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Composable data management at Meta

Engineering at Meta

In recent years, Meta’s data management systems have evolved into a composable architecture that creates interoperability, promotes reusability, and improves engineering efficiency. Data is at the core of every product and service at Meta. Data is at the core of every product and service at Meta.

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Master Data Management: Common Misconceptions You Should Know

Precisely

When most people think of master data management, they first think of customers and products. But master data encompasses so much more than data about customers and products. Challenges of Master Data Management A decade ago, master data management (MDM) was a much simpler proposition than it is today.

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Aligning Velox and Apache Arrow: Towards composable data management

Engineering at Meta

This new convergence helps Meta and the larger community build data management systems that are unified, more efficient, and composable. Meta’s Data Infrastructure teams have been rethinking how data management systems are designed.

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Modern Data Management Essentials: Exploring Data Fabric

Precisely

Key Takeaways Data Fabric is a modern data architecture that facilitates seamless data access, sharing, and management across an organization. Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata.

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Why is Data Management so Important to Data Science?

KDnuggets

High data availability may help power digital transformation, but data management systems are needed to keep that data organizaed and make it accessible. Read this article to see why data management is important to data science.

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ROW and Easement Data Management Solution Released

ArcGIS

ROW and Easement Data Management improves infrastructure planning, utility maintenance, and other functions that require access to land.

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Managing Database Access Control For Teams With strongDM

Data Engineering Podcast

Summary Controlling access to a database is a solved problem… right? It can be straightforward for small teams and a small number of storage engines, but once either or both of those start to scale then things quickly become complex and difficult to manage.