Treatwell Automates Financial Processes With Fivetran

Beauty booking marketplace replaces custom ETL, enabling the data platform team to focus on data modelling and automating processes for internal stakeholders.

Key Takeaway

  • Treatwell replaces time-consuming, in-house ETL solution with Fivetran
  • Data platform team focuses on data modelling and enabling the business to use data rather than data pipeline maintenance
  • The business automates many month-end processes, saving the finance team an estimated three working days each month

Data Stack

Treatwell is Europe’s largest hair and beauty booking marketplace. The company has over 500 employees, with a data platform team of five people that includes a data product manager, data engineers and a business intelligence analyst. The team serves users directly and through embedded analysts within the direct business units.

Challenge: Build vs. Buy

As the business grew, adopted new applications and gathered new datasets, scalability became a concern. Maintaining an in-house ETL solution to access the APIs, extract the data and load it into Redshift was difficult and time-consuming, especially from Salesforce. While it generally worked, Data Product Manager Jeff Sloan, recognized it wasn’t the best use of resources:

We hit a point where our mission to help business users get value from the data came second to our efforts to simply access the data. Instead of data modeling and education, our time was spent maintaining existing integrations and adding new ones to Redshift, As our business scaled we needed an effective way to access the data to solve problems and drive value.

It didn’t take Sloan long to convince the business that buying a data integration solution was the obvious choice over continuing to build internally:

The economics make sense: Fivetran is more affordable than hiring additional engineers solely dedicated to building and maintaining pipelines. Our aim is to help enable better and faster decisions through data – not build pipelines. With that as our guiding principle, Fivetran was the clear choice.

Improving Data Modeling, Data Accuracy and Engineering Practices

With Fivetran managing the data integration, the data platform team can focus on improving the business model and accurately using the data. Analysts are able to configure Looker using LookML in ways that allow business users to intuitively access the correct data. “About 50% of the business is active in Looker,” says Sloan. “People are inspired to build their own reports and they understand what they’re looking at.”

The team is also able to implement best engineering practices across the technology stack and code base. “There was a large opportunity cost associated with building our own pipelines,” Sloan admits. “Now we can look more deeply into how we’re processing data, investigate opportunities in streaming technologies, and more. We have a whole list of items we now have the resources to tackle."

Automating Month-End Financial Processes

Treatwell has been working on automating many of its month-end processes for the finance team. Previously, the data-heavy process required a lot of manual work in spreadsheets. With Fivetran and Looker, the process is much smoother, and saves the Finance team three days of reconciliation and investigation each month. As Sloan explains:

We use Fivetran to integrate our Stripe data, reconcile that with different systems within our data warehouse, and provide access to that information to our finance team. Because there are so many ways that the finance team needs to inspect, pivot and group data to post its month-end journals, being able to visualize this data at a granular level in Looker is really important. Rather than having to chase down numbers, the finance team can conduct more value-adding analyses and answer questions like: where should we allocate our money?

To learn more about the impact of Fivetran, check out our resource center, sign up for a personalized demo or start your free trial today.

About Fivetran: Shaped by the real-world needs of data analysts, Fivetran technology is the smartest, fastest way to replicate your applications, databases, events and files into a high-performance cloud warehouse. Fivetran connectors deploy in minutes, require zero maintenance, and automatically adjust to source changes — so your data team can stop worrying about engineering and focus on driving insights.

About Amazon Redshift: Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse solution that makes it simple and cost-effective to efficiently analyze all of your data using your existing business intelligence tools.

About Looker: Looker is the business intelligence (BI) and analytics platform part of the Google Cloud data and analytics suite. Transcending traditional BI, Looker powers data experiences that deliver actionable business insights at the point of decision and infuses data into products and workflows to allow organizations to extract value from data at web-scale.

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Treatwell automates financial processes with Fivetran

Company size
500-1999
Region
Europe and Middle East
Industry
Healthcare & wellness
Key results
  • Treatwell replaces time-consuming, in-house ETL solution with Fivetran
  • Data platform team focuses on data modelling and enabling the business to use data rather than data pipeline maintenance
  • The business automates many month-end processes, saving the finance team an estimated three working days each month

Treatwell is Europe’s largest hair and beauty booking marketplace. The company has over 500 employees, with a data platform team of five people that includes a data product manager, data engineers and a business intelligence analyst. The team serves users directly and through embedded analysts within the direct business units.

Challenge: Build vs. Buy

As the business grew, adopted new applications and gathered new datasets, scalability became a concern. Maintaining an in-house ETL solution to access the APIs, extract the data and load it into Redshift was difficult and time-consuming, especially from Salesforce. While it generally worked, Data Product Manager Jeff Sloan, recognized it wasn’t the best use of resources:

We hit a point where our mission to help business users get value from the data came second to our efforts to simply access the data. Instead of data modeling and education, our time was spent maintaining existing integrations and adding new ones to Redshift, As our business scaled we needed an effective way to access the data to solve problems and drive value.

It didn’t take Sloan long to convince the business that buying a data integration solution was the obvious choice over continuing to build internally:

The economics make sense: Fivetran is more affordable than hiring additional engineers solely dedicated to building and maintaining pipelines. Our aim is to help enable better and faster decisions through data – not build pipelines. With that as our guiding principle, Fivetran was the clear choice.

Improving Data Modeling, Data Accuracy and Engineering Practices

With Fivetran managing the data integration, the data platform team can focus on improving the business model and accurately using the data. Analysts are able to configure Looker using LookML in ways that allow business users to intuitively access the correct data. “About 50% of the business is active in Looker,” says Sloan. “People are inspired to build their own reports and they understand what they’re looking at.”

The team is also able to implement best engineering practices across the technology stack and code base. “There was a large opportunity cost associated with building our own pipelines,” Sloan admits. “Now we can look more deeply into how we’re processing data, investigate opportunities in streaming technologies, and more. We have a whole list of items we now have the resources to tackle."

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Automating Month-End Financial Processes

Treatwell has been working on automating many of its month-end processes for the finance team. Previously, the data-heavy process required a lot of manual work in spreadsheets. With Fivetran and Looker, the process is much smoother, and saves the Finance team three days of reconciliation and investigation each month. As Sloan explains:

We use Fivetran to integrate our Stripe data, reconcile that with different systems within our data warehouse, and provide access to that information to our finance team. Because there are so many ways that the finance team needs to inspect, pivot and group data to post its month-end journals, being able to visualize this data at a granular level in Looker is really important. Rather than having to chase down numbers, the finance team can conduct more value-adding analyses and answer questions like: where should we allocate our money?

To learn more about the impact of Fivetran, check out our resource center, sign up for a personalized demo or start your free trial today.

About Fivetran: Shaped by the real-world needs of data analysts, Fivetran technology is the smartest, fastest way to replicate your applications, databases, events and files into a high-performance cloud warehouse. Fivetran connectors deploy in minutes, require zero maintenance, and automatically adjust to source changes — so your data team can stop worrying about engineering and focus on driving insights.

About Amazon Redshift: Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse solution that makes it simple and cost-effective to efficiently analyze all of your data using your existing business intelligence tools.

About Looker: Looker is the business intelligence (BI) and analytics platform part of the Google Cloud data and analytics suite. Transcending traditional BI, Looker powers data experiences that deliver actionable business insights at the point of decision and infuses data into products and workflows to allow organizations to extract value from data at web-scale.

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