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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. This allows the organization to comply with government regulations and internal security policies.

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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. This allows the organization to comply with government regulations and internal security policies.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.

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Expanding Role of Data Governance, Metadata Management, and Data Quality

TDAN

Ensuring data quality is an important aspect of data management and these days, DBAs are increasingly being called upon to deal with the quality of the data in their database systems more than ever before. The importance of quality data cannot be overstated.

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Data Speaks for Itself: Is Metadata Data?

TDAN

Well, of course, metadata is data. Our standard definition explicitly says that metadata is data describing other data. So why would I even ask this question in the article title?

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Metadata Governance: An Outline for Success (Part Two)

TDAN

In part one of “Metadata Governance: An Outline for Success,” I discussed the steps required to implement a successful data governance environment, what data to gather to populate the environment, and how to gather the data.

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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Source: [link] SAP also announced key partners that further enhance Datasphere as a powerful business data fabric.