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Data Analytics for Absolute Beginners: A Deconstructed Guide to Data Literacy: (Introduction to Data, Data Visualization, Business Intelligence & ...
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Make better decisions with this deconstructed guide to data analytics
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What Stands Out
Rincian Produk
| Publisher | Independently published |
| Publication date | July 21, 2019 |
| Language | English |
| Print length | 149 pages |
| ISBN-10 | 1081762462 |
| ISBN-13 | 978-1081762469 |
| Item Weight | 7.4 ounces (209.79 grams) |
| Dimensions | 6 x 0.38 x 9 inches (15.2 x 1 x 22.9 cm) |
| Book 1 of 2 | Learn Data Analytics & Data Storytelling for Beginners |
Who Should Buy?
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Complete Beginners
Individuals with no prior knowledge of data analytics seeking foundational understanding in data literacy and visualization.
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Small Business Owners
Entrepreneurs needing insights into data to make informed decisions and enhance their business performance effectively.
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Students and Learners
College students or those in online courses wanting to develop basic data skills and competencies for future job opportunities.
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Advanced Analysts
Professionals with expertise in data analytics may find this content overly simplistic and lacking in depth.
DESKRIPSI PRODUK
Data Analytics for Absolute Beginners: A Deconstructed Guide to Data Literacy: (Introduction to Data, Data Visualization, Business Intelligence & ... Analytics & Data Storytelling for Beginners)
About This Item
Are you interested in learning data analytics but don't know where to start? Look no further than "Data Analytics for Absolute Beginners: A Deconstructed Guide to Data Literacy." This comprehensive guide is designed specifically for beginners who want to dive into the world of data analytics. With this book, you'll gain a solid foundation in data literacy, allowing you to understand and interpret data in a meaningful way. Whether you're an e-commerce professional looking to enhance your data analytics skills or an absolute beginner with no prior knowledge, this book is perfect for you. The book covers a wide range of topics, including an introduction to data, data visualization techniques, business intelligence, and more. You'll also learn the basics of Python programming and statistics, which are essential skills for anyone in the data analytics field. One of the highlights of this book is its focus on e-commerce data analytics.
It delves into the specific challenges and strategies unique to the e-commerce industry, providing practical insights and real-world examples. Whether you're looking to drive growth, make data-driven decisions, or improve your overall understanding of e-commerce data, this book has you covered. Additionally, this guide emphasizes the importance of data visualization in e-commerce. You'll learn effective visualization techniques and discover the best tools available to help you make sense of complex data sets.
By mastering data visualization, you'll be able to communicate insights and trends in a visually compelling manner, making it easier for decision-makers to understand and act upon the information. To further enhance your learning experience, this book provides resources for e-commerce data literacy, including platforms, courses, and workshops. You'll have access to practical training materials and additional learning opportunities to help you sharpen your skills and stay updated on the latest trends in e-commerce data analytics. Start your journey into the world of data analytics with "Data Analytics for Absolute Beginners: A Deconstructed Guide to Data Literacy." Whether you're an e-commerce professional or someone looking to break into the field, this book will provide you with the foundation and knowledge you need to succeed. Order your paperback copy today and begin your data analytics journey!.
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Fitur & Manfaat
- Ideal for beginners in data analytics
- Hands-on approach to learning
- Practical examples and visual examples
- Includes two bonus coding exercises in Python
- Learn common data types and trends in data analytics
- Gain knowledge in Regression Analysis, Classification, Clustering, Association Analysis, and Natural Language Processing
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