Big Data Fundamentals - Concepts, Drivers & Techniques

Big Data Fundamentals provides a pragmatic, no-nonsense introduction to Big Data. This course clearly explains key Big Data concepts, theory and terminology, as well as fundamental technologies and techniques. All coverage is supported with case study examples and numerous simple diagrams. The course begins by explaining how Big Data can propel an organization forward by solving a spectrum of previously intractable business problems. Next, it demystifies key analysis techniques
and technologies and show how a Big Data solution environment can be built and integrated to offer competitive advantages.
▪ Discovering Big Data’s Fundamental Concepts And What Makes İt Different From Previous Forms Of Data Analysis And Data Science
▪ Understanding The Business Motivations And Drivers Behind Big Data Adoption, From Operational İmprovements Through İnnovation
▪ Planning Strategic, Business-Driven Big Data İnitiatives
▪ Addressing Considerations Such As Data Management, Governance, And Security
▪ Recognizing The 5 “V” Characteristics Of Datasets İn Big Data Environments: Volume, Velocity, Variety, Veracity, And Value
▪ Clarifying Big Data’s Relationships With OLTP, OLAP, ETL, Data Warehouses, And Data Marts
▪ Working With Big Data İn Structured, Unstructured, Semi-Structured, And Metadata Formats
▪ Increasing Value By İntegrating Big Data Resources With Corporate Performance Monitoring
▪ Understanding How Big Data Leverages Distributed And Parallel Processing
▪ Using Nosql And Other Technologies To Meet Big Data’s Distinct Data Processing Requirements
▪ Leveraging Statistical Approaches Of Quantitative And Qualitative Analysis
▪ Applying Computational Analysis Methods, İncluding Machine Learning

▪ Part I: The Fundamentals Of Big Data
▪ Understanding Big Data
▪ Business Motivations and Drivers for Big Data Adoption
▪ Big Data Adoption and Planning Considerations
▪ Enterprise Technologies and Big Data Business Intelligence
▪ Part II: Storing And Analyzing Big Data
▪ Big Data Storage Concepts
▪ Big Data Processing Concepts
▪ Big Data Storage Technology
▪ Big Data Analysis Techniques
▪ Case Study Conclusion