Wonderschool Overview

Wonderschool is on a mission to ensure that every child has access to childcare and early childhood education. Its childcare marketplace provides a one-stop shop where childcare providers and families seeking childcare can connect. The company also offers software and services for childcare providers including administration and family communication, billing, and website development, plus a community for networking and professional development. The Wonderschool Government Platform offers tools, data, and insights to help states make strategic decisions about resource and funding allocation.

Helping Childcare Succeed with Data

Wonderschool wants every family to have access to childcare, and acts as a marketplace to connect families with quality childcare providers. But another part of the company’s mission is to ensure that providers and their regulating state governments have the information they need to help them succeed. Providers have access to a variety of tools, and analytics from those tools give insight into business performance and adherence to standards. Wonderschool also provides analytics-as-a-service to providers and individual states to help them assess the state of the childcare market. And of course, Wonderschool uses data to measure its own performance and to help drive growth.

All of that is a tall order for a data team of two people. 

A New Team Struggling with Data Agility

The data team at Wonderschool needed to be as agile as possible to adapt to shifts in business and changing definitions. But a few things were hampering their ability to move quickly. 

  1. After Wonderschool acquired a company whose product became their next-generation childcare management app, the team needed to model data in the new product, aggregate all of their data, and stitch their new and existing products together.
  2. While the team did have some repeatable analytics processes, they lacked a truly modular way to make changes and update products. 

“When we have to change something, we have to change it in a bunch of different places,” said Martin Bourqui, Data Analyst at Wonderschool. “It was the equivalent of handing out 5000 pieces of paper, then needing to find all of those pieces of paper to change a definition on each one of them. It’s easier to make a change once that shows up everywhere.”

The team struggled with lag times, a lack of data integration, and an overall lack of visibility into the state of the business. 

Adopting Analytics Engineering

The data team at Wonderschool wanted to set up a data architecture that included modular and repeatable analytic concepts and the ability to make a change once and have it filter down through the business, rather than having to make the same change many times. Partnering with Data Clymer, they began to set up a standardized, consistent analytics engineering practice. Using dbt, the team was able to centralize data from several different sources and model it effectively. Data Clymer provided the extra resources Wonderschool needed to build out introductory models and efficient processes to leverage data they never had the time and resources to tap into before. 

But beyond the nuts and bolts of architecting a new modern data stack for Wonderschool and implementing dbt best practices, Data Clymer played an important role in helping Wonderschool think about data and analytics differently. Data Clymer helped drive additional conversations on division of labor, the hiring process, and the roles of data analytics, data modeling, and analytics engineering. 

“They didn’t just build the table,” Bourqui said. “They taught me how to think about building the table, and every other table. Data Clymer helped us create a whole framework of how to think about the modern data stack.”

Delivering Consistent Analytics Value for Less Money

Wonderschool now has a modern data stack in place, as well as an established set of requirements to architect a scalable system and track data as it changes. “We’re now able to track changes and use version control to see how data is changing,” Bourqui said. “Before, we would pull a report based on old data and definitions. Being able to centralize and document data is really important.”

The team has also been able to move from a very ad-hoc, one-off paradigm for data and analytics to delivering regular insight to the business. A modular, repeatable analytics engineering process helps the team be more productive and work more cost-effectively. 

Now that data is merged together and the team understands the best practices of modern data and analytics, it hopes to continue to get all of Wonderschool’s data into its centralized data warehouse and scale the solution to deliver even more value to the business. “Things used to be very opaque, but we’re now in much better shape,” Bourqui said. “It’s easier to understand what we’re doing. And it’s easier to know how to build solutions for the future.”

The Results

  • Integrated picture of the business with data from multiple products merged into a centralized data warehouse
  • Improved data quality and productivity with a modular, repeatable analytics engineering practice
  • Established a more regular reporting cadence for consistent delivery of insight across the business
  • Built the foundation for a scalable team and modern data stack that meets business and technical requirements and adheres to best practices

Wonderschool is another example of a successful ongoing Data Clymer relationship. Check out the many other case studies and companies we work with on the Data Clymer website. 

Find out about how a partnership with Data Clymer can help you modernize your data architecture and eliminate data silos.  Give us a shout – we’d love to hear from you!