Data Modeling Essentials : A Comprehensive Guide to Data Analysis
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Data Modeling Made Simple with PowerDesigner (Take It With You) – VERY GOOD Product Id:0977140091 Condition:USED_VERY_GOOD Notes:Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc…
Title: Data Modeling for MongoDB: Building Well-Designed and Supportabl Item Condition: used item in a very good condition. Book Details.
Notes: Item in good condition.
Condition Notes: Gently read. Binding tight; spine straight and smooth, with no creasing; covers clean and crisp. Minimal signs of handling or shelving.
You are purchasing a Very Good copy of ‘Data Modeling Essentials, Third Edition’. Condition Notes: Book is in very good condition and may include minimal underlining highlighting.
“Designing Data-Intensive Applications: The Big Ideas Behind Reliable PB” by Martin Kleppmann is a textbook published by O’Reilly Media in 2017. It focuses on data modeling and design, as well as desktop applications and databases. The book is a trade paperback with dimensions of 9.2 inches in length, 6.9 inches in width, and 1.5 inches in height. It weighs 36.3 ounces and is written in English. The author presents big ideas and concepts related to designing reliable and data-intensive applications, making it a valuable resource for those interested in the subject area of computers and data management.
Data Modeling Essentials, Third Edition. Sku: 0126445516-4-36879385. Condition: Used: Acceptable. Qty Available: 1.
“Designing Data-Intensive Applications: The Big Ideas Behind Reliable PB” is a textbook written by Martin Kleppmann and published by O’Reilly Media, Incorporated in 2017. The book covers subjects such as data modeling and design, as well as desktop applications and databases. It is a trade paperback format, written in English, and has dimensions of 9.2 inches in length, 6.9 inches in width, and 1.5 inches in height, with a weight of 36.3 ounces. This book is a valuable resource for those interested in designing and building reliable data-intensive applications.