SQL for Data Analysis: Advanced Techniques for Transforming Data into Insights
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This practical book reveals new and hidden ways to improve your SQL skills, solve problems, and make the most of SQL as part of your workflow.
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What Stands Out
Детаљи о производу
| Publisher | O'Reilly Media |
| Publication date | 30 Sept. 2021 |
| Language | English |
| Print length | 357 pages |
| ISBN-10 | 1492088781 |
| ISBN-13 | 978-1492088783 |
| Item weight | 1.05 kg |
| Dimensions | 17.15 x 1.91 x 22.23 cm |
Who Should Buy?
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Data Analysts
Ideal for professionals seeking to enhance their SQL skills and perform advanced data analysis effectively.
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Business Intelligence
Suitable for individuals in BI roles needing to extract meaningful insights from complex data sets using SQL.
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Data Scientists
Perfect for data scientists looking to improve their data manipulation techniques and gain deeper analytical insights.
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Beginners
Not suitable for those with little or no experience in SQL as it covers advanced techniques.
OPIS PROIZVODA
SQL for Data Analysis: Advanced Techniques for Transforming Data into Insights
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Едиториал Ревиев
SQL For Data Analysis Advanced Techniques For Transforming Data Into Insights offers a comprehensive approach to mastering SQL, ideal for those looking to turn data into actionable insights. With its detailed explanations, relevant code examples, and clear elucidation of concepts like the execution order of SQL statements, the book serves as an essential resource for both beginners and seasoned users. Despite brief mentions of some quality issues with the print, readers appreciate the structured learning path and practical application of the content, making it a staple for revisiting SQL fundamentals.
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- Comprehensive coverage of SQL techniques
- Clear explanations with relevant code examples
- Effective for both beginners and advanced learners
- Helpful insights into execution order of SQL
- Regular reference for SQL fundamentals
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Карактеристике и предности
- Learn how to use both common and exotic SQL functions
- Combine SQL techniques to accomplish your goals faster
- Perform time series analysis using SQL's date and time manipulations
- Use cohort analysis to investigate how groups change over time
- Detect outliers in your data and replace them with alternate values
- Establish causality using experiment analysis, also known as A/B testing
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