Welcome to the first edition of our new blog series: “Hazards on the Road to Self-Service Analytics.” A couple weeks back, I introduced this series and requested our readers’ input to inform the topics we’d address. Well, we heard from you and we’re back with our first post about a common cited self-service analytics hazard – data preparation.

For this, we turned to Alfonso Vaca-Lubischer, an analytics consultant with a background in the education sector, which serves as the backbone for our discussion today. We decided to conduct this as an interview, which we formatted below with the bold text representing the questions and the plain text containing Alfonso’s answers.

The Interview

Tell us about yourself and your experience solving data challenges within the Education sector.

Prior to joining InterWorks, I spent several years collaborating with Chicago Public Schools, helping them build public facing dashboards about school quality, enrollment and program availability. The dashboards had a wide audience within the community and with local policy makers, so we needed intuitive and user friendly design and functionality. The work wasn’t easy, but I’m happy to say it was successful and CPS continues to do great work with Tableau today.

What was a commonly encountered data preparation “hazard” you faced during this work?

A big part of the challenge I faced was something that I think a lot data folks face in the education space: much of the source data lived in unstructured Excel files and needed extensive cleaning before going into Tableau. The result was that I became pretty savvy in Tableau (and now I work at InterWorks!) and significantly improved my Excel skills. Unfortunately, I also spent a lot of time cleaning data. In retrospect, a data preparation tool such as Alteryx or Tableau Prep could have saved me a ton of time and kept me from having to repeat the same data cleaning tasks with each new school year.

What’s a quick story and/or some helpful hints about how an organization can address this “hazard?”

After a couple of years of wrangling data in Excel, I decided to write some code to automate parts of the process. This was helpful and allowed me to spend time running data quality checks and improving my dashboards. However, custom code isn’t easy to maintain. In a perfect world, CPS would have a fully mature data architecture with ETL processes and warehouse to fuel their dashboards. Unfortunately, that just isn’t economically feasible for school districts serving hundreds of thousands of kids and operating on thin budgets.

Looking back, Tableau Prep would have been a great solution for some of these challenges. It can handle many of the common data cleaning tasks, comes with your existing Tableau subscription, and automatically documents all the changes you make to the data. Alteryx is another great option for data preparation and has the added bonus of being an incredibly powerful program that can scale with your organization as your data maturity grows.

Wrapping Up

We hope that this post was helpful in giving you a glimpse into a data “hazard” faced by an organization in the education sector. If you want to request another look at some hazards faced in different sectors, you can fill out this anonymous survey here so we can tailor this series to you!