Data Analytics Certification
This course teaches you everything you need to know about data analytics on AWS. You’ll learn how to design, build, and manage big data systems using AWS tools. It includes practical experience with data processing, analytics, machine learning, and business intelligence. Data Analytics Certification. The course also helps you get ready for the AWS Certified Data Analytics (Specialty) exam with hands-on labs and real-world examples. Data Analytics Certification.

Course Highlights: Data Analytics Certification
- Learn the main AWS data analytics tools and how to use them
- Create and manage data lakes using AWS S3 and Lake Formation
- Build scalable data warehouses with Amazon Redshift
- Design and run big data processing systems using AWS EMR
What You’ll Learn: Data Analytics Certification
- Understand the main AWS data analytics services and how they work
- Build and manage data lakes using Amazon S3 and Lake Formation
- Set up powerful data warehouses with Amazon Redshift
- Create big data solutions using Amazon EMR
- Automate data workflows using AWS Glue and other tools
- Work with real-time data streams using AWS Kinesis
- Use AWS QuickSight to create dashboards and reports
- Apply machine learning to your data with Amazon SageMaker
- Save costs by using efficient storage and processing options
- Build data pipelines for analytics and machine learning
- Learn about data security, compliance, and governance on AWS
- Get practical experience with AWS data tools
- Follow AWS best practices for data analytics projects.
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Requirements Data Analytics Certification
- Familiarity with AWS cloud services
- Basic understanding of data analytics and big data
- Experience with AWS tools like S3, EC2, and Lambda is helpful
- A computer with a stable internet connection
Introduction to Data Analytics on AWS
- Learn about the main AWS data analytics tools and what they’re used for
- Understand the differences between data lakes, data warehouses, and big data systems
- Set up a basic data lake using Amazon S3
- Learn how AWS Lake Formation helps manage your data lake
- Understand how data flows through AWS in a processing pipeline
- Learn about different AWS storage options like S3, Glacier, and EBS
- Discover how Amazon Redshift is used for big data and analytics
- Understand how AWS Lambda helps in processing data without managing servers.
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Working with AWS Data Lakes and Data Warehouses
- Learn why data lakes are important for big data analytics
- Create and manage data lakes using Amazon S3 and Lake Formation
- Combine data from different sources into your data lake
- Use AWS Glue to clean and prepare data for analysis
- Set up data catalogs and manage metadata with Lake Formation
- Protect your data lakes with encryption and access control
- Build a data warehouse on AWS using Amazon Redshift
- Perform large-scale analytics and reporting with Redshift
- Learn how to speed up Redshift performance for better results
Real-Time Data Processing with AWS
- Set up live data streams using AWS Kinesis
- Analyze streaming data using Amazon Kinesis Analytics
- Connect Kinesis with Lambda and S3 for real-time insights
- Use AWS Glue to automatically prepare real-time data
- Visualize live data with AWS QuickSight
- Create alerts and monitor your data streams in real time
- Connect real-time data with your data lakes and warehouses
- Understand how a real-time analytics system works on AWS
- Use Kinesis Firehose and Kinesis Streams to bring in live data
Business Intelligence and Data Visualization with AWS
- Learn how to use AWS QuickSight for reports and business insights
- Build interactive dashboards and charts using QuickSight
- Connect QuickSight to AWS tools like Redshift and S3
- Automate your BI reports and dashboards
- Use AWS Glue to clean and prepare data for BI use
- Understand self-service BI and how users can explore data on their own
- Manage who can access BI tools and data in AWS
- Link QuickSight with your data lakes and data warehouses
- Make QuickSight faster when handling large amounts of data
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