Remove Analytics Remove Contextual Data Remove Data Lake Remove Enterprise
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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. Contextual data understanding Data systems often cause major problems in manufacturing firms. IBM built a workforce advisor that uses summarization and contextual data understanding with intent detection and multi-modal interaction.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Five benefits of a data catalog

IBM Big Data Hub

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

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Identity and Access Management: The Pursuit of Invisible Value

CIO Business Intelligence

IAM can enable enterprise transformation projects through automation that enables quicker access. It allows for movement of workloads into the cloud seamlessly and enables companies to externalize applications that are on-premises. – Protecting data from hackers is the critical task of CDOs. IAM brings value .

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OCBC Bank Accelerates Its Data Strategy with Cloudera 

Cloudera

Real-time data analysis for better business and customer solutions. Andrea Pisoni, Head of Data Science says “OCBC worked with Cloudera to design and secure big data platforms as part of its comprehensive data project. The partnership has enabled OCBC to better store, manage and harness the power of our data.”.

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Why Icon Ventures Invested in Alation

Alation

It’s a truism that data is the most important asset in the 21 st century economy. But, today too many enterprises exist in a data fog, with poorly contextualized data scattered across millions of tables. Dispelling this data fog is one of the key challenges for the next generation enterprise.

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Constructing A Digital Transformation Strategy: Putting the Data in Digital Transformation

erwin

Part Two of the Digital Transformation Journey … In our last blog on driving digital transformation , we explored how enterprise architecture (EA) and business process (BP) modeling are pivotal factors in a viable digital transformation strategy. The solution is data intelligence.