Reading/References
Data Analytics Made Accessible, A. Maheshwari
If you’ve just started to learn about data, or if you’re not quite sure how it works— this book offers a wealth of information. Data Analytics Made Accessible breaks down data analysis into an easy to follow, digestible format. By offering real-world examples (instead of complex hypothetical situations), readers at any skill level will be able to pick up this data analytics book and follow along to learn the basics. This resource is so well-received that several universities have included it in the required reading for many analytics courses.
Too Big To Ignore: The Business Case for Big Data, P. Simon
Whether you’re skeptical about or intrigued by business uses for big data, this is the go - to big data book. The author does an incredible job of examining and laying out how businesses and even local governments are using big data to their advantage. With several case studies and quotes from big data professionals all over the world, Too Big To Ignore: The Business Case for Big Data is a must-read for anyone entering the field. Readers will gain valuable insight on turning data into intelligence, and intelligence into something actionable.
Developing Analytic Talent: Becoming a Data Scientist, V. Granville
By reading this book, you will learn how to develop detailed analytics that can help you meet business goals. The author explores the more intricate aspects of data science, the required skills and how to acquire them. You will be able to explore the skills that employers are looking for and understand how the growing demand for big data has furthered the demand for data professionals. This in-depth book includes job interview questions, sample resumes, salary surveys and examples of job postings. Readers can also explore case studies that explain how data science is utilized on Wall Street, in botnet detection, in digital advertising and more.
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