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

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. 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.

Data Lake 102
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The Data Lakehouse: Blending Data Warehouses and Data Lakes

Data Virtualization

Reading Time: 3 minutes First we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one? In a way, the name describes what.

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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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Doing Cloud Migration and Data Governance Right the First Time

erwin

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (APIs), file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

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My Understanding of the Gartner® Hype Cycle™ for Finance Data and Analytics Governance, 2023

Data Virtualization

As noted in the Gartner Hype Cycle for Finance Data and Analytics Governance, 2023, “Through. The post My Understanding of the Gartner® Hype Cycle™ for Finance Data and Analytics Governance, 2023 appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Finance 69
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Data architecture strategy for data quality

IBM Big Data Hub

Next generation of big data platforms and long running batch jobs operated by a central team of data engineers have often led to data lake swamps. Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads.

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Five benefits of a data catalog

IBM Big Data Hub

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Technical metadata to describe schemas, indexes and other database objects.