Big Data Technologies and Advanced Analytics

What Will You Learn?

• Understand the core characteristics of big data: volume, velocity, variety, veracity, and value
• Gain hands-on knowledge of big data ecosystems and tools, including Hadoop Distributed File System (HDFS), MapReduce, Apache Spark, and various NoSQL databases (MongoDB, Cassandra, Redis, Neo4j)
• Learn to process and analyze large-scale datasets using distributed storage and in-memory computing techniques
• Master advanced analytics techniques such as text mining, sentiment analysis, and time series forecasting
• Explore practical applications of NLP for extracting keywords, topics, and sentiments from unstructured text data
• Develop skills in forecasting future trends using time series models like Moving Averages, ARIMA, and Facebook Prophet
• Understand how to build scalable data pipelines combining big data tools and advanced analytics methods
• Examine real-world case studies demonstrating end-to-end big data projects integrating Spark and NoSQL databases
• Identify common challenges in big data analytics and learn best practices for managing complexity and ensuring data quality
• Stay current with emerging trends, including streaming analytics, AI-driven big data processing, and cloud-based big data services from AWS, Azure, and Google Cloud