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Why companies are in need of data lineage solutions

O'Reilly on Data

The O’Reilly Data Show Podcast: Neelesh Salian on data lineage, data governance, and evolving data platforms. In this episode of the Data Show , I spoke with Neelesh Salian , software engineer at Stitch Fix , a company that combines machine learning and human expertise to personalize shopping.

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What Is Data Governance? (And Why Your Organization Needs It)

erwin

Organizations with a solid understanding of data governance (DG) are better equipped to keep pace with the speed of modern business. In this post, the erwin Experts address: What Is Data Governance? Why Is Data Governance Important? What Is Good Data Governance? What Is Data Governance?

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.

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HEMA accelerates their data governance journey with Amazon DataZone

AWS Big Data

Initially, the data inventories of different services were siloed within isolated environments, making data discovery and sharing across services manual and time-consuming for all teams involved. Implementing robust data governance is challenging.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs. Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications.

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It’s 2025. Are your data strategies strong enough to de-risk AI adoption?

CIO Business Intelligence

Despite decades of investment in data management solutions, many continue to struggle with data quality issues, either through their failure to modernise legacy investments or through the outcomes of acquisitions and business decisions, which in either instance have led to data existing in multiple silos across their organisations.

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The future of data: A 5-pillar approach to modern data management

CIO Business Intelligence

The proposed model illustrates the data management practice through five functional pillars: Data platform; data engineering; analytics and reporting; data science and AI; and data governance. This development will make it easier for smaller organizations to start incorporating AI/ML capabilities.

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Partner Webinar: A Framework for Building Data Mesh Architecture

Speaker: Jeremiah Morrow, Nicolò Bidotti, and Achille Barbieri

In this webinar, learn how Enel Group worked with Agile Lab to implement Dremio as a data mesh solution for providing broad access to a unified view of their data, and how they use that architecture to enable a multitude of use cases. Leveraging Dremio for data governance and multi-cloud with Arrow Flight.