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

AWS Big Data

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

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Data Intelligence in the Next Normal; Why, Who and When?

erwin

As the economy slowed, they focused on cost optimization. I have long stated that data is the lifeblood of digital transformation, and if the pandemic really has accelerated digital transformation, then the trends reported in IDC’s worldwide surveys make sense. Technical metadata is what makes up database schema and table definitions.

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Minimizing Supply Chain Disruptions with Advanced Analytics

Cloudera

Advanced analytics and enterprise data empower companies to not only have a completely transparent view of movement of materials and products within their line of sight, but also leverage data from their suppliers to have a holistic view 2-3 tiers deep in the supply chain. Digital Transformation is not without Risk.

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Process and analyze highly nested and large XML files using AWS Glue and Amazon Athena

AWS Big Data

By analyzing XML files, organizations can easily integrate data from different sources and ensure consistency across their systems, However, XML files contain semi-structured, highly nested data, making it difficult to access and analyze information, especially if the file is large and has complex, highly nested schema.

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How Ruparupa gained updated insights with an Amazon S3 data lake, AWS Glue, Apache Hudi, and Amazon QuickSight

AWS Big Data

AWS DMS is a database migration tool that supports many relational database management services, and also supports Amazon S3. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data. The audience of these few reports was limited—a maximum of 20 people from management.

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The Future of the Data Lakehouse – Open

CIO Business Intelligence

It provided the concept of a database, schemas, and tables for describing the structure of a data lake in a way that let BI tools traverse the data efficiently. If large and valuable data for the enterprise is managed, then there has to be openness for the business to choose different analytic engines, or even vendors.

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The Future of the Data Lakehouse – Open

Cloudera

It provided the concept of a database, schemas, and tables for describing the structure of a data lake in a way that let BI tools traverse the data efficiently. If large and valuable data for the enterprise is managed, then there has to be openness for the business to choose different analytic engines, or even vendors.