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Building a Beautiful Data Lakehouse

CIO Business Intelligence

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Warehouse, data lake convergence. Meet the data lakehouse.

Data Lake 119
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Your 5-Step Journey from Analytics to AI

CIO Business Intelligence

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Just starting out with analytics?

Analytics 115
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Use AWS Glue to streamline SFTP data processing

AWS Big Data

With AWS Glue, you can discover and connect to hundreds of diverse data sources and manage your data in a centralized data catalog. It enables you to visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

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4 ways generative AI addresses manufacturing challenges

IBM Big Data Hub

Or we create a data lake, which quickly degenerates to a data swamp. Generative AI makes other AI and analytics technologies more consumable, which helps manufacturing enterprises realize the value of their investments. Or we keep adding applications, so our technical debt continues to increase.

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Prepare and load Amazon S3 data into Teradata using AWS Glue through its native connector for Teradata Vantage

AWS Big Data

With AWS Glue, you can discover and connect to more than 100 diverse data sources and manage your data in a centralized data catalog. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

IT 109
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Addressing the Three Scalability Challenges in Modern Data Platforms

Cloudera

In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads. Increased integration costs using different loose or tight coupling approaches between disparate analytical technologies and hosting environments.

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Customer Data Culture: The Innovators Have Already Reinvented Themselves

Alation

The re-insurance product that they introduced was inspired by collaboration between geographically dispersed teams coming together through the Alation Data Catalog. With the introduction of a new data lake, MunichRe created a new way for actuaries and business experts to explore new product concepts and test new markets.