Mac & Mia
Not writing ETL scripts saves Mac & Mia weeks of time
"We were suffering from the usual 'we have data in many different places and need a way to consolidate it so we can have better reporting' story," says Alex Mohr, data analyst at Mac & Mia. The online retailer offers a curated collection of boutique children's clothing.
"When I joined the company, we had data scattered across a web app database (run on Heroku) and various advertising, sales, and customer service platforms, with all reporting coming from the platforms themselves, CSV exports, or Heroku Dataclips, which were loaded into Excel or PowerPoint and then distributed to the team. As you might imagine, weekly or sometimes daily repetition of this process was not fun – in fact it was a massive waste of our limited time. We needed a way to automate the reporting and visualization of our data.
"I was given charge of setting up our data analytics stack, and I had close to zero experience with anything analytics-related beyond Excel. The sheer amount of new knowledge that I had to acquire was overwhelming, and I knew that after I learned where to start, the implementation work was likely to be even more challenging.
"After a brief research period (and a very misguided attempt at building my own Shiny dashboard web app), we settled on Looker as our reporting tool. It was amazing, but the almost immediate next question was: How could we get Looker to show us more data than what was in the Mac & Mia app? Our devs said they could ETL all of our data sources themselves. We decided they could find better uses for their time.
"Our Looker rep recommended we check out Stitch. We also looked at three other cloud-native ETL platforms. Since on the surface many of the ETL tools we looked at seemed to be similar in functionality, we kept our review simple and looked at three points for each tool:
"Stitch supported all the tools we were already using, and for our volume of data, Stitch easily won on price. On top of that, one of the biggest draws for me was how accessible it was to create a free account. With literally a few button clicks, we could have millions of rows loaded into our data warehouse. There was no 'demo' to sit through, no sales call to get access set up. It was almost suspiciously easy at first; I thought I must have missed some critical step. Within a few minutes all of our app data was in our analytics warehouse, and after a couple more clicks, data from our third-party tools followed. I spent maybe 30 minutes setting it all up. Most of that time was spent deciding what tables to sync into the warehouse.
Stitch was almost suspiciously easy at first; I thought I must have missed some critical step. Within a few minutes all of our app data was in our analytics warehouse, and after a couple more clicks, data from our third-party tools followed.
"By using Stitch, we saved 80+ hours of developer time that we would’ve spent writing up scripts to ETL from the various sources, and likely another 10 hours a month ongoing to investigate various errors that would inevitably pop up.
"I also appreciate the wealth of documentation Stitch provides to help me understand how to analyze all these new schemas once they're loaded, and an incredibly helpful support team.
"Having the resources available that Stitch provides has been invaluable to me to help me understand what data I’m looking at, so I can spend less time worrying about how to get the data I need and more time worrying about what to do with it."
Now I can spend less time worrying about how to get the data I need and more time worrying about what to do with it.