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Hands-On Big Data Modeling. Effective database design techniques for data architects and business intelligence professionals James Lee, Tao Wei, Suresh Kumar Mukhiya

(ebook) (audiobook) (audiobook) Książka w języku 1
Hands-On Big Data Modeling. Effective database design techniques for data architects and business intelligence professionals James Lee, Tao Wei, Suresh Kumar Mukhiya - okladka książki

Hands-On Big Data Modeling. Effective database design techniques for data architects and business intelligence professionals James Lee, Tao Wei, Suresh Kumar Mukhiya - okladka książki

Hands-On Big Data Modeling. Effective database design techniques for data architects and business intelligence professionals James Lee, Tao Wei, Suresh Kumar Mukhiya - audiobook MP3

Hands-On Big Data Modeling. Effective database design techniques for data architects and business intelligence professionals James Lee, Tao Wei, Suresh Kumar Mukhiya - audiobook CD

Autorzy:
James Lee, Tao Wei, Suresh Kumar Mukhiya
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
306
Dostępne formaty:
     PDF
     ePub
     Mobi
Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements.
To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets.
By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently.

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O autorach książki

James Lee is a passionate software wizard working at one of the top Silicon Valley-based start-ups specializing in big data analysis. He has also worked at Google and Amazon. In his day job, he works with big data technologies, including Cassandra and Elasticsearch, and is an absolute Docker geek and IntelliJ IDEA lover. Apart from his career as a software engineer, he is keen on sharing his knowledge with others and guiding them, especially in relation to start-ups and programming. He has been teaching courses and conducting workshops on Java programming / IntelliJ IDEA since he was 21. James also enjoys skiing and swimming, and is a passionate traveler.
Tao Wei is a passionate software engineer who works in a leading Silicon Valley-based big data analysis company. Previously, Tao worked in big IT companies, including IBM and Cisco. He has intensive experience in designing and building distributed, large-scale systems with proven high availability and reliability. Tao has an MS degree in computer science from McGill University and many years' experience as a teaching assistant in a variety of computer science classes. In his spare time, he enjoys reading and swimming, and is a passionate photographer.
Suresh Kumar Mukhiya is a PhD candidate, currently affiliated to the Western Norway University of Applied Sciences (HVL). He is a big data enthusiast, specializing in Information Systems, Model-Driven Software Engineering, Big Data Analysis, Artificial Intelligence and Frontend development. He has completed a Masters in Information Systems from the Norwegian University of Science and Technology (NTNU, Norway) along with a thesis in processing mining. He also holds a bachelor's degree in computer science and information technology (BSc.CSIT) from Tribhuvan University, Nepal, where he was decorated with the Vice-Chancellor's Award for obtaining the highest score. He is a passionate photographer and a resilient traveler.

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