Big Data and Analytics for Business Users

Cloud Computing Basics

• Objectives
• The Origin of Cloud Computing
• Defining Cloud Computing
• Five Characteristic of Cloud
• Three Service Models of the Cloud
• Four Deployment Models of the Cloud
• Understanding by Analogy
• Cloud Adoption By the Numbers

Introduction to Big Data

• Objectives
• How did my data get so Big?
• Big Data sources
• Big Data analysis
• Big Data Use Cases
• Key vendors

The World of Analytics

• Objectives
• Data Analytics
• Predictive Analytics
• The Life Cycle of Data Analytics
• Common Analytical Models (Decision Trees, Linear vs Logistic Regression, Bayesian Techniques, etc.)

Exploring the Four Vs

• Objectives
• The Value of Big Data and Analytics
• Key Business Cases
• Handling Data Volume
• Handling Data Velocity
• Handling Data Variety
• Recommended Best Practices

The Technology of Big Data

• Objectives
• Distributed Computing with MapReduce
• Apache Hadoop and the Hadoop Distributed File System (HDFS)
• Apache Hive, Pig, Sqoop, and Oozie
• Google Fusion Tables
• Machine Learning with BigML
• Web Analytics Toolsets

Standing up a Big Data and Analytics Team

• Objectives
• The importance of a Business Domain Model
• The role of an Information Architect
• Data Owners and Data Stewards
• Data Scientists
• Process Considerations
• Tool and Technology Recommendations
• Recommended Next Steps