Remove Data Governance Remove Data Processing Remove Management Remove Metadata
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Data Governance Maturity and Tracking Progress

erwin

Data governance is best defined as the strategic, ongoing and collaborative processes involved in managing data’s access, availability, usability, quality and security in line with established internal policies and relevant data regulations. Data Governance Is Business Transformation. Predictability.

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How Data Governance Protects Sensitive Data

erwin

Organizations are managing more data than ever. With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance.

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Data governance beyond SDX: Adding third party assets to Apache Atlas

Cloudera

In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. The SDX layer of CDP leverages the full spectrum of Atlas to automatically track and control all data assets.

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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. 10) Data Quality Solutions: Key Attributes.

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Orchestrate an end-to-end ETL pipeline using Amazon S3, AWS Glue, and Amazon Redshift Serverless with Amazon MWAA

AWS Big Data

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that you can use to set up and operate data pipelines in the cloud at scale. By using multiple AWS accounts, organizations can effectively scale their workloads and manage their complexity as they grow.

Metadata 100
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Gartner Data & Analytics Summit 2022 in London: 3 Key Takeaways

Alation

Establish what data you have. Active metadata gives you crucial context around what data you have and how to use it wisely. Active metadata provides the who, what, where, and when of a given asset, showing you where it flows through your pipeline, how that data is used, and who uses it most often. Data Governance.

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Introducing AWS Glue crawler and create table support for Apache Iceberg format

AWS Big Data

Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. Iceberg captures metadata information on the state of datasets as they evolve and change over time. For more details, refer to Creating Apache Iceberg tables.