Introduction to the Big Data Specialty Course

Beginner
3m
2,030
4.8/5

This course prepares you for the 3-hour AWS Big Data Specialty Certification exam and provides you an in-depth understanding of AWS Big Data services available and how to use those AWS services together to create big data solutions.

We cover the six domains of the big data specialty exam outline with lessons, labs, and quizzes.

Collection
For domain one we explain the various data collection methods and techniques for determining the operational characteristics of a collection system. We explore how to define a collection system able to handle the frequency of data change and the type of data being ingested. We identify how to enforce data properties such as order, data structure, and metadata, and to ensure the durability and availability for our collection approach.


Storage
Domain two of the Big Data Specialty course focuses on storage. In this group of lessons, we outline the key storage options for big data solutions. We determine data access and retrieval patterns, and some of the use cases that suit particular data patterns such as evaluating mechanisms for capture, update, and retrieval of catalog entries. We learn how to determine appropriate data structure and storage formats, and how to determine and optimize the operational characteristics of a Big Data storage solution.


Processing
In domain three of the Big Data Specialty course, we learn how to identify the appropriate data processing technologies needed for big data scenarios. We explore how to design and architect a data processing solution, and explore and define the operational characteristics of big data processing. We delve into the various processing services available focusing on Amazon Kinesis, Elastic Map Reduce and Amazon Rekognition.


Analysis
For domain four of the Big Data Specialty course, we learn how to determine the tools and techniques required for data analysis. We explore how to design and architect an analytical solution, and how to optimize the operational characteristics of the Analysis System using tools such as Amazon Athena and Kinesis.


Visualization
In domain five we learn how to determine the appropriate techniques for delivering the results/output of a query or analysis. We examine how to design and create a visualization platform using AWS services, and how to optimize visualization services to present results in an effective and accessible manner using Amazon Quicksight.


Data Security
Data security comprises 20% of the certification curriculum so it is important students have a thorough understanding of security best practices for Big Data solutions. In this lesson, we examine how to determine encryption requirements and how to implement encryption services. We examine how to choose the appropriate technology to enforce data governance, and Identify how to ensure data integrity while working with Big Data solutions.

About the Author
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Andrew is fanatical about helping business teams gain the maximum ROI possible from adopting, using, and optimizing Public Cloud Services. Having built  70+ Cloud Academy courses, Andrew has helped over 50,000 students master cloud computing by sharing the skills and experiences he gained during 20+  years leading digital teams in code and consulting. Before joining Cloud Academy, Andrew worked for AWS and for AWS technology partners Ooyala and Adobe.

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