Aegis School of Business, Data Science, Cyber Security & Telecommunication
| Application fee: | 1000 * INR |
| Course fee: | 15000 * INR |
| GST: | 18 % |
Big Data on AWS: Amazon Elastic MapReduce (EMR)
Details
| Certification Body: | Aegis School of Data Science |
|---|---|
| Location: | On-campus (India, Mumbai, Pune, Bangalore) |
| Type: | Certificate course |
| Director: | Dr. Vinay Kulkarni |
| Coordinator: | Ritin Joshi |
| Language: | English |
| Course fee: | 15000 * INR |
| GST: | 18% |
| Total course fee: | 17700 * INR |
| Rating: |
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Course Details
Big Data on AWS: Amazon Elastic MapReduce (EMR)
Description
This course introduces you to cloud-based big data solutions and Amazon Elastic MapReduce (EMR), the AWS big data platform. In this course, we show you how to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Pig and Hive. We also teach you how to create big data environments, work with Amazon DynamoDB, Amazon Redshift, and Amazon Kinesis, and leverage best practices to design big data environments for security and cost-effectiveness.
Course Objectives
This course is designed to teach you how to:
- Understand Apache Hadoop in the context of Amazon EMR
- Understand the architecture of an Amazon EMR cluster
- Launch an Amazon EMR cluster using an appropriate Amazon Machine Image and Amazon EC2 instance types
- Choose appropriate AWS data storage options for use with Amazon EMR
- Know your options for ingesting, transferring, and compressing data for use with Amazon EMR
- Use common programming frameworks available for Amazon EMR including Hive, Pig, and Streaming
- Work with Amazon Redshift to implement a big data solution
- Leverage big data visualization software
- Choose appropriate security options for Amazon EMR and your data
- Perform in-memory data analysis with Spark and Shark on Amazon EMR
- Choose appropriate options to manage your Amazon EMR environment cost-effectively
- Understand the benefits of using Amazon Kinesis for big data
Intended Audience
This course is intended for:
- Individuals responsible for designing and implementing big data solutions, namely Solutions Architects and SysOps Administrators
- Data Scientists and Data Analysts interested in learning about big data solutions on AWS
Prerequisites
We recommend that attendees of this course have:
- Basic familiarity with big data technologies, including Apache Hadoop and HDFS
- Knowledge of big data technologies such as Pig, Hive, and MapReduce is helpful but not required
- Working knowledge of core AWS services and public cloud implementation
- Students should complete the Amazon Web Services Technical Fundamental course or have equivalent experience
- Basic understanding of data warehousing, relational database systems, and database design
Hands-On Activity
This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises
Course Outline
Module 1
- Overview of Big Data, Apache Hadoop, and the Benefits of Amazon EMR
- Amazon EMR Architecture
- Using Amazon EMR
- Launching and Using an Amazon EMR Cluster
- Hadoop Programming Frameworks
Module 2
- Using Hive for Advertising Analytics
- Using Streaming for Life Sciences Analytics
- Overview: Spark and Shark for In-Memory Analytics
- Using Spark and Shark for In-Memory Analytics
- Managing Amazon EMR Costs
- Overview of Amazon EMR Security
- Data Ingestion, Transfer, and Compression
- Using Amazon Kinesis for Real-Time Big Data Processing
Module 3
- Using Amazon Kinesis and Amazon EMR to Stream and Process Big Data
- AWS Data Storage Options
- Using DynamoDB with Amazon EMR
- Overview: Amazon Redshift and Big Data
- Using Amazon Redshift for Big Data
- Visualizing and Orchestrating Big Data
- Using Tableau Desktop or Jaspersoft BI to Visualize Big Data