Data Science & Analytics
Apache Hadoop Big Data
At the core of Hadoop lies two essential components: the storage part, the Hadoop Distributed File System (HDFS), and the processing part, called MapReduce.
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Included with Skilldacity Membership
About This Course
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At the core of Hadoop lies two essential components: the storage part, the Hadoop Distributed File System (HDFS), and the processing part, called MapReduce. Hadoop operates by breaking down files into sizable blocks and distributing them among the nodes within a cluster. For data processing, Hadoop's MapReduce mechanism transmits packaged code to nodes for parallel processing based on the data each node requires.
This approach capitalizes on data locality, allowing nodes to process data they already possess. Consequently, data can be processed faster and more efficiently than traditional supercomputing architectures reliant on parallel file systems connected via high-speed networking.this course covers Big Data and Hadoop, covering topics like single and multi-node cluster installation, configuration, and management, HDFS management, writing MapReduce jobs, and working with various Hadoop projects such as Pig, Hive, HBase, Sqoop, and Zookeeper.
What You’ll Learn
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- Explain the data and analytics concepts addressed in the course
- Prepare, clean, and organize data for analysis
- Use the featured tools to explore patterns and answer questions
- Create clear visualizations, reports, or data products
- Communicate findings that support informed decisions
Skills You’ll Gain
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Apache
Developer
Data Science
Database
Storage
Career Path
Data Science & Analytics
Provider
Skilldacity
Level
Foundational
Certification
No certification associated
Access
Included with eligible Skilldacity subscription
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