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Big Data Specialty Learning Path Conclusion

The course is part of this learning path

Big Data – Specialty Certification Preparation for AWS

course-steps 14 lab-steps 5 quiz-steps 3

Contents

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Overview
Transcript
DifficultyIntermediate
Duration4m
Students105

Description

This learning path has enabled you to recognize and explain the AWS big data services that are available and how to use those AWS services together to create Big Data solutions.

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

Collection
For domain one we explained the various data collection methods and techniques for determining the operational characteristics of a collection system. We explored how to define a collection system able to handle the frequency of data change and the type of data being ingested. We identifed 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 learning path focused on storage. In this group of courses, we outlined the key storage options for big data solutions. We determined 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 learned 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 learning path we learnt how to identify the appropriate data processing technologies needed for big data scenarios. We explored how to design and architect a data processing solution, and explored and defined the operational characteristics of big data processing. We delved in to the various processing services available focusing on Amazon Kinesis, Elastic Map Reduce and Amazon Recoknition.


Analysis
For domain four of the Big Data Specialty learning path we learnt how to determine the tools and techniques required for data analysis. We explored 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 learnt how to determine the appropriate techniques for delivering the results/output of a query or analysis. We examined 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
In this course we examined how to determine encryption requirements and how to implement encryption services. We examined 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

Students60977
Courses69
Learning paths15

Andrew is an AWS certified professional who is passionate about helping others learn how to use and gain benefit from AWS technologies. Andrew has worked for AWS and for AWS technology partners Ooyala and Adobe.  His favorite Amazon leadership principle is "Customer Obsession" as everything AWS starts with the customer. Passions around work are cycling and surfing, and having a laugh about the lessons learnt trying to launch two daughters and a few start ups.