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From Data Mesh to Valuable Data Products: A Comprehensive Guide

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Chapter 1: Understanding Your Data Strategy

If you're new here, welcome to your go-to source for Data, AI, and Analytics updates. In this weekly digest, I sift through the most impactful data stories, presenting what's trending and what's not.

  1. Assessing Your Data Strategy Stage

To gauge where you stand in your data strategy journey, take a look at Samir's survey below. Recent findings reveal three crucial insights:

  • Over half of the participants (53.0%) claim to have a corporate data strategy in place.
  • Less than 60% of these strategies are reported to be yielding positive outcomes.
  • Transitioning to a "data-driven" approach may take longer than anticipated. While 60% believe it should take 2 to 3 years, the reality could be closer to the 30% who indicate a timeframe of 4 to 5 years or more.

Credit to Randy Bean. Participate in Samir's survey here.

Data strategy assessment survey results

The fundamental issue with data challenges isn't rooted in our technology but rather in our data management frameworks, as stated by Joe Hilleary from Eckerson Group.

  1. Seven Steps to Crafting a Valuable Data Product

Insights from Joseph Hilleary of Eckerson Group provide a valuable roadmap for building effective data products:

  • Begin by understanding consumer needs: What issues are they facing? What existing resources fall short?
  • Identify your target market: Who stands to gain from your product, and what value does it add to the organization?
  • Release a prototype for initial testing.
  • Open channels for feedback: Utilizing a data catalog or internal data exchange can facilitate structured feedback from users.
  • Create a collaborative environment: A platform that allows data providers and consumers to work together securely is ideal, enabling analysts to demonstrate how they manipulate data post-provisioning.
  • Prepare for iterations: Repeat steps 3 to 5 until the product aligns with demand.
  • Focus on publishing and refining: Concentrate on one product at a time while remaining open to revisiting earlier decisions during the development of future products.
Steps to building a data product
  1. Customer Spotlight: Postmates & Delivery Hero

This week, I want to highlight two remarkable customers: Aaron Biller and Matteo Fava, who were recently featured in our new DataJourneys podcast format. Thanks to Mark Mirchandani and Stephanie Wong for showcasing their contributions!

  1. Embracing Technology Adoption

Technology adoption hinges on five vital components: Use cases, Skills, Data, Technology, and Organization.

Components of technology adoption
  1. Developing Your Analytics Roadmap

An insightful blog by Xiao Zhou from Best Buy outlines a framework for creating an analytics roadmap:

  1. We aim to ____
  2. Today we ____
  3. Ideally, we should ____
  4. Fill the gap
Framework for analytics roadmap development

EXTRAS

Extra resources for data strategies Additional insights on data management

How BERT Enhances Google Search Language Understanding

Understanding the distinction between recognizing words and grasping their meanings is crucial. This video delves into the nuances!

In Case You Missed It: Replay of The Monday Morning Data Chat

Don't forget to join me next week for the State of Data Mesh 2022 (register here).

Upcoming event: State of Data Mesh 2022

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