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Comprehensive data management for AI: The next-gen data management engine that will drive AI to new heights

CIO

The next phase of this transformation requires an intelligent data infrastructure that can bring AI closer to enterprise data. The challenges of integrating data with AI workflows When I speak with our customers, the challenges they talk about involve integrating their data and their enterprise AI workflows.

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Cloudera and AWS Partner to Deliver Cost-Efficient and Sustainable Infrastructure for AI and Analytics

Cloudera

As organizations adopt a cloud-first infrastructure strategy, they must weigh a number of factors to determine whether or not a workload belongs in the cloud. By optimizing energy consumption, companies can significantly reduce the cost of their infrastructure. Sustainable infrastructure is no longer optional–it’s essential.

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See clearly, spend wisely: The power of data platform observability

Xebia

Businesses can onboard these platforms quickly, connect to their existing data sources, and start analyzing data without needing a highly technical team or extensive infrastructure investments. This means no more paying for unused capacity or worrying about outgrowing a fixed-size infrastructure. The result?

Data 130
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See clearly, spend wisely: The power of data platform observability

Xebia

Businesses can onboard these platforms quickly, connect to their existing data sources, and start analyzing data without needing a highly technical team or extensive infrastructure investments. This means no more paying for unused capacity or worrying about outgrowing a fixed-size infrastructure. The result?

Data 130
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Fundamentals of Data Engineering

Xebia

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

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What is Data Engineering: Explaining Data Pipeline, Data Warehouse, and Data Engineer Role

Altexsoft

However, they often forget about the fundamental work – data literacy, collection, and infrastructure – that must be done prior to building intelligent data products. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

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The success of GenAI models lies in your data management strategy

CIO

The data preparation process should take place alongside a long-term strategy built around GenAI use cases, such as content creation, digital assistants, and code generation. Known as data engineering, this involves setting up a data lake or lakehouse, with their data integrated with GenAI models.

Strategy 215