Exploration of Big Data Analytics

Exploration of Big Data Analytics

Course Overview
This study material explores the fundamental concepts of Big Data Analytics, focusing on its dimensions, challenges, and technological stack. You will gain insights into how organizations leverage big data, access public datasets, and apply machine learning techniques to derive actionable insights.

Key Topics Covered:

• What is Big Data?: Understand the core definition of Big Data, including its three Vs (Volume, Velocity, and Variety) and how it differs from traditional data sets.

• Big Data Dimensions: Explore the multiple dimensions of big data, such as Veracity, Value, and Variability, and their implications for data analysis.

• Where to Find Big Data?: Discover common sources of big data, including social media, IoT devices, and publicly available datasets. Examples of Big Data Public Datasets are provided to help users access large, open data sets for research and analysis.

• What to Do with Big Data?: This section covers practical applications of big data, including case studies such as Leasing Vehicle Return and the Business Intelligence (BI) approach to handling large data sets.

• Challenges Posed by Big Data: Understand the key challenges posed by big data, including issues related to data privacy, storage, processing speeds, and data quality.

• Technology Stack for Big Data:

  • Storing: Learn about the storage options for big data, with a focus on Distributed File Systems like Hadoop’s HDFS.
  • Databases for Big Data - NoSQL: Explore the use of NoSQL databases in managing unstructured and semi-structured data, and their scalability in handling massive datasets.

• Accessing and Learning from Big Data:

  • Explore different methods for accessing big data, including APIs and cloud platforms.
  • Learn how to extract insights using machine learning algorithms, focusing on Recommender Systems as a key application in big data analytics.

Why Choose This Material?

• Comprehensive coverage of the Big Data landscape, from data sources to advanced analytics.
• Focuses on the challenges and tools needed for effective Big Data management.
• Practical applications through real-world case studies and examples.

This course material is perfect for students and professionals looking to understand the full scope of Big Data Analytics and its practical applications in industries like finance, healthcare, and retail.