Big Data on AWS

Learn about cloud-based Big Data solutions such as Amazon EMR, Amazon Redshift, Amazon Kinesis, and the rest of the AWS Big Data platform during this 3-day course. Discover how to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue. The course also teaches you how to create Big Data environments, work with Amazon DynamoDB, Amazon Redshift, Amazon QuickSight, Amazon Athena, and Amazon Kinesis, and leverage best practices to design Big Data environments for security and cost-effectiveness. 

Gain an understanding in: 

• Fit AWS solutions inside a Big Data ecosystem 
• Leverage Apache Hadoop in the context of Amazon EMR 
• Identify the components of an Amazon EMR cluster, then launch and configure an Amazon EMR cluster 
• Use common programming frameworks available for Amazon EMR, including Hive, Pig, and streaming 
• And much more 

Level: Intermediate | Duration: 3 Days | Mode: Live Virtual

Date: 1-3 Nov 2021 

Fee: RM 5,400  

Who is this course for? 

• Solutions architects 
• SysOps administrators 
• Data scientists 
• Data analysts 

What experience you require: 

• Basic familiarity with big data technologies, including Apache Hadoop, HDFS, and SQL/NoSQL querying 
• Completed Data Analytics Fundamentals free digital training or equivalent experience 
• Working knowledge of core AWS services and public cloud implementation 
• Completed the AWS Technical Essentials classroom training or have equivalent experience 
• Basic understanding of data warehousing, relational database systems, and database design 

Associated Certification: 

AWS Certified Data Analytics - Specialty 

Earn an industry-recognized credential from AWS that validates your expertise in AWS data lakes and analytics services. Build credibility and confidence by highlighting your ability to design, build, secure, and maintain analytics solutions on AWS that are efficient, cost-effective, and secure. Show you have breadth and depth in delivering insight from data. 

You will be validated in your ability to: 

• Define AWS data analytics services and understand how they integrate with each other 
• Explain how AWS data analytics services fit in the data life cycle of collection, storage, processing, and visualization