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Low Friction Data Governance With Immuta

Data Engineering Podcast

Summary Data governance is a term that encompasses a wide range of responsibilities, both technical and process oriented. One of the more complex aspects is that of access control to the data assets that an organization is responsible for managing. What is data governance? How is the Immuta platform architected?

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Beyond Legacy Detection: How AI-Driven Data Governance Surpasses Traditional Methods

Striim

These incidents serve as a stark reminder that legacy data governance systems, built for a bygone era, are struggling to fend off modern cyber threats. They react too slowly, too rigidly, and cant keep pace with the dynamic, sophisticated attacks occurring today, leaving hackable data exposed.

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A Guide to Data Pipelines (And How to Design One From Scratch)

Striim

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. We’ll answer the question, “What are data pipelines?” Table of Contents What are Data Pipelines?

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The Challenge of Data Quality and Availability—And Why It’s Holding Back AI and Analytics

Striim

Business Intelligence Needs Fresh Insights: Data-driven organizations make strategic decisions based on dashboards, reports, and real-time analytics. If data is delayed, outdated, or missing key details, leaders may act on the wrong assumptions. Poor data management can lead to compliance risks, legal issues, and reputational damage.

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No Python, No SQL Templates, No YAML: Why Your Open Source Data Quality Tool Should Generate 80% Of Your Data Quality Tests Automatically

DataKitchen

Current open-source frameworks like YAML-based Soda Core, Python-based Great Expectations, and dbt SQL are frameworks to help speed up the creation of data quality tests. They are all in the realm of software, domain-specific language to help you write data quality tests. Download Now Request Demo

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The Intersection of GenAI and Streaming Data: What’s Next for Enterprise AI?

Striim

The Future of Enterprise AI: Moving from Vision to Reality Successfully integrating GenAI with real-time data streaming requires strategic investments across infrastructure, data governance, and AI model development. Sherlock monitors your data streams to identify sensitive information.

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What is Apache Iceberg: Features, Architecture & Use Cases

ProjectPro

Ensure strong data governance and auditability. Support time travel queries and rollback capabilities for data recovery or compliance. This setup is particularly beneficial for e-commerce platforms and content providers aiming to enhance user engagement through data-driven decisions. GitHub Repository: tj /iceberg-demo 3.