In order to get insights and make wise decisions, vast amounts of structured and unstructured data from multiple sources are combined and processed using methodologies, techniques, and tools known as "big data integration and processing."

Professionals may gain a variety of technical and analytical abilities, including data analysis, data management, data visualization, and machine learning, by learning about big data integration and processing.

You may anticipate working on projects that entail data ingestion, data storage, data processing, data analysis, and data visualization in a Big Data Integration and Processing course.

Hadoop, Spark, Pig, Hive, Kafka, Cassandra, and HBase are a few of the frequently used tools in big data integration and processing.

Data security, data privacy, data quality, data governance, and scalability are a few of the difficulties in integrating and processing big data.