The course "Data Analysis Using Hadoop Tools" provides a thorough and hands-on introduction to key tools within the Hadoop ecosystem, such as Hive, Pig, HBase, and Apache Spark, for data processing, management, and analysis. Learners will gain practical experience with Hive's SQL-like interface for complex data querying, Pig Latin scripting for data transformation, and HBase's NoSQL capabilities for efficient big data management. The course also covers Apache Spark's powerful in-memory computation capabilities for high-performance data processing tasks. By the end, participants will be equipped with the skills to leverage these technologies within the Hadoop platform to address real-world big data challenges.
Data Analysis Using Hadoop Tools
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Data Analysis Using Hadoop Tools
This course is part of Big Data Processing Using Hadoop Specialization
Instructor: Karthik Shyamsunder
Included with 
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
23 hours to complete
3 weeks at 7 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Learn to set up and configure Hive, Pig, HBase, and Spark for efficient big data analysis and processing within the Hadoop ecosystem.
Master Hive’s SQL-like queries for data retrieval, management, and optimization using partitions and joins to enhance query performance.
Understand Pig Latin for scripting data transformations, including the use of operators like join and debug to process large datasets effectively.
Gain expertise in NoSQL databases with HBase for real-time read/write operations, and use Spark’s core programming model for fast data processing.
Skills you'll gain
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Recently updated!
January 2025
Assessments
15 assignments
Taught in English
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This course is part of the Big Data Processing Using Hadoop Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 5 modules in this course
This course provides a comprehensive overview of key tools within the Hadoop ecosystem, including Hive, Pig, HBase, and Apache Spark. You will learn how to set up and configure these technologies for data processing, management, and analysis. The course covers Hive's query execution, Pig's scripting language, and HBase's NoSQL capabilities. You'll also gain hands-on experience with Spark's core programming model for efficient big data processing. By the end, you'll be equipped to leverage these tools for optimized data analysis and management.
What's included
2 readings
In this module, we will cover MapReduce programming using a higher-level language called Hive which translates Hive SQL-like queries to MapReduce.
What's included
9 videos7 readings4 assignments
In this module, we will cover MapReduce programming using a higher-level language called Pig which translates Pig Latin queries to MapReduce.
What's included
9 videos7 readings4 assignments
In this module, we will start with a primer of NoSQL databases and then dive into HBase, a NoSQL database built on top of Hadoop that allows for random, real-time read/write access to your Big Data.
What's included
8 videos3 readings3 assignments
In this module, we will cover the Spark engine and framework and show how it integrates on the Hadoop platform.
What's included
8 videos5 readings4 assignments
Instructor
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Frequently asked questions
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