This page provides you with instructions on how to extract data from Magento and analyze it in Metabase. (If the mechanics of extracting data from Magento seem too complex or difficult to maintain, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)
What is Magento?
Magento is an open source content management system for ecommerce web sites. It's known for its flexibility and wide adoption across ecommerce businesses of all sizes.
What is Metabase?
Metabase provides a visual query builder that lets users generate simple charts and dashboards, and supports SQL for gathering data for more complex business intelligence visualizations. It runs as a JAR file, and its developers make it available in a Docker container and on Heroku and AWS. Metabase is free of cost and open source, licensed under the AGPL.
Getting data out of Magento
You can use the Magento API to extract information. In most recent version, Magento offers both REST and SOAP versions of its API. Be warned, however, that historical versions of different Magento API calls could display inconsistent compatibility.
You can also pull data directly from the underlying database. (Using the API is really just doing this via a layer of abstraction.) If you go this route, familiarize yourself with the Magento database structure.
Preparing Magento data
Your Magento data needs to be structured into a schema for your destination database. If you choose to work with the default Magento database structure in your analytical environment, this simply means recreating the tables and fields that you pulled from your Magento API. You can refer to the API docs or use the information_schema tables in those databases to get the information you need.
Loading data into Metabase
Metabase works with data in databases; you can't use it as a front end for a SaaS application without replicating the data to a data warehouse first. Out of the box Metabase supports 15 database sources, and you can download 10 additional third-party database drivers, or write your own. Once you specify the source, you must specify a host name and port, database name, and username and password to get access to the data.
Using data in Metabase
Metabase supports three kinds of queries: simple, custom, and SQL. Users create simple queries entirely through a visual drag-and-drop interface. Custom queries use a notebook-style editor that lets users select, filter, summarize, and otherwise customize the presentation of the data. The SQL editor lets users type or paste in SQL queries.
Keeping Magento data up to date
At this point you've coded up a script or written a program to get the data you want and successfully moved it into your data warehouse. But how will you load new or updated data? It's not a good idea to replicate all of your data each time you have updated records. That process would be painfully slow and resource-intensive.
Instead, identify key fields that your script can use to bookmark its progression through the data and use to pick up where it left off as it looks for updated data. Auto-incrementing fields such as updated_at or created_at work best for this. When you've built in this functionality, you can set up your script as a cron job or continuous loop to get new data as it appears in Magento.
And remember, as with any code, once you write it, you have to maintain it. If Magento modifies its API, or the API sends a field with a datatype your code doesn't recognize, you may have to modify the script. If your users want slightly different information, you definitely will have to.
From Magento to your data warehouse: An easier solution
As mentioned earlier, the best practice for analyzing Magento data in Metabase is to store that data inside a data warehousing platform alongside data from your other databases and third-party sources. You can find instructions for doing these extractions for leading warehouses on our sister sites Magento to Redshift, Magento to BigQuery, Magento to Azure Synapse Analytics, Magento to PostgreSQL, Magento to Panoply, and Magento to Snowflake.
Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to move data automatically, making it easy to integrate Magento with Metabase. With just a few clicks, Stitch starts extracting your Magento data, structuring it in a way that's optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Metabase.