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.
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Data Analysis Using Hadoop Tools
Dieser Kurs ist Teil von Spezialisierung Big Data Processing Using Hadoop
![Karthik Shyamsunder](https://d3njjcbhbojbot.cloudfront.net/api/utilities/v1/imageproxy/https://coursera-instructor-photos.s3.amazonaws.com/81/8405a4e6c748aa9352a28064a25059/karthik---Passport-size-photo.jpg?auto=format%2Ccompress&dpr=1&w=75&h=75&fit=crop)
Dozent: Karthik Shyamsunder
Bei enthalten
Empfohlene Erfahrung
Was Sie lernen werden
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.
Wichtige Details
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Januar 2025
15 Aufgaben
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In diesem Kurs gibt es 5 Module
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.
Das ist alles enthalten
2 Lektüren
In this module, we will cover MapReduce programming using a higher-level language called Hive which translates Hive SQL-like queries to MapReduce.
Das ist alles enthalten
9 Videos7 Lektüren4 Aufgaben
In this module, we will cover MapReduce programming using a higher-level language called Pig which translates Pig Latin queries to MapReduce.
Das ist alles enthalten
9 Videos7 Lektüren4 Aufgaben
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.
Das ist alles enthalten
8 Videos3 Lektüren3 Aufgaben
In this module, we will cover the Spark engine and framework and show how it integrates on the Hadoop platform.
Das ist alles enthalten
8 Videos5 Lektüren4 Aufgaben
Dozent
![Karthik Shyamsunder](https://d3njjcbhbojbot.cloudfront.net/api/utilities/v1/imageproxy/https://coursera-instructor-photos.s3.amazonaws.com/81/8405a4e6c748aa9352a28064a25059/karthik---Passport-size-photo.jpg?auto=format%2Ccompress&dpr=1&w=75&h=75&fit=crop)
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