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2Month/20 Hours Price:85,000
80,000
Amazon AWS Certified Data Analytics – Specialty
The AWS Certified Data Analytics Specialty Exam is one of the most challenging certification exams you can take from Amazon. Passing it tells employers in no uncertain terms that your knowledge of big data systems is wide and deep. But, even experienced technologists need to prepare heavily for this exam. This course sets you up for success, by covering all of the big data technologies on the exam and how they fit together.
The AWS Certified Data Analytics Specialty (DAS-C01) exam validates the candidate’s knowledge and understanding of using AWS services for planning, creating, securing, and maintaining analytics solutions that provide insight from data. However, this exam is also best for those in the data analytics-focused role.
Course Key Learnings
Move and transform massive data streams with Kinesis
Store big data with S3 and DynamoDB in a scalable, secure manner
Process big data with AWS Lambda and Glue ETL
Use the Hadoop ecosystem with AWS using Elastic MapReduce
Apply machine learning to massive data sets with Amazon ML, SageMaker, and deep learning
Analyze big data with Kinesis Analytics, Amazon Elasticsearch Service, Redshift, RDS, and Aurora
Visualize big data in the cloud using AWS QuickSight
Course Outline
Describe Collection
Determining the operational characteristics of the collection systemSelecting a collection system that handles the frequency, volume, and source of data
Selecting a collection system that addresses the key properties of data, such as order, format, and compression
Describe Storage and Data Management
Determining the operational characteristics of a storage solution for analyticsDetermining data access and retrieval patterns
Selecting suitable data layout, schema, structure, and format
Defining a data lifecycle based on usage patterns and business requirements
Determining a suitable system for cataloguing data and managing metadata
Describe Processing
Determining appropriate data processing solution requirementsDesigning a solution for transforming and preparing data for analysis
Automating and operationalizing a data processing solution
Analysis and Visualization
Determining the operational characteristics of an analysis and visualization solutionSelecting a suitable data analysis solution for a given scenario
Selecting the appropriate data visualization solution for a given scenario
Security
electing appropriate authentication and authorization mechanismsApplying data protection and encryption methods
Applying data governance and compliance controls
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