A Practical Introduction to Data Analysis and Big Data - 3 Days

• A general understanding of math
• A general understanding of programming
• A general understanding of databases

Audience

• Developers / programmers
• IT consultants

Participants who complete this instructor-led, live training will gain a practical, real-world understanding of Big Data and its related technologies, methodologies and tools.

Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class.

The course starts with an introduction to elemental concepts of Big Data, then progresses into the programming languages and methodologies used to perform Data Analysis. Finally, we discuss the tools and infrastructure that enable Big Data storage, Distributed Processing, and Scalability.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Data Analysis and Big Data

• What Makes Big Data "Big"?
  • Velocity, Volume, Variety, Veracity (VVVV)
• Limits to Traditional Data Processing
• Distributed Processing
• Statistical Analysis
• Types of Machine Learning Analysis
• Data Visualization

Big Data Roles and Responsibilities

• Administrators
• Developers
• Data Analysts

Languages Used for Data Analysis

• Python
  • Why Python for Data Analysis?
  • Manipulating, processing, cleaning, and crunching data

Approaches to Data Analysis

• Statistical Analysis
  • Time Series analysis
  • Forecasting with Correlation and Regression models
  • Inferential Statistics (estimating)
  • Descriptive Statistics in Big Data sets (e.g. calculating mean)
• Machine Learning
  • Supervised vs unsupervised learning
  • Classification and clustering
  • Estimating cost of specific methods
  • Filtering

Big Data Infrastructure

• Data Storage
  • Relational databases (SQL)
    • MySQL
    • Postgres
    • Oracle
  • Understanding the nuances
    • Hierarchical databases
    • Object-oriented databases
    • Document-oriented databases
    • Graph-oriented databases
    • Other

The Future of Big Data

Summary and Next Steps