Data Stack Considerations: Build vs Buy at Tout





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Uploaded on Jul 25, 2016

Growing from an in-house data analytics solution to an outsourced model with Looker and Treasure Data

Build vs buy - It’s a common dilemma in a world of seemingly endless engineering talent and an abundance of SaaS products. Many companies start by building but quickly realize that maintenance costs and engineering hours can quickly cause budgets and project-time lines to spiral out of control.

Tout, a video app platform that allows users to upload content directly to their sites, found themselves facing this exact dilemma after building their own analytics infrastructure and using it in conjunction with a BI tool. After three years of heavy growth and feature expansion, their analytics stack could no longer keep up with the demands and costs were through the roof.

Tout decided it was time to invest in a new solution and turned to Treasure Data for their analytical infrastructure and Looker for Analytics and is now reaping the rewards.

What will you learn?
-The pitfalls of building (and maintaining) in-house solutions
-How Treasure Data simplifies data pipelines for effective data lifecycle management
-How Looker let Tout give every employee access to the data they needed when they needed it
-Actionable criteria for deciding when to buy vs. build analytics infrastructure


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