Format
Multiple choice, multiple answer

Type
Specialty

Delivery Method
Testing center or online proctored exam

Time
180 minutes to complete the exam

Cost
300 USD (Practice exam: 40 USD)

Language
Available in English, Japanese, Korean, and Simplified Chinese

Earn an industry-recognized credential from AWS that validates your expertise in AWS data lakes and analytics services. Build credibility and confidence by highlighting your ability to design, build, secure, and maintain analytics solutions on AWS that are efficient, cost-effective, and secure. Show you have breadth and depth in delivering insight from data.

The world of data analytics on AWS includes a dizzying array of technologies and services. Just a sampling of the topics we cover in-depth are:

• Streaming massive data with AWS Kinesis

• Queuing messages with Simple Queue Service (SQS)

• Wrangling the explosion data from the Internet of Things (IOT)

• Transitioning from small to big data with the AWS Database Migration Service (DMS)

• Storing massive data lakes with the Simple Storage Service (S3)

• Optimizing transactional queries with DynamoDB

• Tying your big data systems together with AWS Lambda

• Making unstructured data query-able with AWS Glue

• Processing data at unlimited scale with Elastic MapReduce, including Apache Spark, Hive, HBase, Presto, Zeppelin, Splunk, and Flume

• Applying neural networks at massive scale with Deep Learning, MXNet, and Tensorflow

• Applying advanced machine learning algorithms at scale with Amazon SageMaker

• Analyzing streaming data in real-time with Kinesis Analytics

• Searching and analyzing petabyte-scale data with Amazon Elasticsearch Service

• Querying S3 data lakes with Amazon Athena

• Hosting massive-scale data warehouses with Redshift and Redshift Spectrum

• Integrating smaller data with your big data, using the Relational Database Service (RDS) and Aurora

• Visualizing your data interactively with Quicksight

• Keeping your data secure with encryption, KMS, HSM, IAM, Cognito, STS, and more

  
  

Abilities Validated by the Certification

• Define AWS data analytics services and understand how they integrate with each other

• Explain how AWS data analytics services fit in the data life cycle of collection, storage, processing, and visualization

Recommended Knowledge and Experience

• At least 5 years of experience with data analytics technologies

• At least 2 years of hands-on experience working with AWS

• Experience and expertise working with AWS services to design, build, secure, and maintain analytics solutions