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Data Engineering Best Practices - #2. Metadata & Logging

Start Data Engineering

Metadata: Information about pipeline runs, & data flowing through your pipeline 3.2. Introduction 2. Setup & Logging architecture 3. Data Pipeline Logging Best Practices 3.1. Obtain visibility into the code’s execution sequence using text logs 3.3. Understand resource usage by tracking Metrics 3.4.

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Machine Learning Metadata Store

KDnuggets

In this article, we will learn about metadata stores, the need for them, their components, and metadata store management.

Metadata 157
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How Metadata Improves Security, Quality, and Transparency

KDnuggets

Metadata is the data providing context about the data, more than what you see in the rows and columns. By managing your metadata, you're effectively creating an encyclopedia of your data assets.

Metadata 148
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Metadata Management and Data Governance with Cloudera SDX

Cloudera

This will allow a data office to implement access policies over metadata management assets like tags or classifications, business glossaries, and data catalog entities, laying the foundation for comprehensive data access control. First, a set of initial metadata objects are created by the data steward.

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Metadata Management & Data Governance with Cloudera SDX

Cloudera

This will allow a data office to implement access policies over metadata management assets like tags or classifications, business glossaries, and data catalog entities, laying the foundation for comprehensive data access control. First, a set of initial metadata objects are created by the data steward.

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Eliminate Friction In Your Data Platform Through Unified Metadata Using OpenMetadata

Data Engineering Podcast

Summary A significant source of friction and wasted effort in building and integrating data management systems is the fragmentation of metadata across various tools. After experiencing the impacts of fragmented metadata and previous attempts at building a solution Suresh Srinivas and Sriharsha Chintalapani created the OpenMetadata project.

Metadata 100
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Metadata Management And Integration At LinkedIn With DataHub

Data Engineering Podcast

The key to those solutions is a robust and flexible metadata management system. LinkedIn has gone through several iterations on the most maintainable and scalable approach to metadata, leading them to their current work on DataHub. What were you using at LinkedIn for metadata management prior to the introduction of DataHub?

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