AWS Big Data Practice Exam
AWS Big Data Practice Exam
About AWS Big Data Exam
The AWS Big Data Exam is designed to assess your knowledge and skills in managing and analyzing large-scale datasets using Amazon Web Services (AWS) technologies. This exam focuses on the core AWS services used for big data solutions, including data storage, processing, and analytics. It is ideal for professionals looking to leverage AWS tools for handling big data workloads, enabling them to implement scalable and cost-efficient big data solutions in the cloud.
Who should take the Exam?
This exam is ideal for:
- Data engineers and data architects
- Cloud professionals working with AWS services
- Big data analysts looking to optimize cloud-based big data workflows
- Developers looking to specialize in AWS big data technologies
- IT professionals interested in cloud-based data analytics and processing
Skills Required
- Basic understanding of cloud computing and AWS services
- Familiarity with big data technologies such as Hadoop, Spark, or Kafka
- Experience with data storage, processing, and analytics tools
- Basic knowledge of SQL and data processing techniques
Knowledge Gained
- Proficiency in AWS big data services such as Amazon S3, Redshift, and EMR
- Understanding of how to set up and manage big data pipelines in the AWS environment
- Familiarity with data lakes, data warehouses, and NoSQL databases on AWS
- Expertise in processing and analyzing large datasets using AWS analytics services
Course Outline
The AWS Big Data Exam covers the following topics -
Domain 1 – Big Data Technologies on AWS
- Overview of AWS services for big data processing
- Amazon S3 for data storage and backup solutions
- Amazon Redshift for data warehousing and analytics
- Data lakes and NoSQL databases on AWS (DynamoDB)
Domain 2 – Data Processing and Analytics
- Introduction to AWS Elastic MapReduce (EMR) for big data processing
- Using AWS Glue for data transformation and ETL (Extract, Transform, Load)
- Real-time data processing with Amazon Kinesis
- Running data analytics with Amazon Athena and QuickSight
Domain 3 – Data Pipeline Management
- Building and managing big data workflows with AWS Data Pipeline
- Automating data ingestion, transformation, and storage
- Monitoring and optimizing data pipelines for efficiency and cost
Domain 4 – Security and Data Governance
- Implementing security best practices for big data solutions on AWS
- Data encryption, access control, and identity management on AWS
- Implementing data governance and compliance in big data projects
Domain 5 – Performance Optimization and Cost Management
- Optimizing big data workflows for performance
- Cost management strategies for big data solutions on AWS
- Using AWS pricing calculators and cost optimization tools
