Building Batch Data Analytics Solutions on AWS Training

Live Online & Classroom Enterprise Certification Training

Building Batch Data Analytics Solutions on AWS is a course that teaches how to design and implement scalable batch data processing workflows using AWS services like Amazon EMR, AWS Glue, and Amazon S3.

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What is Building Batch Data Analytics Solutions on AWS Certification Training about?

In this course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR.

What are the objectives of Building Batch Data Analytics Solutions on AWS Certification Training ?

In this course, you will learn to:

Compare the features and benefits of data warehouses, data lakes, and modern data architectures
Design and implement a batch data analytics solution
Identify and apply appropriate techniques, including compression, to optimize data storage
Select and deploy appropriate options to ingest, transform, and store data
Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case
Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
Secure data at rest and in transit
Monitor analytics workloads to identify and remediate problems
Apply cost management best practices

Who is Building Batch Data Analytics Solutions on AWS Certification Training for?

This course is intended for:

Data platform engineers
Architects and operators who build and manage data analytics pipelines

What are the prerequisites for Building Batch Data Analytics Solutions on AWS Certification Training?

Completed either AWS Technical Essentials or Architecting on AWS
Completed either Building Data Lakes on AWS or Getting Started with AWS Glue

Available Training Modes

Live Online Training

Classroom Training

1 Days

Course Outline Expand All

Expand All

Module 1: Introduction to Batch Data Analytics

What is batch processing?

Batch vs. streaming analytics

Common use cases (e.g., log analysis, ETL, reporting)

AWS analytics landscape overview

Module 2: Data Ingestion for Batch Processing

Data sources: logs, files, RDBMS, NoSQL, external systems

Using Amazon S3 as a data lake

Ingesting data using:

AWS Glue

AWS DataSync

Amazon Kinesis Data Firehose (for micro-batches)

AWS Snowball (for offline batch ingestion)

Module 3: Storing and Cataloging Data

Amazon S3 best practices for batch storage

Folder structure for partitioned batch data

AWS Glue Data Catalog

Creating and managing metadata tables

Integrating Glue Catalog with Athena and Redshift Spectrum

Module 4: Data Transformation Using AWS Glue

AWS Glue overview: ETL engine, crawlers, jobs

Building ETL jobs using PySpark or Scala

DynamicFrame vs. DataFrame

Partitioning and schema evolution

Job monitoring and retry mechanisms

Module 5: Querying Data with Amazon Athena and Redshift

Running SQL queries directly on S3 using Amazon Athena

Query optimization techniques (partition pruning, compression, columnar formats)

Using Amazon Redshift for batch querying and data warehousing

Redshift Spectrum for querying S3 data

Module 6: Automating Batch Workflows

Orchestrating ETL workflows with AWS Step Functions

Triggering jobs with Amazon EventBridge

Using AWS Lambda to coordinate batch jobs

Glue Workflows for scheduling and chaining jobs

Module 7: Cost Optimization and Performance Tuning

Data formats: CSV vs. Parquet vs. ORC

Compression techniques (Snappy, GZIP)

Partitioning and bucketing

Spot Instances and Glue job optimization

Monitoring with AWS CloudWatch and AWS Cost Explorer

Module 8: Security and Governance

IAM policies and roles for Glue, Athena, S3

Encryption in transit and at rest

Access control using Lake Formation

Auditing with CloudTrail

Module 9: Real-World Use Cases and Design Patterns

Data lake batch analytics architecture

Weekly reporting pipelines

Marketing campaign analytics

Compliance and audit reporting

Integrating with third-party BI tools (e.g., QuickSight, Tableau)

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Who is the instructor for this training?

The trainer for this Building Batch Data Analytics Solutions on AWS Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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