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Mastering Tableau 2023: Implement advanced business intelligence techniques, analytics, and machine learning models with Tableau Paperback – 29
97% of respondents would recommend this to a friend
NGN 123171
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By the end of this book, you'll have mastered Tableau 2023 and be able to tackle common and advanced challenges in the BI domain.
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What Stands Out
Product Details
| Publisher | Packt Publishing |
| Publication date | 29 Aug. 2023 |
| Edition | 4th |
| Language | English |
| Print length | 684 pages |
| ISBN-10 | 1803233761 |
| ISBN-13 | 978-1803233765 |
| Item weight | 1.16 kg |
| Dimensions | 19.05 x 3.94 x 23.5 cm |
Who Should Buy?
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Business Analysts
Ideal for analysts seeking to enhance their data visualization and analytical skills using advanced Tableau techniques.
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Data Scientists
Useful for data scientists wanting to integrate machine learning models into their business intelligence workflows with Tableau.
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Decision Makers
Great for executives needing to understand advanced analytics for data-driven decision-making and strategic planning.
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Beginners
Not suitable for absolute beginners without prior knowledge of Tableau and data analysis concepts.
Product Description
Mastering Tableau 2023: Implement advanced business intelligence techniques, analytics, and machine learning models with Tableau Paperback – 29 Aug. 2023
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E-business Editorial Review
** Mastering Tableau 2023** "Mastering Tableau 2023" emerges as an essential guide for professionals across various levels of expertise seeking to harness the full potential of Tableau, the leading business intelligence tool. Authored by the seasoned Marleen Meier, this comprehensive fourth edition is skillfully crafted to elevate the understanding of both newcomers and seasoned users alike. Beginning with fundamental concepts such as dimensions, measures, and data quality Considerations, the book sets a strong foundation for readers. As it transitions into advanced features, readers are immersed in insights surrounding OData connectors, data densification, and Level of Detail (LOD) calculations. This meticulous structure allows users to incrementally build their skill set while also addressing complex challenges they may face in real-world scenarios. One of the book's standout contributions is its emphasis on practical, interactive examples—such as visualizing spatial data and understanding static vs. dynamic mapping. Users have shared experiences that resonate deeply, recalling transformative applications of knowledge gained from the book. Additionally, the mention of best practices for dashboard creation, data governance, and the integration of programming languages, such as R and Python, showcases how the text caters to the diverse ambitions of its audience. The author doesn't shy away from critical discussions around data privacy and governance, making it relevant in this era of stringent regulations. Readers are equipped with valuable tools like free datasets and advanced analytical techniques, fostering a hands-on learning environment that promotes active engagement with Tableau’s capabilities. Overall, "Mastering Tableau 2023" is not just a book; it’s a robust educational companion that encourages readers to explore and innovate within the expansive realm of data analytics. Whether for seasoned users looking to refine their skills or beginners aiming to understand the basics, this book serves as a vital resources poised to inspire a profound journey into the world of Tableau. **
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Pros
- Comprehensive coverage from basic to advanced Tableau functionalities.
- Practical examples and real-world applications.
- Emphasis on best practices in dashboard design and data governance.
- Addressing critical topics like data privacy and advanced analytics integration.
- Inclusion of free datasets for applied learning.
Cons
- May be less beneficial for individuals entirely new to data analytics without any familiarization with Tableau.
Product Price History
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NGN 123171
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Features & Benefits
- Master Tableau’s newest features for advanced business intelligence.
- Learn both pre-defined and self-created Machine Learning models.
- Implement data governance and ensure high data quality.
- Gain expertise in complex data handling and visualization techniques.
- Understand self-service analysis, time series, and geo-spatial analytics.
- Utilize Python and R integrations for enhanced functionality.
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