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Item #:
22414139
Introduction to Data Visualization & Storytelling: A Guide For The Data Scientist (Visual Thinking)
89% of respondents would recommend this to a friend
Item #:
22414139
GHS 282
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What Stands Out
Comprehensive Guidance
This guide offers a thorough exploration of data visualization techniques and storytelling principles, tailored specifically for data scientists, enhancing their ability to communicate insights effectively.
Practical Techniques
Includes actionable steps and real-world examples, allowing readers to translate complex data into compelling visuals and narratives, bridging the gap between data analytics and audience engagement.
Enhanced Skills
By focusing on visual thinking, this book empowers data scientists to improve their analytical storytelling skills, making data-driven insights more accessible and impactful for all stakeholders.
Product Details
| Publisher | Independently published |
| Publication date | July 28, 2019 |
| Language | English |
| Print length | 173 pages |
| ISBN-10 | 1085827836 |
| ISBN-13 | 978-1085827836 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 5 x 0.39 x 8 inches (12.7 x 1 x 20.3 cm) |
| Part of series | Visual Thinking |
Who Should Buy?
-
Aspiring Data Scientists
Perfect for beginners looking to understand data visualization principles and storytelling in data analysis effectively.
-
Business Analysts
Helps analysts improve their data presentation skills, enhancing insights and decision-making through effective visualization.
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Educators & Trainers
Great resource for educators teaching data visualization concepts, providing clear examples and frameworks to engage students.
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Advanced Data Professionals
Experienced data scientists may find the content too basic and not challenging enough for their skill level.
Product Description
Introduction to Data Visualization & Storytelling: A Guide For The Data Scientist (Visual Thinking)
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Information Management Editorial Review
Introduction to Data Visualization & Storytelling: A Guide For The Data Scientist (Visual Thinking) offers a concise yet engaging approach to mastering data visualization. Readers have highlighted the book's ability to oversimplify complex concepts and transform them into actionable insights, making it ideal for beginners in data science. The integration of visual pop culture references adds a unique flavor, although some felt that certain sections could benefit from more depth. Additionally, the inclusion of an email contact for accessing instructional materials enhances its utility as a learning resource. Overall, this book is a solid pick for anyone looking to elevate their data visualization skills.
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Pros
- Concise and engaging writing style
- Accessible for beginners in data science
- Useful visual pop culture references
- Great for developing compelling visuals
- Includes supplemental materials for readers
Cons
- Some readers desire more depth on complex topics
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