Johnston / Shan / Goldwasser | SQL for Data Analytics. | E-Book | sack.de
E-Book

E-Book, Englisch, 540 Seiten

Johnston / Shan / Goldwasser SQL for Data Analytics.

Harness the power of SQL to extract insights from data
3. Auflage 2022
ISBN: 978-1-80181-780-6
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

Harness the power of SQL to extract insights from data

E-Book, Englisch, 540 Seiten

ISBN: 978-1-80181-780-6
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection



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Weitere Infos & Material


Table of Contents - Understanding and Describing Data
- The Basics of SQL for Analytics
- SQL for Data Preparation
- Aggregate Functions for Data Analysis
- Window Functions for Data Analysis
- Importing and Exporting Data
- Analytics Using Complex Data Types
- Performant SQL
- Using SQL to Uncover the Truth – a Case Study


Johnston Benjamin:
Benjamin Johnston is a senior data scientist for one of the world's leading data-driven MedTech companies and is involved in the development of innovative digital solutions throughout the entire product development pathway, from problem definition to solution research and development, through to final deployment. He is currently completing his Ph.D. in machine learning, specializing in image processing and deep convolutional neural networks. He has more than 10 years of experience in medical device design and development, working in a variety of technical roles, and holds first-class honors bachelor's degrees in both engineering and medical science from the University of Sydney, Australia.Shan Jun:
Jun Shan is an expert information technology professional who has been designing and implementing data management systems for more than 20 years. He also teaches SQL and Relational Database at Columbia University in the City of New York and Saint Peter's University. He completed his Master of Science in Computer Science from Virginia Tech and is currently a solution architect in a top 3 cloud computing service provider.Malik Upom:
Upom Malik is a data science and analytics leader who has worked in the technology industry for over 8 years. He has a master's degree in chemical engineering from Cornell University and a bachelor's degree in biochemistry from Duke University. As a data scientist, Upom has overseen efforts across machine learning, experimentation, and analytics at various companies across the United States. He uses SQL and other tools to solve interesting challenges in finance, energy, and consumer technology. Outside of work, he likes to read, hike the trails of the Northeastern United States, and savor ramen bowls from around the world.



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