Data Analytics: Practical Guide to Leveraging the Power of Algorithms, Data Science, Data Mining, Statistics, Big Data, and Predictive Analysis to Improve Business, Work, and Life

Data Analytics: Practical Guide to Leveraging the Power of Algorithms, Data Science, Data Mining, Statistics, Big Data, and Predictive Analysis to Improve Business, Work, and Life

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Synopsis

The Ultimate Guide to Data Science and Analytics


This practical guide is accessible for the reader who is relatively new to the field of data analytics, while still remaining robust and detailed enough to function as a helpful guide to those already experienced in the field. Data science is expanding in breadth and growing rapidly in importance as technology rapidly integrates ever deeper into business and our daily lives. The need for a succinct and informal guide to this important field has never been greater.


RIGHT NOW you can get ahead of the pack!


This coherent guide covers everything you need to know on the subject of data science, with numerous concrete examples, and invites the reader to dive further into this exciting field. Students from a variety of academic backgrounds, including computer science, business, engineering, statistics, anyone interested in discovering new ideas and insights derived from data can use this as a textbook. At the same time, professionals such as managers, executives, professors, analysts, doctors, developers, computer scientists, accountants, and others can use this book to make a quantum leap in their knowledge of big data in a matter of only a few hours. Learn how to understand this field and uncover actionable insights from data through analytics.


UNDERSTAND the following key insights when you grab your copy today:



  • WHY DATA IS IMPORTANT TO YOUR BUSINESS

  • DATA SOURCES

  • HOW DATA CAN IMPROVE YOUR BUSINESS

  • HOW BIG DATA CREATES VALUE

  • DEVELOPMENT OF BIG DATA

  • CONSIDERING THE PROS AND CONS OF BIG DATA

  • BIG DATA FOR SMALL BUSINESSES

  • THE COST EFFECTIVENESS OF DATA ANALYTICS

  • WHAT TO CONSIDER WHEN PREPARING FOR A NEW BIG DATA SOLUTION

  • DATA GATHERING

  • DATA SCRUBBING

  • DESCRIPTIVE ANALYTICS

  • INFERENTIAL STATISTICS

  • PREDICTIVE ANALYTICS

  • PREDICTIVE MODELS

  • DESCRIPTIVE MODELING

  • DECISION MODELING

  • PREDICTIVE ANALYSIS METHODS

  • MACHINE LEARNING TECHNIQUES

  • DATA ANALYSIS WITH "R"

  • ANALYTICAL CUSTOMER RELATIONSHIP MANAGEMENT (CRM)

  • THE USE OF PREDICTIVE ANALYTICS IN HEALTHCARE

  • THE USE OF PREDICTIVE ANALYTICS IN THE FINANCIAL SECTOR

  • PREDICTIVE ANALYTICS & BUSINESS

  • MARKETING STRATEGIES

  • FRAUD DETECTION

  • SHIPPING BUSINESS

  • CONTROLLING RISK FACTORS

  • THE REVOLUTION OF PREDICTIVE ANALYSIS ACROSS A VARIETY OF INDUSTRIES

  • DESCRIPTIVE AND PREDICTIVE ANALYSIS

  • CRUCIAL FACTORS FOR DATA ANALYSIS

  • RESOURCES AND FLEXIBLE TECHNICAL STRUCTURE

  • BUSINESS INTELLIGENCE

  • HYPER TARGETING

  • WHAT IS DATA SCIENCE?

  • DATA MUNGING

  • DEMYSTIFYING DATA SCIENCE

  • SECURITY RISKS TODAY

  • BIG DATA AND IMPACTS ON EVERYDAY LIFE

  • FINANCE AND BIG DATA

  • APPLYING SENTIMENT ANALYSIS

  • RISK EVALUATION AND THE DATA SCIENTIST

  • THE FINANCE INDUSTRY AND REAL-TIME ANALYTICS

  • HOW BIG DATA IS BENEFICIAL TO THE CUSTOMER

  • CUSTOMER SEGMENTATION IS GOOD FOR BUSINESS

  • USE OF BIG DATA BENEFITS IN MARKETING

  • GOOGLE TRENDS

  • THE PROFILE OF A PERFECT CUSTOMER

  • LEAD SCORING IN PREDICTIVE ANALYSIS

  • EVALUATING THE WORTH OF LIFETIME VALUE

  • BIG DATA ADVANTAGES AND DISADVANTAGES

  • MAKING COMPARISONS WITH COMPETITORS

  • DATA SCIENCE IN THE TRAVEL SECTOR

  • SAFETY ENHANCEMENTS THANKS TO BIG DATA

  • BIG DATA AND AGRICULTURE

  • BIG DATA AND LAW ENFORCEMENT

  • THE USE OF BIG DATA IN THE PUBLIC SECTOR

  • BIG DATA AND GAMING

  • PRESCRIPTIVE ANALYTICS

  • GOOGLE’S “SELF-DRIVING CAR”

  • AND MUCH MORE!


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