Big Data is a technology "Moonshot," those that arise and change people's lives and their professional careers.
This eBook is organized to summarize Big Data, Data Science, Analytics and Machine Learning, structuring knowledge, less technical, for a better understanding and rapid learning, demystifying and guiding Executives and Market Professionals on how to use Big Data on their favor, for greater professional success.
It is the first stage to become interested in Big Data.
Check the learning summary you take on this journey.

- Introduction to Big Data and Data Science. Main Technologies applied to Big Data. Cloud technologies, systems, hardware, and software.

- Hadoop Ecosystem and its importance to Big Data. The parallel programming paradigm of MapReduce to solve problems in Big Data. Data Lake, Data Warehouse, and the ETL processes for Big Data.

- Analytics Science and its derivations for Predictive and Big Data. The Analytics Tools and their Big Data applications. Machine Learning (ML) and its relationship with Big Data. ML Applications for Big Data. Data Visualization introduction.

- Professional careers in Big Data. Companies that created Big Data and adopted the technology. Big Data applications for social networks and the Internet of things.

- Privacy and Governance in Big Data. Big Data and Data Science Influencers. How to become a Data Scientist.

- Big Data for Professionals. Big Data for Market Professionals. Summary and general conclusions about the Big Data era. Its implications for business and professional life.

What goes on in this Third Edition?

We looked at the content and texts for readability.

And included new information into the chapters to update the content.

A new Summary section for each Chapter was included.

Beyond, the new sections included are:

Chapter 3 - Section 2 - Data is Files

Chapter 7 - Section 5 - Success Story - Tesla

Chapter 8 - Section 2 - GDPR and LGPD Privacy

Chapter 10 - Section 6 - Edge Computing

Chapter 10 - Section 7 - Digital Transformation

Chapter 11 - Section 10 - The Importance of Spark

Chapter 16 - Section 7 - Big Data + Data Science + ML

Chapter 18 - Section 4 - Analytics Translator

Chapter 18 - Section 5 - Is it worth going for a new career