve listed two great programming languages that are bursting with modules to help you analyse your data, and options for more traditional spreadsheet analysis.


Python - Python is a scripting language with lots of tools and support for data analysis. Either install from the main site, or go for an all in distribution like Anaconda which will have all the modules you’ll (probably) ever need. I’ll try and write up more about getting this all set up - but for now, look into pandas and jupyter notebooks for examples of how this will make your life more awesome.


The R Project for Statistical Computing is another programming language, more specifically aimed at stats and data analysis, so worth checking out. Python is a more general purpose language which can be good or bad, depending on your aims and past experiences. I found Python easier to learn, but R definately has its place. Check out RStudio for a powerful IDE to get started.

LibreOffice Calc

LibreOffice Calc is the Exlce equivilent of the open source LibreOffice suite. For simple spreadsheet analysis, it is pretty much on par with Excel, although Excel certainly has more advanced features and tools which can be useful (e.g. PowerBi) if you’ve got access to them. Still, LibreOffice will almost certainly help you load up your data and start looking for trends and plotting simple charts.

Google sheets

Google Sheets is the Excel equivilant for Google’s office suite. A bit like LibreOffice, it does the basics well and if you don’t have Excel it can be a good first step.

Data visualisation and reporting

So now you’ve done some analysis, you’ll want to share it with your team. Both Python and R have built in charting and visualisation options which you can explore. But here are a few more things to check out.


Metabase sits on top of your databases and makes asking questions about your data easy. It’s a great option for creating a product dashboard. Once connected to your database, you can use the built in query builder or SQL to analyse your data, and then select from loads of built in visualisations to make the data more meaningful.


Redash is similar to Metabase and worth checking out for some different visualisation options.


QGIS - if you need to do any geographical analysis or visualisation, QGIS can help with options for colouring maps based on data you have

Missing anything?

Hopefully there is something new or interesting to you in the list above. Do you know of any other cool free/open source data tools? If so, let me know in the comments and I’ll keep the list updated!

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