Jose Antonio Ribeiro Neto

Summary Jose Antonio Ribeiro Neto

Welcome to the book "SUMMARY: Big Data for Executives and Market Professionals".
This Book is the first step for you to get to know and to become interested in Big Data.

It represents a content reorganization of the Second and Third Editions, providing a lighter reading, considering that:
- The texts was resized in a less technical language possible.
- The sections curiosities was removed, not useful anymore for the new summaries.
- There are new summaries sections implemented to review the contents.
- More technical chapters are available as an Appendix for optional reading.
- The kowledge was scrutured in a less technical way for quick learning.

The added value of this book SUMMARY is in saving time and learning of the contents with quick revisions.
As a bedside book, you can read the Summary Sections, reviewing concepts, for a broad view of the technology.

The book aims to summarize knowledge of Big Data. Concepts, technologies, applications, case studies. Data analysis, Insights, Machine Learning and practical actions to business results. Impact on society. Data careers.

Designed for executives and professionals who want information about this new area that is revolutionizing business, its products and services, changing markets and existing careers.

Businesses and professions become every day more "data-driven" (oriented data).
It will require a new culture of data of professionals, which should incorporate the data analysis as one of their professional skills. These are alerts for Executives and Professionals interested in understanding this new area.

That reading this summary can pique the interest of big data and serve as a guide for your personal and professional growth.

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