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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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Achieving Trusted AI in Manufacturing

Cloudera

As we navigate the fourth and fifth industrial revolution, AI technologies are catalyzing a paradigm shift in how products are designed, produced, and optimized. But with this data — along with some context about the business and process — manufacturers can leverage AI as a key building block to develop and enhance operations.

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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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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

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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.

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How Etihad taps data science to optimise airline operations

CIO Business Intelligence

Despite the worldwide chaos, UAE national airline Etihad has managed to generate productivity gains and cost savings from insights using data science. Our digital transformation has allowed us to be more streamlined, more agile, and more efficient. Etihad is on a digital transformation journey. A change was needed.