Enterprise Data Architecture
May 11, 2024
6 minute read
Enterprise Data Architecture (EDA) is a high-level plan that describes how an organization's data assets are used and managed. It provides a roadmap for how data will be used to achieve the organization's business goals. EDA is important because it helps organizations make better use of their data, which can lead to improved decision-making, increased efficiency, and reduced costs.
Why Learn Enterprise Data Architecture?
There are many reasons why you might want to learn about EDA. Some common reasons include:
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Find a path to becoming a Enterprise Data Architecture. Learn more at:
OpenCourser.com/topic/8rx6fi/enterprise
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Enterprise Data Architecture.
Provides a practical guide to designing and implementing data architectures for organizations of all sizes. It covers a wide range of topics, including data modeling, data integration, and data governance.
Provides a comprehensive overview of enterprise data management (EDM), covering the key concepts, principles, and best practices involved in managing data as a strategic asset.
Comprehensive guide to dimensional modeling, a data modeling technique that is widely used in data warehouses and business intelligence systems.
Provides a comprehensive guide to data management, covering a wide range of topics, including data architecture, data governance, and data quality.
Provides a comprehensive overview of database security, covering a wide range of topics, including data encryption, access control, and intrusion detection.
Provides a comprehensive overview of data science, covering a wide range of topics, including data mining, machine learning, and data visualization.
Provides a comprehensive overview of big data analytics, covering a wide range of topics, including data management, data analysis, and data visualization.
Provides a comprehensive overview of Hadoop, a popular open-source framework for distributed computing. It covers a wide range of topics, including data storage, data processing, and data analysis.
Provides a comprehensive overview of machine learning, a subfield of artificial intelligence that gives computers the ability to learn without being explicitly programmed.
Provides a comprehensive overview of deep learning, a subfield of machine learning that uses artificial neural networks to learn from data.
Provides a comprehensive overview of artificial intelligence, covering a wide range of topics, including machine learning, natural language processing, and computer vision.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/8rx6fi/enterprise
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