Big Data Processing Using Hadoop
About this course
The specialization "Big Data Processing Using Hadoop" is intended for post-graduate students seeking to develop advanced skills in big data processing and management using the Hadoop ecosystem. Through four detailed courses, you will explore key technologies such as HDFS, MapReduce, and advanced data analysis tools like Hive, Pig, HBase, and Apache Spark. You’ll learn how to set up, configure, and optimize these tools to process, manage, and analyze large-scale datasets. The program covers fundamental concepts such as YARN and MapReduce architecture, and progresses to practical applications such as Hive query execution, Pig scripting, NoSQL management with HBase, and high-performance data processing with Spark. By the end of the specialization, you will be capable of designing and deploying big data solutions, optimizing workflows, and leveraging the power of Hadoop to address real-world challenges. This specialization prepares you for roles such as Data Engineer, Big Data Analyst, or Hadoop Developer, making you a highly competitive candidate in the fast-growing big data field, ready to drive innovations in industries such as data science, business analytics, and machine learning.
90/100
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- What the provider tells you
- 39/45
- Who stands behind it
- 35/35
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- 16/20
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What you'll learn
- understanding of HDFS and MapReduce architecture
- ability to execute Hive queries and write Pig scripts
- knowledge of NoSQL management with HBase
- skills in optimizing data workflows using Apache Spark
Course objectives
- develop advanced skills in big data processing
- learn to configure and optimize big data tools
- design and deploy big data solutions
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