AWS DATA ENGINEER VERY VERY URGENT

₹ 1,500.00 — 12,500.00 INR

AWS DATA ENGINER TRAINER REQUIRED IMMEDIATE BASIS

5 DAYS OF TRAINIG UREGENT BASIS NEED TO START IMMEDAITELY
Module 2 - Big Data on AWS Introduction
1.
Learning Objective
2.
Cloud computing and it's advantages
3.
Cloud Computing Models
4.
Cloud Service Categories
5.
AWS Cloud Platform
6.
Design Principles - Part One
7.
Design Principles - Part Two
8. 8.
Why AWS for Big Data - Reasons and Challenges
9. 9.
Databases in AWS
10.
Data Warehousing in AWS
11.
Redshift, Kinesis and EMR
12.
DynamoDB, Machine Learning and Lambda
13.
Elastic Search Services and EC2
14.
Key Takeaways

Module 3 - AWS Big Data Collection Services
1.
Learning Objective
2.
Amazon Kinesis and Kinesis Stream
3.
Kinesis Data Stream Architecture and Core Components
4.
Data Producer
5.
Data Consumer
6.
Kinesis Stream Emitting Data to AWS Services and Kinesis Connector Library
7.
Kinesis Firehose
8.
Transferring Data Using Lambda
9.
Amazon SQS, Lifecycle and Architecture
10.
IoT and Big Data
11.
IoT Framework
12.
AWS Data Pipelines and Data Nodes
13.
Activity, Pre-condition and Schedule
14.
Key Takeaways
Module 4 - AWS Big Data Storage Services
1.
Learning Objective
2.
Amazon Glacier and Big Data
3.
DynamoDB Introduction
4.
DynamoDB and EMR
5.
DynamoDB Partitions and Distributions
6.
DynamoDB GSI LSI
7.
DynamoDB Stream and Cross Region Replication
8.
DynamoDB Performance and Partition Key Selection
9.
Snowball and AWS Big Data
10.
AWS DMS
11.
AWS Aurora in Big Data
12.
Key Takeaways
Module 5 - AWS Big Data Processing Services
1.
Learning Objective
2.
Amazon EMR
3.
Apache Hadoop
4.
EMR Architecture
5.
EMR Releases and Cluster
6.
Choosing Instance and Monitoring
7.
Demo - Advance EMR Setting Options
8.
Hive on EMR
9.
HBase with EMR
10.
Presto with EMR
11.
Spark with EMR
12.
EMR File Storage
13.
AWS Lambda
14.
Key Takeaways
Module 6 - Analysis
1.
Learning Objective
2.
Redshift Intro and Use cases
3.
Redshift Architecture
4.
MPP and Redshift in AWS Eco-System
5.
Columnar Databases
6.
Redshift Table Design - Part 2
7.
Demo - Redshift Maintenance and Operations
8.
Machine Learning Introduction
9.
Machine Learning Algorithm
10.
Amazon SageMaker
11.
Amazon Elasticsearch
12.
Amazon Elasticsearch Services
13.
Demo - Loading Dataset into Elasticsearch
14.
Logstash and R Studio
15.
Demo - Fetching the File and Analyzing it using RStudio
16.
Athena
17.
Demo - Running Query on S3 using the Serverless Athena
18.
Key Takeaways
Module 7 - Visualization
1.
Introduction to Amazon QuickSight
2.
Visual Types
3.
Story
4.
Big Data Visualization
5.
Key Takeaways
Module 8 - Security

Cloud ComputingAmazon Web ServicesBig Data SalesPostgreSQLGCP AI

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