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Navigating the Data Mesh Landscape: Insights and Trends

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Chapter 1: Understanding Data Mesh

In this week's edition of your go-to Data, AI & Analytics Digest, we delve into the intriguing world of Data Mesh, featuring survey outcomes, data retention insights, and the potential of AI.

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The results from our recent survey on Data Mesh have revealed surprising trends, indicating that this concept will be significant in 2022. To further explore this topic, join us on January 31 for an insightful discussion on how Data Mesh relates to your existing architectural frameworks and the Modern Data Stack, led by experts Matt Housley and Joe Reis.

For a primer on Data Mesh, check out my LinkedIn blog, which includes resources to help you navigate this evolving concept for your organization.

Section 1.1: The Data Mesh Debate

Data Mesh has sparked lively discussions, with many questioning its novelty and relevance. The term gained traction in 2021, as highlighted by surveys I conducted on LinkedIn and Tony Baer's insights in ZDNet. However, be cautious of "VendorSpeak," which may obscure its true meaning.

To aid your understanding, I've compiled a list of unbiased principles that can help the community refine this essential concept.

Section 1.2: Data Retention Insights

Recent data from IDC and Research and Markets, as reported by Datanami's Alex Woodie, offers intriguing insights:

  1. The global big data and business analytics market is projected to hit $448 billion by 2027, with IDC forecasting a staggering 175ZB of new data creation by 2025.
  2. In 2020, only 2% of the 64.1 ZB of data generated was retained into 2021.
  3. Data storage is lagging behind data creation by a significant margin, with only 6.7ZB of installed storage in 2020.

David Reinsel from IDC noted that the volume of digital data created in the next five years will exceed twice the total amount created since the dawn of digital storage.

Chapter 2: Innovations and Achievements

In the video "Behind the Hype: Why Data Mesh Is Not Right For You," industry experts discuss the potential pitfalls of adopting Data Mesh without careful consideration. This video is a must-watch for anyone looking to navigate the complexities of this paradigm.

The second video, "What is DATA MESH? And how not to mesh it up," provides a foundational understanding of Data Mesh, offering practical advice on how to implement it effectively within your organization.

In the realm of safety, Subaru's ambitious vision aims for zero fatal traffic accidents by 2030. This initiative combines AI, machine learning, and advanced real-time technologies, showcasing how innovation can drive societal change.

Highlighting excellence in data management, my Customer of the Week Award goes to Di Mayze, Global Head of Data and AI at WPP. Her team has developed strong data discovery and curation capabilities across over 500 datasets, empowering a community of 3,000 employees with a goal to upskill 50,000.

Similarly, Ramnik Kaur, Head of Infrastructure at LiveRamp, has achieved remarkable scale with 100,000 applications and 30 petabytes of data, enabling 600 partnerships for 75 million households.

As we look ahead, the technology trends for 2022 include Edge Computing, AI, and IoT, all contributing to a race towards a trillion-dollar market.

Lastly, the concept of Product-Led Growth (PLG) is gaining traction, emphasizing the importance of product usage in driving growth. As the landscape shifts from term licenses to subscription models, understanding this paradigm is crucial for both buyers and developers.

For additional resources, consider checking out the Ultimate Product-Led Growth Resources Guide and the insightful piece by Ben Horowitz on the distinctions between good and bad product managers.

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