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Big Data Analytics Essentials –
Mastering Big Data in your Business

Overview:  Approach big data analytics with confidence by mastering the core skills needed to put data to work for your business. This course covers the basics of big data technology, managing and accessing big data, analytics, and business intelligence. Big Data Analytics expert explains the importance of Big Data and organize your data so you can deliver results that your organization can leverage. The course starts by examining the modern data ecosystem and how it relates to running a smart and efficient data hub. Then, participants will learn how to perform the principle tasks involved in managing, loading, extracting, and transforming data. The instructor also takes you through basic data exploration and analysis process to extract the insight from your data. He, then, shows you how visual analytics helps you translate data into a visible from that highlights important features, including commonalities and anomalies, he provides actionable recommendations that applicable to data experts throughout an organization—analysts, engineers, scientists, modelers, and more.
Who Should Attend: Anyone who needs to use data analysis in their job role such as:
  · Strategists, programmer
  · Programmer
  · Proroject Managers
  · Business Analysts
  · Business Process Managers
Method:  Lecture and workshop
Duration:    2 days (13 hours), 09:00 – 16:30
Date:    See Training Schedule on
Fee:      15,900 Baht (VAT7% = 1,113 Baht, Total = 17,013 Baht)
Early Bird 13,900 Baht - to be paid 2 weeks prior to training (VAT7% = 973 Baht, Total = 14,873 Baht)
Venue:     TOT Academy 174 Ngam Wong Wan Rd., Soi 17 Muang Nonthaburi 11000 THAILAND
(See Map)
Language:    Thai
Instructors:    Dr. Sittapong Settapat (View Profile)
Registration: Download Registration Form and send to
Course Outline: Big Data Analytics Essentials – Mastering Big Data in your Business
Day 1 · Section One
  · Big Data - It’s Not Just Size that Matters
    ·  A Definition of What is Big Data
    ·  Identify who uses Big Data
    ·  Describe the importance of Big Data
    ·  Big Data Analytics in Business Today
    ·  Come up with a Data Map to Analyze the Big data in your Business
    ·  Establish Clear Objectives of Big Data Analytics
  · Section Two
  · Big Data - How to Collect It and Where to Store it
    ·  Recognise and Apply various data collection method
    ·  Identify and resolve
    ·  Problems associated with data collection
    ·  Consider the various types of data storage
    ·  Examine the difference between data warehouse and data lakes
    ·  Determine when to use data blending in your analysis
  · Section Three
  · Big Data Technologies and Tools (Technical Hands-on)
    ·  Make connection with relational databases
    ·  Make connection with Hive
    ·  Make connection with NoSQL
    ·  Get data into Big Data
    ·  Access your data
    ·  Processing your data (ETL/ELT)
  · Section Four
  · Dealing with Big Data
    ·  Keep things simple with structured data
    ·  Share semi structured data
    · Collect unstructured data
                               ·  Basic SQL for Data Exploration
                        ·  Big Data, Data Science, and Data Mining
 Day 2 · Section Five
  · What is Data Science?
    ·  Define a multidisciplinary practice with multiple meanings
    ·  Use statistics and software
    ·  Uncover insights and create knowledge
  · Section Six
  · Using Business Intelligence Tools 
    ·  An Overview of BI tools
    ·  Tableau demonstration
    ·  Discuss the concept of visualization analytics
    ·  Lean how to use Infographics
    ·  Build a business dashboard prototype
  · Section Seven
  · Applying Statistical Analysis
    ·   Start out the descriptive statistics
    ·   Understand probability
    ·   Find a correlation
    ·   See how correlation does not imply causation
    ·   Comb techniques for predictive analytics
    ·   Avoiding pitfalls
  · Section Eight
                           · Interpreting Your Data
     ·   Articulate the Importance of Accurately Interpreting Data
    ·   Determine How to Validate Your Data Analysis
    ·   Mitigate and Analyze Risk, Uncertainty, And Probability
    ·   Spot Patterns and Trends Through Statistical Analysis
    ·   Understand How to Conduct Correlation Analysis and Regression Testing
  · Section Nine
  · Deploying three types of analytics
    ·   Understand How You Use Descriptive Analytics
    ·   Plan A Strategy to Use Predictive Analytics
    ·   Think About When It Would Benefit to Use Prescriptive Analytics
    ·   Recognize When to Employ Descriptive, Predictive or Prescriptive Analytics
    ·   Build a Data Model Prototype
  · Section Ten
  · Marketing Your Big Data Analytics
    ·   Always Be Closing with Big Data Analytics
    ·   Master the Power of Enchantment
    ·   Being Decisive with Your Analysis
    ·   Use Findings from Big Data to Data Driven Business

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