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RDF-Star: Metadata Complexity Simplified

Ontotext

With graph databases the representation of relationships as data make it possible to better represent data in real time, addressing newly discovered types of data and relationships. Relational databases benefit from decades of tweaks and optimizations to deliver performance. It provides meaning.

Metadata 119
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Metadata Management, Data Governance and Automation

erwin

In most companies, an incredible amount of data flows from multiple sources in a variety of formats and is constantly being moved and federated across a changing system landscape. With automation, data professionals can meet the above needs at a fraction of the cost of the traditional, manual way.

Metadata 102
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How Metadata Makes Data Meaningful

erwin

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

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How Metadata Makes Data Meaningful

erwin

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time. Apache Iceberg offers integrations with popular data processing frameworks such as Apache Spark, Apache Flink, Apache Hive, Presto, and more.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

Several of the overall benefits of data management can only be realized after the enterprise has established systematic data governance. To counter that, BARC recommends starting with a manageable or application-specific prototype project and then expanding across the company based on lessons learned.

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Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.