BIG DATA ON AWS
- Description
- Reviews
Course Overview
Introduction
This course provides an in-depth understanding of how to leverage AWS services to manage, analyze, and visualize big data. Participants will gain practical knowledge of AWS tools and frameworks to process vast amounts of data efficiently, uncover insights, and drive business decisions.
Business Relevance
With the exponential growth of data, businesses need robust solutions for data processing, analysis, and storage. This course equips professionals with the skills to manage big data workloads on AWS, enabling businesses to unlock insights, improve operational efficiency, and enhance decision-making.
Target Area
This course supports big data analytics, cloud data management, and data engineering. It’s ideal for organizations looking to implement scalable, cost-efficient big data solutions using AWS.
What You’ll Learn & Who Should Enroll
Key Topics Covered:
- Introduction to Big Data on AWS: Learn about the fundamental AWS services for big data, such as Amazon S3, Amazon EMR, and Amazon Redshift.
- Data Storage & Management: Understand how to store and manage large datasets using AWS services, focusing on Amazon S3 and Glacier for long-term storage.
- Data Processing with Amazon EMR: Learn how to process vast amounts of data using Hadoop and Spark in Amazon EMR for distributed computing.
- Data Analysis & Visualization: Explore Amazon Redshift, Athena, and QuickSight for real-time analytics, data warehousing, and visualization.
- Big Data Security & Compliance: Understand how to secure and manage data in compliance with industry regulations using AWS security features.
Ideal Participants:
This course is designed for:
- Data Engineers & Big Data Analysts – Professionals managing and processing large-scale datasets using AWS services.
- Cloud Architects & IT Professionals – Individuals designing and implementing big data solutions on AWS infrastructure.
- Machine Learning & AI Specialists – Experts leveraging big data tools for advanced analytics and model training.
- Business Intelligence Professionals – Analysts and decision-makers using AWS big data services for insights and reporting.
Business Applications & Next Steps
Key Business Impact:
- Data-Driven Decision Making: Enable your business to extract valuable insights from big data, supporting more accurate and timely decisions.
- Scalable & Cost-Efficient Solutions: Implement big data solutions that scale with your business needs while optimizing costs on AWS.
- Operational Efficiency: Automate data processing pipelines and workflows to improve efficiency and reduce operational overhead.
Next-Level Training:
To further build expertise, consider:
- AWS Certified Big Data – Specialty: Gain advanced knowledge and skills in implementing big data solutions on AWS.
- Advanced Data Engineering on AWS: Learn to design and implement large-scale data systems and processing pipelines.
Why Choose Acumen IT Training?
- Enterprise-Focused Curriculum: Tailored to provide businesses with the tools and techniques to process and analyze big data effectively on AWS.
- Expert-Led Training: Delivered by experienced trainers with deep expertise in big data technologies and AWS solutions.
- Practical Application: Includes hands-on labs, case studies, and real-world examples to ensure participants can directly apply their learning to business needs.
Master the art of big data! Enroll now and gain the expertise to implement scalable, efficient, and secure big data solutions using AWS to drive business growth and innovation.
Course Outline
COURSE OBJECTIVES
- Fit AWS solutions inside of a big data ecosystem
- Leverage Apache Hadoop in the context of Amazon EMR
- Identify the components of an Amazon EMR cluster
- Launch and configure an Amazon EMR cluster
- Leverage common programming frameworks available for Amazon EMR including Hive, Pig, and Streaming
- Leverage Hue to improve the ease-of-use of Amazon EMR
- Use in-memory analytics with Spark on Amazon EMR
- Choose appropriate AWS data storage options
- Identify the benefits of using Amazon Kinesis for near real-time big data processing
- Leverage Amazon Redshift to efficiently store and analyze data
- Comprehend and manage costs and security for a big data solution
- Identify options for ingesting, transferring, and compressing data
- Leverage Amazon Athena for ad-hoc query analytics
- Leverage AWS Glue to automate ETL workloads.
