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The Future of the Data Lakehouse – Open

CIO Business Intelligence

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

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The Future of the Data Lakehouse – Open

Cloudera

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

Streaming data facilitates the constant flow of diverse and up-to-date information, enhancing the models’ ability to adapt and generate more accurate, contextually relevant outputs. In this post, we discuss why data streaming is a crucial component of generative AI applications due to its real-time nature.

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5 Ways Data Engineers Can Support Data Governance

Alation

What’s worse, just 3% of the data in a business enterprise meets quality standards. There’s also no denying that data management is becoming more important, especially to the public. This has spawned new legislation controlling how data can be collected, stored, and utilized, such as the GDPR or CCPA.

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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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Introducing watsonx: The future of AI for business

IBM Big Data Hub

At IBM, we believe it is time to place the power of AI in the hands of all kinds of “AI builders” — from data scientists to developers to everyday users who have never written a single line of code. It helps facilitate the entire data and AI lifecycle, from data preparation to model development, deployment and monitoring.

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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.