Big data is a hot topic in BI and analytics. Yet it is a complex topic that is still in the early stages of evolution. Successful big data projects that deliver real business value are challenged by multiple definitions and rapidly shifting technologies. Achieving good return on your big data investment requires strategy that focuses on purpose, people, and process before exploring data and technologies. Strategy drives planning and architecture to ensure that big data complements and does not disrupt the existing BI and analytics environment. To prepare for success with big data, start by understanding all of the pieces and how they fit together.
There are no prerequisites for this course.
Business and data analysts; BI and analytics program and project managers; BI and data warehouse architects, designers, and developers; data governance and data quality professionals getting started with big data; anyone seeking to cut through the hype to understand the opportunities, challenges, and realities of the big data phenomenon.
Common definitions of big data and the implications of each
Key characteristics of big data and why size is not among the top five
The structures that can be found in “unstructured” data
Types of big data sources—streaming data, social data, sensor data, etc.
Value opportunities and common applications for big data
Considerations when adapting architectures, organizations, and cultures to incorporate big data
The scope of big data processes, tools, and technologies
Module 1 – Big Data Basics
What Is Big Data?
Characteristics (3 V’s plus 2)
Types of Big Data
Why Big Data Analytics – Extending Advanced Analytics Capabilities
Big Data Use Cases
Customer Understanding and Targeting
Business Process Optimization
Law Enforcement and Public Safety
Sports Performance Improvement
Public Transportation and Infrastructure Advances
Why Big Data Now? – The Driving Forces
Kinds of Big Data – Data Variety
Sources of Big Data
Web and Social Media
Machine to Machine
Other Sources (Big Transaction Data, Biometrics, Human Generated Data,