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Building a Data Strategy for Defence Partners

Alation

Data gathering and use pervades almost every business function these days — and it’s widely acknowledged that businesses with a clear strategy around data are best placed to succeed in competitive, challenging markets such as defence. What is a data strategy? Why is a data strategy important?

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5 recommendations to get your data strategy right

IBM Big Data Hub

The rise of data strategy. There’s a renewed interest in reflecting on what can and should be done with data, how to accomplish those goals and how to check for data strategy alignment with business objectives. The evolution of a multi-everything landscape, and what that means for data strategy.

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Data Strategies for Getting Greater Business Value from Distributed Data

Data Virtualization

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

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Prioritizing Data: Why a Solid Data Management Strategy Will Be Critical in 2024

Ontotext

In 2023, data leaders and enthusiasts were enamored of — and often distracted by — initiatives such as generative AI and cloud migration. Although corporate pressures may prompt organizations to “do something with AI,” being data-driven must come first and remain top priority.

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A Look Back at the Gartner Data and Analytics Summit

Cloudera

With the arrival of the latest AI-powered technologies like large language models (LLMs) and generative AI (GenAI), there’s a vast amount of opportunities for innovation, growth, and improved business outcomes right around the corner. All of that technology, though, depends on data to be successful.

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What Is Data Modeling? Data Modeling Best Practices for Data-Driven Organizations

erwin

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

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Metadata-Driven Data Warehouses are Ideal

TDAN

A metadata-driven data warehouse (MDW) offers a modern approach that is designed to make EDW development much more simplified and faster. It makes use of metadata (data about your data) as its foundation and combines data modeling and ETL functionalities to build data warehouses.