The Big Data Analytics and Engineering: Hadoop, Spark and NoSQL Technologies course is designed for learners who want to understand how large and complex datasets are stored, processed and analysed. It introduces key big data technologies, including Hadoop, MapReduce, NoSQL databases, Apache Spark and Apache Pig.
Whether you are interested in data analytics, data engineering, database management or emerging technologies, this course can help you develop foundational knowledge of big data systems and their applications in modern organisations.
Description
This course explores the core concepts, tools and technologies used in big data environments. Learners will begin with an introduction to big data before examining Hadoop and MapReduce for distributed data processing. The course also covers NoSQL databases, data storage and retrieval, data processing with Apache Spark, and data analysis using Hadoop and Pig. It provides an overview of how these technologies support the management and analysis of large-scale datasets.
Key Features
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Introduction to big data concepts and technologies
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Understanding the characteristics of big data
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Hadoop architecture and fundamentals
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Introduction to MapReduce
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Understanding NoSQL databases
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Data storage and retrieval techniques
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Data processing with Apache Spark
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Introduction to Apache Pig
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Data analysis using Hadoop and Pig
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Exploring distributed data processing systems
Learning Benefits
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Understand the fundamentals of big data
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Explore how organisations manage large datasets
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Develop awareness of Hadoop architecture
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Understand the basic principles of MapReduce
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Explore NoSQL databases and their applications
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Learn about different data storage and retrieval approaches
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Understand how Apache Spark supports large-scale data processing
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Develop awareness of data analysis using Hadoop and Pig
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Recognise the role of distributed computing in big data environments
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Build a foundation for further learning in data engineering and analytics
Who Is This Course For?
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Beginners interested in big data
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Aspiring Big Data Analysts
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Aspiring Big Data Engineers
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Data Science students
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Computer Science students
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Software Engineering students
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IT students and professionals
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Aspiring Data Engineers
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Junior Data Analysts
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Database Management beginners
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Database Administrators
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Data Processing Assistants
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Business Intelligence beginners
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Individuals interested in Hadoop
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Individuals interested in Apache Spark
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Professionals exploring data technologies
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Career changers entering the data industry
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Students and lifelong learners
Requirements
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No formal big data qualifications are required.
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No previous experience with Hadoop or Spark is necessary.
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Basic computer literacy is recommended.
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Basic knowledge of databases can be helpful.
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Familiarity with programming or data analysis may be useful but is not essential for beginners.
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An internet-enabled computer or laptop is recommended.
Career Path
This course can support foundational knowledge relevant to roles such as:
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Junior Big Data Analyst
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Big Data Engineering Assistant
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Junior Data Engineer
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Data Analyst
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Data Processing Assistant
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Data Management Assistant
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Database Support Assistant
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NoSQL Database Assistant
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Hadoop Support Assistant
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Apache Spark Support Assistant
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Business Intelligence Assistant
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Data Operations Assistant
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Data Analytics Assistant
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Data Infrastructure Support Assistant
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Junior Database Administrator
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Data Science Support Assistant
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Further Study in Big Data, Data Engineering, Data Science and Database Technologies
