Edureka’s Big Data Hadoop Training Course is curated by Hadoop industry experts, and it covers in-depth knowledge on Big Data and Hadoop Ecosystem tools such as HDFS, YARN, MapReduce, Hive, Pig, HBase, Spark, Oozie, Flume and Sqoop. Throughout this online instructor-led Hadoop Training, you will be working on real-life industry use cases in Retail, Social Media, Aviation, Tourism and Financedomain using Edureka’s Cloud Lab.
- In-depth knowledge of Big Data and Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator) & MapReduce
- Comprehensive knowledge of various tools that fall in Hadoop Ecosystem like Pig, Hive, Sqoop, Flume, Oozie, and HBase
- The capability to ingest data in HDFS using Sqoop & Flume, and analyze those large datasets stored in the HDFS
- The exposure to many real-world industry-based projects which will be executed in Edureka’s CloudLab
- Projects which are diverse in nature covering various data sets from multiple domains such as banking, telecommunication, social media, insurance, and e-commerce
- Rigorous involvement of a Hadoop expert throughout the Big Data Hadoop Training to learn industry standards and best practices
- Master the concepts of HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator), & understand how to work with Hadoop storage & resource management.
- Understand MapReduce Framework
- Implement complex business solution using MapReduce
- Learn data ingestion techniques using Sqoop and Flume
- Perform ETL operations & data analytics using Pig and Hive
- Implementing Partitioning, Bucketing and Indexing in Hive
- Understand HBase, i.e a NoSQL Database in Hadoop, HBase Architecture & Mechanisms
- Integrate HBase with Hive
- Schedule jobs using Oozie
- Implement best practices for Hadoop development
- Understand Apache Spark and its Ecosystem
- Learn how to work with RDD in Apache Spark
- Work on real-world Big Data Analytics Project
- Work on a real-time Hadoop cluster
Batch Start Date: Oct 26, 2019
Timings: 07:00 AM to 10:00 AM (IST)
For full details and online registration visit the link below.
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