Remove 2023 Remove Data Integration Remove Data Lake Remove Metadata
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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 105
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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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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

AWS Big Data

You can slice data by different dimensions like job name, see anomalies, and share reports securely across your organization. With these insights, teams have the visibility to make data integration pipelines more efficient. An AWS Glue crawler scans data on the S3 bucket and populates table metadata on the AWS Glue Data Catalog.

Metrics 108
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Amazon Redshift announcements at AWS re:Invent 2023 to enable analytics on all your data

AWS Big Data

These announcements drive forward the AWS Zero-ETL vision to unify all your data, enabling you to better maximize the value of your data with comprehensive analytics and ML capabilities, and innovate faster with secure data collaboration within and across organizations.

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AWS re:Invent 2023 Amazon Redshift Sessions Recap

AWS Big Data

Sessions ANT203 | What’s new in Amazon Redshift Watch this session to learn about the newest innovations within Amazon Redshift—the petabyte-scale AWS Cloud data warehousing solution. Easily build and train machine learning models using SQL within Amazon Redshift to generate predictive analytics and propel data-driven decision-making.

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The Enduring Significance of Data Modeling in the Modern Data-Driven Enterprise

erwin

It delivers the ability to capture and unify the business and technical perspectives of data assets, enables effective collaboration between a variety of stakeholders, and delivers metadata-driven automation to accelerate the creation and maintenance of data sources on virtually any data management platform. by Quest ®.