Big Data Analytics

intro

About

By the end of this module, students will be able to:

Understand the fundamental concepts of big data, including its characteristics (Volume, Velocity, Variety, Veracity, and Value).
Explain the importance of big data analytics and its role in modern decision-making processes.
Identify and differentiate between the main types of analytics: descriptive, diagnostic, predictive, and prescriptive.
Describe the architecture of big data systems and the principles of distributed computing.
Understand the functioning and use of key technologies such as Apache Hadoop and Apache Spark.
Explore data storage techniques, including distributed file systems and NoSQL databases.
Analyze different data processing models, such as batch processing and real-time (stream) processing.
Apply basic data analysis techniques on large datasets using appropriate tools and frameworks.
Recognize common challenges in big data analytics, including data quality, scalability, and security issues.
Evaluate real-world applications of big data analytics across various domains.