Data Architecture: A Primer for the Data Scientist: A Primer for the Data Scientist
Inmon, W.H.; Linstedt, Daniel; Levins, Mary
Language: English
Published by Academic Press, 2019
- Softcover
- Used

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- Title
- Data Architecture: A Primer for the Data Scientist: A Primer for the Data Scientist
- Author
- Inmon, W.H.; Linstedt, Daniel; Levins, Mary
- Publisher
- Academic Press
- Publication year
- 2019
- Condition
- very_good
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 0128169168
- ISBN 13
- 9780128169162
- Edition
- 2nd Edition
Over the past 5 years, the concept of big data has matured, data science has grown exponentially, and data architecture has become a standard part of organizational decision-making. Throughout all this change, the basic principles that shape the architecture of data have remained the same. There remains a need for people to take a look at the "bigger picture" and to understand where their data fit into the grand scheme of things.
Data Architecture: A Primer for the Data Scientist, Second Edition addresses the larger architectural picture of how big data fits within the existing information infrastructure or data warehousing systems. This is an essential topic not only for data scientists, analysts, and managers but also for researchers and engineers who increasingly need to deal with large and complex sets of data. Until data are gathered and can be placed into an existing framework or architecture, they cannot be used to their full potential. Drawing upon years of practical experience and using numerous examples and case studies from across various industries, the authors seek to explain this larger picture into which big data fits, giving data scientists the necessary context for how pieces of the puzzle should fit together.
- New case studies include expanded coverage of textual management and analytics
- New chapters on visualization and big data
- Discussion of new visualizations of the end-state architecture
"Synopsis" may belong to another edition of this title.
About the Author
Dan Linstedt has more than 25 years of experience in the Data Warehousing and Business Intelligence field and is internationally known for inventing the Data Vault 1.0 model and the Data Vault 2.0 System of Business Intelligence. He helps business and government organizations around the world to achieve BI excellence by applying his proven knowledge in Big Data, unstructured information management, agile methodologies and product development. He has held training classes and presented at TDWI, Teradata Partners, DAMA, Informatica, Oracle user groups and Data Modeling Zone conference. He has a background in SEI/CMMI Level 5, and has contributed architecture efforts to petabyte scale data warehouses and offers high quality on-line training and consulting services for Data Vault.
Mary Levins is recognized as a leader in Data Governance with over 20 years of experience working with organizations to bring value through data strategies that drive business results. Mary has a BS and MS in Industrial Engineering, and her experience spans across many different industries including manufacturing, healthcare, energy/utilities, automotive, electronics, and financial (including Consumer Credit Bureaus and Credit Unions). Today, Mary is the founder of Sierra Creek Consulting, a specialized firm delivering Data Governance, Data Management, and Data Solutions to help companies bring value through data.
"About the title" may belong to another edition of this title.
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