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The Future of the Data Lakehouse – Open

CIO Business Intelligence

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

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The Future of the Data Lakehouse – Open

Cloudera

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

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10 ways to accelerate digital transformation

CIO Business Intelligence

Understand that we might have to throw it away quickly, and that’s not a sunk cost,” Piddington says, adding that as a result CIOs need to get okay with more churn in the tech stack and truly embrace technology strategies centered around smaller investments and iterative builds rather than the big projects of yesteryear.

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The year’s top 10 enterprise AI trends — so far

CIO Business Intelligence

It doesn’t matter how accurate an AI model is, or how much benefit it’ll bring to a company if the intended users refuse to have anything to do with it. The world has flipped since 2022,” says David McCurdy, chief enterprise architect and CTO at Insight. Then gen AI came out.

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Your Data Architecture Holds the Key to Unlocking AI’s Full Potential

CIO Business Intelligence

In order to move AI forward, we need to first build and fortify the foundational layer: data architecture. This architecture is important because, to reap the full benefits of AI, it must be built to scale across an enterprise versus individual AI applications. Constructing the right data architecture cannot be bypassed.

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Build a transactional data lake using Apache Iceberg, AWS Glue, and cross-account data shares using AWS Lake Formation and Amazon Athena

AWS Big Data

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. Furthermore, making the data available in the data lake in near-real time often leads to the data being fragmented over many small files, resulting in poor query performance and compaction maintenance.

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How Mapfre gets cloud to coexist with its tech model ambitions

CIO Business Intelligence

Over the years we’ve been working with business intelligence (BI) tools, and then incorporating other big data solutions outside of traditional BI, and, later, adopting advanced analytics. So in the data part, we’ve grown with technologies that weren’t convergent. What’s the reasoning behind that?