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Metadata Management and Data Governance with Cloudera SDX

Cloudera

In this article, we will walk you through the process of implementing fine grained access control for the data governance framework within the Cloudera platform. Case Introduction In this article we will take the example of a data governance office that wants to control access to metadata objects in the company’s central data repository.

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Metadata Management & Data Governance with Cloudera SDX

Cloudera

In this article, we will walk you through the process of implementing fine grained access control for the data governance framework within the Cloudera platform. Case Introduction In this article we will take the example of a data governance office that wants to control access to metadata objects in the company’s central data repository.

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FedRAMP In Process Designation, A Milestone in Cybersecurity Commitment

Cloudera

I am pleased to announce that Cloudera has achieved FedRAMP “In Process”, a significant milestone that underscores our commitment to providing the public sector with secure and reliable data management solutions across on-prem, hybrid and multi-cloud environments.

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2. Diving Deeper into Psyberg: Stateless vs Stateful Data Processing

Netflix Tech

By Abhinaya Shetty , Bharath Mummadisetty In the inaugural blog post of this series, we introduced you to the state of our pipelines before Psyberg and the challenges with incremental processing that led us to create the Psyberg framework within Netflix’s Membership and Finance data engineering team.

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Streaming Ingestion for Apache Iceberg With Cloudera Stream Processing

Cloudera

It allows multiple data processing engines, such as Flink, NiFi, Spark, Hive, and Impala to access and analyze data in simple, familiar SQL tables. The CSP engine is powered by Apache Flink, which is the best-in-class processing engine for stateful streaming pipelines. Currently, Iceberg support in CSP is in technical preview mode.

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What Are the Best Data Modeling Methodologies & Processes for My Data Lake?

phData: Data Engineering

However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. With many data modeling methodologies and processes available, choosing the right approach can be daunting. Efficiency through being able to streamline data storage and retrieval processes.

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The Data Discovery Team

Jesse Anderson

A Guest Post by Ole Olesen-Bagneux In this blog post I would like to describe a new data team, that I call ‘the data discovery team’. And that is what the data discovery team that I propose in this blog post should work on: searching for data. In an enterprise data reality, searching for data is a bit of a hassle.

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