#190: I See Your Data Layer and Raise You a Metrics Layer with Benn Stancil
Apr 5, 2022
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Benn Stancil from Mode joins the hosts to discuss the metrics layer in the modern data stack. Topics include challenges with model data and report tables, handling digital analytics data, managing metrics at large companies like Facebook, the importance of metrics in a modern data stack, challenges of building and adopting a metrics layer tool, connection between OLAP and Edgar Codd, normalization rules, and implementing a metrics layer in business intelligence tools.
A metrics layer is an essential component of the modern data stack to ensure consistent metrics and definitions across businesses.
Building a metrics layer in-house can be challenging and may require proper governance and best practices to avoid metrics bloat and maintain data integrity.
Implementing a metrics layer in the modern data stack may involve difficulties in migration and obtaining buy-in from the business, but gradually replacing metrics in a piecemeal manner and effective communication about its importance can help overcome these challenges.
Deep dives
The Evolution of the Modern Data Stack
The podcast episode discusses the development and challenges of the modern data stack. The hosts introduce their guest, Ben Stansall, the Chief Analytics Officer and Founder of Mode. Ben shares his background and how his company aims to help data analysts and scientists with data analysis, visualization, and sharing. The conversation explores the concept of the modern data stack, its definition, and the need for consistent metrics and definitions across businesses. The discussion also touches on the difficulty of building a metrics layer tool in-house and the potential challenges of adoption.
Challenges in Defining the Modern Data Stack
The conversation delves into the various definitions and interpretations of the modern data stack. Different perspectives emerge, including the unbundling of tools, decentralization, and delamination of the warehouse. The guest proposes his own definition, referring to it as analytics tools that were launched in the product era. The discussion further emphasizes the importance of metrics layers and the challenges in standardizing metrics across different tools.
The Implementation and Migration Challenges
The conversation highlights the complexity of implementing a metrics layer and the migration challenges associated with such a transition. It's suggested that companies going through a version update or cleanup of data debt are more likely to adopt a metrics layer tool. Additionally, the discussion touches on the difficulties of building a metrics layer in-house and the need for proper governance and best practices to avoid metrics bloat and maintain data integrity.
Importance of Metrics and Definitions in Analyzing Data
Having clear and consistent metrics and definitions is crucial in analyzing data. This ensures that everyone in the organization is counting the same way and reporting is consistent. Overcomplicating language and using complex charts can hinder understanding, so it's important to communicate data in simple and clear stories. Additionally, focusing on a finite set of key metrics rather than trying to optimize numerous ones allows for better decision-making and alignment in the organization.
Challenges of Implementing a Metrics Layer in the Modern Data Stack
Introducing a metrics layer in the modern data stack can pose challenges in terms of implementation and buy-in from the business. While metrics layer tools are still relatively new, gradually replacing metrics in a piecemeal manner may be feasible, as opposed to a monolithic cutover. Leveraging tools that aid discoverability and tracking of metrics can also assist in the transition. However, obtaining buy-in and prioritizing a metrics layer may require effective communication about its importance and long-term benefits to overcome potential resistance.
"Modern art" was a terrible label because, ya' know, time would pass and here we are 50 years after the end of that period shaking our heads at what a short-sighted semantic gaff that was. We share that observation for no particular reason. On this episode, we sat down with broad, deep, and entertaining thinker Benn Stancil from Mode to talk about one facet of the modern data stack: the metrics layer. What is it? Who's thinking about solving for it? What is a monthly DAU? These are questions to ponder that, hopefully, won't leave you impersonating a piece of modern art. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
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