Wiley India Pvt Ltd
|Number of Pages
Data Science & Big Data Analytics educates readers about what Big Data is and how to extract value from it. The book covers methods and technologies required to analyze structured and unstructured datasets, as more individuals and organizations build out their capabilities to analyze Big Data and draw insights from it. Additional focus areas include machine learning, data visualization and presentation skills.
The book provides practical foundation level training that enables immediate and effective participation in big data and other analytics projects. It provides grounding in basic and advanced analytic methods and an introduction to big data analytics technology and tools, including MapReduce and Hadoop. The book takes an "Open", or technology-neutral approach applying the concepts taught in the context of the Data Analytics Lifecycle. Readers will learn how to take steps toward developing data science skills that they can use to draw insights from Big Data and other common datasets. Upon completing this book, readers will have knowledge about processes, tools and methods for Big Data Analytics projects within their organizations. The book covers
Introduction to Big Data Analytics
Data Analytics Lifecycle
Review of Basic Data Analytic Methods Using R
Advanced Analytical Theory and Methods
Advanced Analytics Technology and Tools
The Endgame, or Putting it All Together Get Certified EMC Proven Professional Data Science Associate (EMCDSA) E20-007.
Wiley & EMC have come together to provide 90% discount on the exam for the students affiliated to the EMC Academic Alliance / any higher education institute in India. Along with this book you will receive a unique exam coupon (An authentication code) in the form of a scratch card which is mandatory to initiate the process of getting the discount on the exam. Do not share it with anyone as it can be used only once. Terms & conditions apply, for details see inside the book.
Exam overview this exam focuses on the practice of data analytics, the role of the data scientist, the main phases of the data analytics lifecycle, analyzing and exploring data with R, statistics for model building and evaluation, the theory and methods of advanced analytics and statistical modeling, the technology and tools that can be used for advanced analytics, operationalizing an analytics project and data visualization techniques. Successful candidates will achieve the EMC Proven Professional - Data science Associate credential.