Remove Analytics Remove Data Architecture Remove Data Integration Remove Metadata
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Data architecture strategy for data quality

IBM Big Data Hub

Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few. But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality.

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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

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions.

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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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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights. Analytics use cases on data lakes are always evolving. In this method, the metadata are recreated in an isolated environment and colocated with the existing data files.

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How Knowledge Graphs Power Data Mesh and Data Fabric

Ontotext

In most enterprises data teams lack a data map and data asset inventory and are often unaware of data that exists across the organization, its associated profile, quality and associated metadata. Teams can’t access data to build their business use cases. For example, a product data tag is basic metadata.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The program must introduce and support standardization of enterprise data. Programs must support proactive and reactive change management activities for reference data values and the structure/use of master data and metadata. One of its key capabilities, TrustCheck, provides real-time “guardrails” to workflows.