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Data architecture strategy for data quality

IBM Big Data Hub

Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few. But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality.

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

CIO Business Intelligence

Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects. Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.

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Accelerating generative AI requires the right storage

CIO Business Intelligence

Before generative AI can be deployed, organizations must rethink, rearchitect and optimize their storage to effectively manage generative AI’s hefty data management requirements. Unstructured data needs for generative AI Generative AI architecture and storage solutions are a textbook case of “what got you here won’t get you there.”

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SAP unveils tools to help enterprises build their own gen AI apps

CIO Business Intelligence

It will be optimized for development in Java and JavaScript, although it’ll also interoperate with SAP’s proprietary ABAP cloud development model, and will use SAP’s Joule AI assistant as a coding copilot. Those initiatives will be made available to users of the new SAP Build Code, among other tools.

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What is a data engineer? An analytics role in high demand

CIO Business Intelligence

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

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Easing Data Woes and Creating Tangible Business Value Through Data Virtualization in the Financial Services Industry

Data Virtualization

Data is becoming increasingly important for understanding markets and customer behaviors, optimizing operations, deriving foresights, and gaining a competitive advantage. Over the last decade, the explosion of structured and unstructured data as well as digital technologies in general, has enabled.

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3 Key Factors Influencing Data Center Modernization

CDW Research Hub

For organizations trying to get a better handle on their data so they can see how it affects their business outcomes, the digital age has accelerated the need for modernizing the data centers. IT is constantly under immense pressure to improve, scale, consolidate, and optimize applications to meet the needs of their end-users.