| Data Analytics for Absolute Beginners: A Deconstructed Guide to Data Literacy: (Introduction to Data, Data Visualization, Business Intelligence & Mach Contributor(s): Theobald, Oliver (Author) |
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ISBN: 1081762462 ISBN-13: 9781081762469 Publisher: Independently Published OUR PRICE: $14.11 Product Type: Paperback Published: July 2019 |
| Additional Information |
| BISAC Categories: - Education | Statistics - Computers | Databases - Data Mining |
| Physical Information: 0.37" H x 6" W x 9" (0.54 lbs) 160 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: Make better decisions with this easy deconstructed guide to data analytics. Want to add data analytics to your skill stack? Having trouble finding where to start? Cell by cell, bit by bit, this book teaches you the vocabulary, tools, and basic algorithms to think like a data scientist. Like assembling a complex Lego set, each chapter connects and adds individual blocks of knowledge to build your data literacy. This linear structure to unpacking data analytics takes you from zero to confidently analyzing and discussing data problems like a data scientist.Who is This Book For?This book is ideal for anyone interested in making sense of data analytics without the assumption that you understand data science terminology or advanced math. If you've tried to learn data analytics before and failed, this book is for you.A Practical ApproachThis book takes a hands-on approach to learning. This includes practical examples, visual examples, as well as two bonus coding exercises in Python, including free video content to walk you through both exercises. By the end of the book, you will have the practical knowledge to tackle real data problems in your organization or daily life.What You Will Learn From Reading This Book- How to recognize the common data types every data scientist needs to master- Where to store your data, including Big Data - New trends in data analytics, including what is Alternative Data and why not many people know about it- How to explain the distinction between Data Mining, Machine Learning, and Analytics to your colleagues- When and how to use Regression Analysis, Classification, Clustering, Association Analysis, and Natural Language Processing- How to make better business decisions using Data Visualization and Business Intelligence |