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

AWS Big Data

The AWS Glue job can transform the raw data in Amazon S3 to Parquet format, which is optimized for analytic queries. The AWS Glue Data Catalog stores the metadata, and Amazon Athena (a serverless query engine) is used to query data in Amazon S3.

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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. Data streaming also helps you optimize data pipelines by processing only the change events, allowing you to respond to data changes more quickly and efficiently.

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5 Ways Data Engineers Can Support Data Governance

Alation

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? Do they have a system to manage the metadata for given assets? One example is the EU’s General Data Protection Regulation (GDPR).

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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. With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs.