How Wayfair Reduces Time from Data Collection to Data-Driven Business Decisions Using a Semantic Layer


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The ability to access and analyze data in real-time can provide a competitive advantage and help companies respond to changes in the market and capitalize on opportunities when they arise. But how do you build a self-service data and analytics environment that enables this?

Common obstacles include:

  • a lack of consistent business definitions and metrics
  • stale data culled from extracts
  • reliance on an overtaxed data engineering team. Legacy analytics stacks are loaded with these bottlenecks.
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What you’ll learn

In this webinar, Matt Hartwig, Wayfair’s Associate Director of Product Management for Data Infrastructure, shares how his team modernized their data and analytics stack for the cloud, transitioned away from old, slow systems, and optimized their analytics strategy through a lightning-speed data pipeline, at scale.

Matt discusses how Wayfair has leveraged a semantic layer to help them:

  • Transition from their legacy dimensional modeling service to an agile framework with a live connection
  • Analyze near real-time data for more accurate key performance indicators (KPIs)
  • Trust that KPIs are being reported consistently across BI tools through a self-serve data service
  • Scale analysis for revenue-driving insights, including period-to-period sales and customer comparisons, store vs. region calculations, and unique customer counts on billions of rows of data
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Data Scientists, BI Analysts, Data & Analytics Leaders, Sales Operations & Demand Planning Professionals, Supply Chain & Logistics Professionals, Finance Analysts.