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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.

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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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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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A Look Back at the Gartner Data and Analytics Summit

Cloudera

All of that technology, though, depends on data to be successful. In those discussions, it was clear that everyone understood the need to treat data estates more cohesively as a whole—that means bringing more attention to security, data governance, and metadata management, the latter of which has become increasingly popular.

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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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Overcome these six data consumption challenges for a more data-driven enterprise

IBM Big Data Hub

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. Here are a few common data management challenges: Regulatory compliance on data use. Data quality. Data silos.

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Top 10 Metadata Management Influencers, Sites, and Blogs You Must Follow in 2021

Octopai

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story.