Data Analytics

Open Source Reverse ETL For Everyone With Grouparoo - Episode 254

Reverse ETL is a product category that evolved from the landscape of customer data platforms with a number of companies offering their own implementation of it. While struggling with the work of automating data integration workflows with marketing, sales, and support tools Brian Leonard accidentally discovered this need himself and turned it into the open source framework Grouparoo. In this episode he explains why he decided to turn these efforts into an open core business, how the platform is implemented, and the benefits of having an open source contender in the landscape of operational analytics products.

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Fast And Flexible Headless Data Analytics With Cube.JS - Episode 248

One of the perennial challenges of data analytics is having a consistent set of definitions, along with a flexible and performant API endpoint for querying them. In this episode Artom Keydunov and Pavel Tiunov share their work on Cube.js and the various ways that it is being used in the open source community.

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Experimentation and A/B Testing For Modern Data Teams With Eppo - Episode 244

A/B testing and experimentation are the most reliable way to determine whether a change to your product will have the desired effect on your business. Unfortunately, being able to design, deploy, and validate experiments is a complex process that requires a mix of technical capacity and organizational involvement which is hard to come by. Chetan Sharma founded Eppo to provide a system that organizations of every scale can use to reduce the burden of managing experiments so that you can focus on improving your business. In this episode he digs into the technical, statistical, and design requirements for running effective experiments and how he has architected the Eppo platform to make the process more accessible to business and data professionals.

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Removing The Barrier To Exploratory Analytics with Activity Schema and Narrator - Episode 234

The perennial question of data warehousing is how to model the information that you are storing. This has given rise to methods as varied as star and snowflake schemas, data vault modeling, and wide tables. The challenge with many of those approaches is that they are optimized for answering known questions but brittle and cumbersome when exploring unknowns. In this episode Ahmed Elsamadisi shares his journey to find a more flexible and universal data model in the form of the “activity schema” that is powering the Narrator platform, and how it has allowed his customers to perform self-service exploration of their business domains without being blocked by schema evolution in the data warehouse. This is a fascinating exploration of what can be done when you challenge your assumptions about what is possible.

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Data Discovery From Dashboards To Databases With Castor - Episode 210

Every organization needs to be able to use data to answer questions about their business. The trouble is that the data is usually spread across a wide and shifting array of systems, from databases to dashboards. The other challenge is that even if you do find the information you are seeking, there might not be enough context available to determine how to use it or what it means. Castor is building a data discovery platform aimed at solving this problem, allowing you to search for and document details about everything from a database column to a business intelligence dashboard. In this episode CTO Amaury Dumoulin shares his perspective on the complexity of letting everyone in the company find answers to their questions and how Castor is designed to help.

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Bringing The Metrics Layer To The Masses With Transform - Episode 206

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.

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