Prerequisites
| Academic Qualification | Any Graduate |
|---|---|
| Course Duration | |
| Industrial Experience Level | Graduate, Professionals |
Big Data and Hadoop
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The world is getting increasingly digital, and this means big data boom will continue. In fact, the importance of big data and data analytics is going to continue growing in the coming years. Choosing a career in the field of big data and analytics might just be the type of role that you have been trying to find to meet your career expectations. Professionals who are working in this field can expect an impressive salary.
With this course You will be able to do following independently:
1. In-depth knowledge of Big Data and Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator) & MapReduce.
2. Understand MapReduce and its characteristics and assimilate advanced MapReduce concepts.
3. Comprehensive knowledge of various tools that fall in Hadoop Ecosystem like Pig, Hive, Sqoop, Flume, Oozie, and HBase.
4. The capability to ingest data in HDFS using Sqoop & Flume, and analyze those large datasets stored in the HDFS.
5. Projects which are diverse in nature covering various data sets from multiple domains such as banking, telecommunication, social media, insurance, and e-commerce.
6. Rigorous involvement of a Hadoop expert throughout the Big Data Hadoop Training to learn industry standards and best practices.
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 Hadoop Training, you will be working on real-life industry use cases in Retail, Social Media, Aviation, Tourism and Finance domain.
There are no such prerequisites for Big Data & Hadoop Course however prior knowledge of Core Java and SQL will be helpful but not mandatory.
• Understand and work with HBase, its architecture and data storage, and learn the difference between HBase and RDBMS.
• Gain a working knowledge of Pig and its components.
• Understand resilient distribution datasets (RDD) in detail.
• Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques.
• Understand the common use cases of Spark and various interactive algorithms.
Big Data and Hadoop Certification
1. Business decision making
2. Banking and Financial market
