Install data analytics into your brain with this comprehensive introduction
Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place. Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling. Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one. You'll learn all about sources of data like data lakes, and you'll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau. You'll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level. With this Dummies guide, you'll be well on your way to becoming a priceless data jockey.
- Mine data from data sources
- Organize and analyze data
- Use data to tell a story with Tableau
- Expand your know-how with Python and R
New and novice data analysts will love this All-in-One reference on how to make sense of data. Get ready to watch as your career in data takes off.
Unravel mysteries and tell stories with data
The world of data analytics requires having a grasp of statistics, visualization tools, business intelligence, and coding. For aspiring data analysts, it's a lot to figure out on the fly. This book provides a trusty guide for getting a handle on the fundamentals of data. Discover how to dig data out of storage, how to extrapolate insight from it, and how to turn that insight into a story that inspires others. It's all in a day's work for a data analyst.
6 Mini-Books Inside? - Learning Data Analytics & Visualization Foundations
- Using Power BI for Data Analytics & Visualization
- Using Tableau for Data Analytics & Visualization
- Extracting Information with SQL
- Performing Statistical Data Analysis & Visualization with R Programming
- Applying Python Programming to Data Science
