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- SQL Pocket Guide: A Guide to SQL Usage
SQL Pocket Guide: A Guide to SQL Usage
86% of respondents would recommend this to a friend
€ 29
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If you use SQL in your day-to-day work as a data analyst, data scientist, or data engineer, this popular pocket guide is your ideal on-the-job reference.
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What Stands Out
Toote üksikasjad
| Publisher | O'Reilly Media |
| Publication date | October 5, 2021 |
| Edition | 4th |
| Language | English |
| Print length | 354 pages |
| ISBN-10 | 1492090409 |
| ISBN-13 | 978-1492090403 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 4.25 x 0.75 x 7 inches (10.8 x 1.9 x 17.8 cm) |
Who Should Buy?
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Beginner SQL Users
Ideal for new users who need a concise introduction to SQL concepts and fundamental commands.
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Database Administrators
Helpful for professionals needing a quick reference for SQL syntax and best practices while managing databases.
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Students and Learners
Great for students studying database management or related courses, offering clear examples and explanations of SQL.
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Advanced SQL Developers
Not suitable for experienced developers seeking in-depth discussions or advanced topics beyond basic SQL syntax.
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SQL Pocket Guide: A Guide to SQL Usage
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Data Modeling & Design Editorial Review
The SQL Pocket Guide, 4th Edition is a comprehensive guide for SQL usage. It is well written and covers a variety of topics which makes it a great resource for aspiring data scientists. The concise and practical code snippets provide a good refresher for professionals using SQL for more than 20 years. The book is an excellent example of how to work hard to make something short with no filler material. The only drawback is that there is no way to practice the code.
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Plussid
- Comprehensive guide for SQL usage
- Concise and practical code snippets
- Well written and covers a variety of topics
- Good refresher for professionals using SQL for more than 20 years
- No filler material
Miinused
- No way to practice the code.
Product Price History
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€ 29
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Omadused ja eelised
- Ideal on-the-job reference for data analysts, data scientists, and data engineers using SQL
- Addresses complexities of SQL and key aspects of SQL in various database management systems
- Includes examples on data types, regular expressions, window functions, pivoting, unpivoting, and more
- Details on performing specific tasks using SQL and updating queries for different database systems
- New sections on connecting Python and R to a relational database and FAQs
- Provides quick syntax examples applicable to real queries
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