Summary

Collecting and cleaning data is only useful if someone can make sense of it afterward. The latest evolution in the data ecosystem is the introduction of a dedicated metrics layer to help address the challenge of adding context and semantics to raw information. In this episode Nick Handel shares the story behind Transform, a new platform that provides a managed metrics layer for your data platform. He explains the challenges that occur when metrics are maintained across a variety of systems, the benefits of unifying them in a common access layer, and the potential that it unlocks for everyone in the business to confidently answer questions with data.

Announcements

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• Your host is Tobias Macey and today I’m interviewing Nick Handel about Transform, a platform providing a dedicated metrics layer for your data stack

Interview

• Introduction
• How did you get involved in the area of data management?
• Can you describe what Transform is and the story behind it?
• How do you define the concept of a "metric" in the context of the data platform?
• What are the general strategies in the industry for creating, managing, and consuming metrics?
  • How has that been changing in the past couple of years?
    • What is driving that shift?
• What are the main goals that you have for the Transform platform?
  • Who are the target users? How does that focus influence your approach to the design of the platform?
• How is the Transform platform architected?
  • What are the core capabilities that are required for a metrics service?
• What are the integration points for a metrics service?
• Can you talk through the workflow of defining and consuming metrics with Transform?
  • What are the challenges that teams face in establishing consensus or a shared understanding around a given metric definition?
  • What are the lifecycle stages that need to be factored into the long-term maintenance of a metric definition?
• What are some of the capabilities or projects that are made possible by having a metrics layer in the data platform?
• What are the capabilities in downstream tools that are currently missing or underdeveloped to support the metrics store as a core layer of the platform?
• What are the most interesting, innovative, or unexpected ways that you have seen Transform used?
• What are the most interesting, unexpected, or challenging lessons that you have learned while working on Transform?
• When is Transform the wrong choice?
• What do you have planned for the future of Transform?

Contact Info

• LinkedIn
• @nick_handel on Twitter

Parting Question

• From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

• Transform
• Transform’s Metrics Framework
• Transform’s Metrics Catalog
• Transform’s Metrics API
• Nick’s experiences using Airbnb’s Metrics Store
• Get Transform
• BlackRock
• AirBnB
• Airflow
• Superset
  • Podcast Episode
• AirBnB Knowledge Repo
• AirBnB Minerva Metric Store
• OLAP Cube
• Semantic Layer
• Master Data Management
  • Podcast Episode
• Data Normalization
• OpenLineage

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA