Remove Data Engineering Remove Data Governance Remove Data Silos
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Governing the ML lifecycle at scale, Part 3: Setting up data governance at scale

Flipboard

This post is part of an ongoing series about governing the machine learning (ML) lifecycle at scale. This post dives deep into how to set up data governance at scale using Amazon DataZone for the data mesh. However, as data volumes and complexity continue to grow, effective data governance becomes a critical challenge.

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How to Power Successful AI Projects with Trusted Data

Precisely

Data quality and governance gaps = inaccurate results A lack of data governance and quality can lead to inaccuracies, hallucinations, and AI failures. AI systems require high-quality, well-governed data to avoid missteps. Ask yourself questions like: Does our data have proper governance and quality controls?

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Using Snowflake Data as an Insurance Company

phData

Insurance companies often face challenges with data silos and inconsistencies among their legacy systems. To address these issues, they need a centralized and integrated data platform that serves as a single source of truth, preferably with strong data governance capabilities.

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How to Build a Data Mesh in Snowflake

phData

A data mesh is a decentralized approach to data architecture that’s been gaining traction as a solution to the challenges posed by large and complex data ecosystems. It’s all about breaking down data silos, empowering domain teams to take ownership of their data, and fostering a culture of data collaboration.

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Data Catalog: Part of the Solution – or Part of the Problem?

Alation

Today a modern catalog hosts a wide range of users (like business leaders, data scientists and engineers) and supports an even wider set of use cases (like data governance , self-service , and cloud migration ). So feckless buyers may resort to buying separate data catalogs for use cases like…. Data governance.

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Data architecture strategy for data quality

IBM Journey to AI blog

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

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Alation and Tableau: From Data Rich to Data Driven

Alation

Mind the (Data Accessibility) Gap. Data is more accessible than ever. Although we don’t live in a perfect data world, data teams throughout nearly every industry have made progress breaking down data silos and moving data to the cloud to take advantage of new capabilities. Use data properly.

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