CODE: IT31
DURATION: 3 Days/5 Days
CERTIFICATIONS: CPD
This practical course provides a comprehensive introduction to the core tools and technologies that form the foundation of modern big data ecosystems. The content focuses on understanding the architecture, use cases, and practical implementation of these technologies to process and analyze large-scale datasets that exceed the capabilities of traditional systems, preparing you to design and work with scalable data solutions. Participants will acquire practical experience with the Hadoop Distributed File System (HDFS) for storage, MapReduce and Spark for distributed processing, and popular NoSQL databases like MongoDB and HBase for handling unstructured data.
This course is available in the following formats:
Virtual
Classroom
Request this course in a different delivery format.
Course Outcomes
Delegates will gain the knowledge and skills to:
Understand the architecture and components of Hadoop and Spark ecosystems.
Process large datasets using MapReduce and Spark transformations.
Work with HDFS for distributed data storage.
Implement basic operations using NoSQL databases.
Choose appropriate big data tools for different use cases.
Develop basic data pipelines using big data technologies.
At the end of this course, you’ll understand:
This course is designed for data engineers, software developers, database administrators, data analysts, and IT professionals who need to process, store, and manage large volumes of data using distributed computing frameworks and non-relational database technologies.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
