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Are Data Silos Undermining Digital Transformation?

BI-Survey

Thus, alternative data architecture concepts have emerged, such as the data lake and the data lakehouse. Which data architecture is right for the data-driven enterprise remains a subject of ongoing debate. Data black holes: the high cost of supposed flexibility. Data Black Holes.

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Deriving Value from Data Lakes with AI

Sisense

AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. Once your data is prepared for analysis, the next question is: how else can AI help you? It’s also a better way to monetize your data in the short term. It’s the future.

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A data strategy checklist for the journey to the data-driven enterprise

BI-Survey

Managers see data as relevant in the context of digitalization, but often think of data-related problems as minor details that have little strategic importance. Thus, it is taken for granted that companies should have a data strategy. But what is the scope of an effective strategy and who is affected by it?

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Achieving Trusted AI in Manufacturing

Cloudera

According to Gartner , 80 percent of manufacturing CEOs are increasing investments in digital technologies—led by artificial intelligence (AI), Internet of Things (IoT), data, and analytics. Yet Gartner reports that only eight percent of industrial organizations say their digital transformation initiatives are successful.

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Why Can’t we Advance Healthcare and Life Sciences this Fast all the time?

Cloudera

While challenges exist in data interoperability, privacy controls, ongoing compliance initiatives, etc, the industry has proven speed is possible despite these obstacles. . The usage of data lakes and automation are helping facilitate the data sharing and collaboration across the healthcare ecosystem.

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What is a data architect? Skills, salaries, and how to become a data framework master

CIO Business Intelligence

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. They often report to data infrastructure and data science leads.

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Data Champions: Balancing IT and Business Needs

Cloudera

Digital transformation has been on the agenda for a long time, but the sudden need to respond to the unprecedented challenges of 2020, has meant the buzzword has become an executable reality for many enterprises. Underlying digital transformation and investment decisions is a precious asset: data.

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