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Extending Power BI with Python and R: Perform advanced analysis using the power of analytical languages
85% of respondents would recommend this to a friend
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Product Details
| Publisher | Packt Publishing |
| Publication date | March 29, 2024 |
| Edition | 2nd ed. |
| Language | English |
| Print length | 814 pages |
| ISBN-10 | 1837639531 |
| ISBN-13 | 978-1837639533 |
| Item Weight | 3.02 pounds (1.37 kg) |
| Dimensions | 7.5 x 1.84 x 9.25 inches (19.1 x 4.7 x 23.5 cm) |
Product Description
Extending Power BI with Python and R: Perform advanced analysis using the power of analytical languages
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Data Processing Editorial Review
The editorial review of "Extending Power BI with Python and R: Perform advanced analysis using the power of analytical languages, 2nd Edition" reveals overwhelmingly positive feedback from users who are both beginners and seasoned professionals within the data analysis community. This updated edition effectively caters to its target audience of business analysts and data scientists looking to harness the capabilities of Python and R within Power BI. Readers appreciate the book’s in-depth exploration of optimizing the integration of Python and R, emphasizing practical techniques that facilitate advanced data analysis. Users have noted the book's comprehensive coverage of key topics, such as managing large datasets, utilizing the Intel Math Kernel Library for improved performance, and effectively tackling integration challenges within Power BI. The arguments presented throughout the text encourage analysts to push beyond traditional limitations, turning Power BI into a versatile analytical hub. Moreover, the author's straightforward writing style, enriched with visuals, screenshots, and sample code, enhances the learning experience, making complex principles more digestible. The inclusion of quizzes at the end of each chapter is highly praised as a feature that allows readers to reinforce their learning. Overall, the book is not only seen as a vital resource for technical advancement and practical analytics but also as an essential guide for leveraging existing Power BI functionalities. Users with prior knowledge of Power BI found the second edition significantly impressive, claiming it expanded their analytical capabilities Considerably. **
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Pros
- Practical guidance on optimizing R and Python in Power BI
- Covers advanced techniques like fuzzy matching and SQL Server external languages
- Highly instructive for managing large datasets efficiently
- Includes quizzes for self-assessment at the end of each chapter
- Clear explanations complemented by visuals and sample code
- New content expands on practical applications and problem-solving
Cons
- May be challenging for complete beginners unfamiliar with Power BI or programming languages
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