- Use visualization software to depict data and queries using Amazon QuickSight
- Orchestrate big data workflows using AWS Data Pipeline
TRAINING INCLUSIONS
- Comprehensive training materials and data processing guides
- Hands-on labs with real-world big data analytics scenarios
- Big Data on AWS Certificate of Training Completion
- Access to AWS big data tools, including Amazon EMR, AWS Glue, and Amazon Redshift
- 30 Days Post-Training Support
COURSE OUTLINE
Day 1
- Overview of Big Data
- Ingestion
- Big Data streaming and Amazon Kinesis
- Using Kinesis to stream and analyze Apache server logs
- Storage Solutions
- Querying Big Data using Amazon Athena
- Using Amazon Athena to analyze log data
- Introduction to Apache Hadoop and Amazon EM
Day 2
- Using Amazon Elastic MapReduce
- Storing and Querying Data on DynamoDB
- Hadoop Programming Frameworks
- Processing Server Logs with Hive on Amazon EMR
- Streamlining Your Amazon EMR Experience with Hue
- Running Pig Scripts in Hue on Amazon EMR
- Spark on Amazon EMR
- Processing New York Taxi dataset using Spark on Amazon EMR
For FULL COURSE OUTLINE, please contact us.
Inquire now for schedules and private class bookings
FAQs
- What is Big Data on AWS training?
This course provides an in-depth understanding of AWS big data tools and best practices for processing, storing, and analyzing large datasets. - Who is this training for?
It is designed for data engineers, analysts, IT professionals, and business leaders who want to leverage AWS for big data analytics. - Do I need prior AWS experience to take this course?
Basic knowledge of AWS and data analytics is recommended but not required. - What skills will I learn in this training?
You will learn how to process large datasets, optimize data storage, implement machine learning workflows, and visualize insights using AWS services. - How long is the training program?
The training spans five days, covering both theoretical concepts and hands-on exercises. - What is the format of the certification exam?
The exam consists of multiple-choice and scenario-based questions evaluating your understanding of AWS big data solutions. - Is this training available online?
Yes, we offer both online and in-person training options. - How will Big Data on AWS training benefit my career?
This training enhances your expertise in data analytics, making you a strong candidate for roles in data engineering, cloud computing, and business intelligence. - How long is the certification valid?
The certification is valid for three years and can be renewed through AWS continuous learning programs. - What career opportunities are available after completing this training?
You can pursue roles such as data engineer, big data analyst, cloud data architect, and machine learning specialist.
Real-World Applications of Big Data on AWS
Case Study 1: Enhancing Customer Insights with Big Data
Challenge: A global e-commerce company struggled to analyze large amounts of customer data in real time.
Solution: The company implemented Amazon Redshift and AWS Glue to process customer behavior data and generate actionable insights.
Result:
✅ 50% faster customer trend analysis
✅ Improved personalization and customer engagement
✅ Enhanced decision-making with real-time analytics
Case Study 2: Optimizing Supply Chain Management
Challenge: A logistics company needed better visibility into shipment tracking and demand forecasting.
Solution: The team used Amazon EMR and AWS Lambda to process real-time data from IoT devices and historical shipment records.
Result:
✅ 30% improvement in delivery efficiency
✅ Reduced costs by optimizing supply chain operations
✅ Improved forecasting accuracy for demand planning
Use Case 1: Fraud Detection in Financial Transactions
Financial institutions use AWS big data tools to detect fraudulent activities by analyzing transaction patterns in real time.
✅ Identify suspicious transactions instantly
✅ Reduce financial losses due to fraud
✅ Strengthen security measures with predictive analytics
Use Case 2: Healthcare Data Analysis
Healthcare providers use AWS to process and analyze large-scale medical records for better patient outcomes and predictive analytics.
✅ Improve diagnosis accuracy with big data insights
✅ Optimize hospital resource allocation
✅ Enhance patient care through personalized treatment plans
Why These Case Studies Matter for You
By mastering AWS big data solutions, you’ll be equipped to handle large datasets, drive business intelligence, and create scalable analytics solutions.
🔗Enroll today and take the next step in mastering big data analytics with AWS!
Testimonials: What Professionals Say About Our Big Data on AWS Training
⭐ ⭐ ⭐ ⭐ ⭐ “A Game Changer for Data Analytics!”
“This training helped me streamline data processing for my company. AWS big data tools are now an essential part of our analytics workflow.”
— Lorenzo D., data engineer, retail industry
⭐ ⭐ ⭐ ⭐ ⭐ “Great Hands-On Experience!”
“The hands-on labs made it easy to understand how to process large datasets efficiently. I highly recommend this training!”
— Angela M., business analyst, finance sector
⭐ ⭐ ⭐ ⭐ ⭐ “Essential for Big Data Professionals!”
“I learned how to leverage AWS for real-time data processing and analytics. This course gave me the skills to build powerful data solutions.”
— Michael R., cloud data architect, IT industry
