Foundations of Big Data Analytics
Description
Introduction to big data concepts, characteristics, applications, and the analytical ecosystem that enables processing of large-scale datasets.
Learning Objectives
Students will understand the fundamental concepts of big data, its characteristics (Volume, Velocity, Variety, Veracity, Value), distinguish between traditional and big data analytics approaches, identify business applications across industries, and comprehend the big data ecosystem including storage, processing, and analysis components.
Topics (8)
Comprehensive introduction to big data concepts, definition, and its transformative impact on businesses and society.
Detailed exploration of the five fundamental dimensions that characterize big data and distinguish it from traditional data.
Comparative analysis of traditional data processing limitations and big data processing capabilities, including architectural differences.
Industry-specific use cases demonstrating how big data analytics drives innovation and competitive advantage across different sectors.
Comprehensive categorization of data types encountered in big data analytics and their specific handling requirements and challenges.
Forward-looking analysis of technological advances and market trends shaping the future of big data analytics and its applications.
Holistic view of the big data technology stack encompassing data ingestion, storage, processing, analysis, and presentation layers.
Critical analysis of obstacles and potential benefits in big data adoption, including technical, organizational, and ethical considerations.