Data Mesh Radio

#271 The Importance of Repeatability of Language to Scalability - Mesh Musings 56

Nov 24, 2023

The podcast discusses the importance of repeatability in language to achieve scalability in data and software work. It highlights the challenges of varying user experiences in data products and the need for universal definitions. It also emphasizes the importance of universal standards for data quality and simplified definitions. The podcast encourages identifying and addressing unnecessary friction to improve data quality and adoption.

11:22

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Quick takeaways

Establishing universal standards and definitions for data aspects like quality enhances trust and simplifies data work for producers and consumers.

Providing a centralized platform for measuring data quality metrics reduces the burden on data producers and makes it easier for consumers to understand data, leading to increased usage and adoption.

Deep dives

The Importance of Repeatability of Language to Scalability

The podcast episode emphasizes the significance of repeatability and automation of language in achieving scalability in data and software work. While much focus is placed on repeatability around code and data transformations, the episode argues for the need to establish universal standards and definitions when it comes to aspects that touch all data products. This includes data quality measurements, where having consistent definitions and measurements across data products enhances trust, enables better data combination, and reduces complexity for both producers and consumers. The episode suggests that finding places to simplify and standardize definitions, especially in areas where nuance isn't valuable, can save time and effort for everyone involved in data work.

Introduction

2min

The Importance of Repeatability of Language to Scalability

3min

The Importance of Universal Standards for Data Quality and Repeatability

3min

The Importance of Standardized Definitions and Simplification for Scalable Data

3min

Important points:

There are places where nuance adds value. Many times, explicit definitions around data aspects like quality or even SRE metrics like uptime and query performance are not one.
Provide a simple way for producers to apply these scalable approaches - the platform should measure data quality metrics for example.
Data producers are having a hard enough time in general learning how to leverage data better. Find places to make it about learning about the information encapsulated in the data product, not learning a new set of SLAs for each data product.
Consumers will thank you too since it make their lives easier. With that, you should see more of an uptick in data usage.

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All music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman): Lesfm, MondayHopes, SergeQuadrado, ItsWatR, Lexin_Music, and/or nevesf

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Data Mesh Radio

#271 The Importance of Repeatability of Language to Scalability - Mesh Musings 56

Podcast summary created with Snipd AI

Quick takeaways

Deep dives

The Importance of Repeatability of Language to Scalability

Simplifying and Standardizing for Scalability

Remember Everything You Learn from Podcasts