Big Data – Specialty Certification Preparation for AWS

Intermediate

LP Box Courses 14 Video Courses
LP Box quiz 4 Quiz sessions
LP Box Lab 5 Hands-on Labs
Duration 18h 22m
Karma ~550 karma points
Certificate 18699 students
This Learning path prepares you for the AWS Big Data Specialty Certification. We cover the six domains of the Big Data Specialty exam outline with courses, labs and quizzes. We start with an introduction to analytics and database fundamentals. We then learn more relevant detail on Big Data collection, storage, processing, analysis, visualization and security. 


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 learning path focuses on storage. In this group of courses, 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 learning path 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 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 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 course 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.  

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This learning path prepares you for the 3 hour AWS Big Data Specialty Certification exam. This learning path 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 courses, labs, and quizzes. CollectionFor domain one we explain the ...

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In this course we will explore the Analytics tools provided by AWS, including Elastic Map Reduce (EMR), Data Pipeline, Elasticsearch, Kinesis, Amazon Machine Learning and QuickSight which is still in preview mode. We will start with an overview about Data Science and Analytics concepts to give beginners the context they need to be successful in the course.The second part of the course will focus ...

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AWS 180, from Cloud Academy's comprehensive Amazon Web Services learning tracks series, provides an introductory tour of Amazon's database solutions. You'll learn about managed database solutions and about the basic structure and function of Amazon's SQL-based RDS database - whether using the MySQL or AWS's new Aurora database engine. You'll get a walkthrough of an actual configuration and launch ...

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Course Description: In course one of the AWS Big Data Specialty Data Collection learning path 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 ...

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Course Description: Course two of the Big Data Specialty learning path focuses on storage. In this course 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 ...

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Lab Overview Amazon Redshift is a managed data warehouse that allows you to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools. Redshift uses query optimization, columnar storage, parallel execution, and high performance disks to query petabytes of data in seconds. In this lab you will learn how to create, query, and resize a Redshift cluster. Lab ...

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Course Description This course provides an introduction to working with Amazon DynamoDB, a fully-managed NoSQL database service provided by Amazon Web Services. We begin with a description of DynamoDB and compare it to other database platforms. The course continues by walking you through designing tables, and reading and writing data, which is somewhat different than other databases you may be ...

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Course Description: In this course for the Big Data Specialty Certification, 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. Intended audience: This course is intended for students wanting to extend ...

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Course Description: This course will provide you with a good foundation to better understand Amazon Kinesis, along with helping you to get started with building streamed solutions. In this course we'll put a heavier emphasis on hands-on demos along with breaking down the concepts and introducing you to the components that make up Amazon Kinesis. Intended audience: People working with Big Data ...

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Get started with Amazon Elastic MapReduce (EMR) and learn the fundamentals of EMR Lab Overview Amazon Elastic MapReduce (Amazon EMR) makes it easy to process vast amounts of data in a variety of applications, including log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics. Amazon EMR uses Hadoop, an open source framework, to ...

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When we saw how incredibly popular our blog post on Amazon Machine Learning was, we asked data and code guru James Counts to create this fantastic in-depth introduction to the principles and practice of Amazon Machine Learning so we could completely satisfy the demand for ML guidance. If you've got a real-world need to apply predictive analysis to large data sources - for fraud detection or ...

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Machine Learning is a very powerful technology to drive your data-driven decisions Lab Overview Nowadays it's possible for anyone to exploit the huge volumes of information available through big data and open datasets, whether you are a data scientist, an enterprise developer, or a small startup. Amazon Machine Learning lets you focus completely on your data, without wasting your time with ...

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In this course, we will perform an in-depth review of the Amazon Athena service. We will review and explain fundamental AWS Athena storage and querying concepts. We will highlight suitable use cases in which Athena can be applied effectively. You will be introduced to the basic underlying technology that Athena has been built on. We spend time discussing the process of creating and setting up ...

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In this Kinesis Analytics course, we will perform an in-depth review of the Amazon Kinesis Analytics service. We review where and when to use this service to best effect. You will be introduced to the key features and core components of the Kinesis Analytics service. We spend time understanding and reviewing Kinesis Analytics Applications, Input Streams, SQL Queries, Pumps, and Output Streams. ...

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How to automate object detection with Amazon Rekognition Amazon Rekognition allows you to detect objects and scene details from images. It provides a stateless and secure API that simply returns a list of related labels, with a certain confidence level. In order to automate the labels extraction process, we will build a serverless system that runs object detection on every image uploaded to S3. ...

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In this course 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 using AWS services, and how to optimize visualization services to present results in an effective and accessible manner. We introduce and outline the core AWS analysis tools and then work through how to integrate and ...

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Resources mentioned throughout this course: Cloud Academy Courses: Amazon Web Services: Key Management Services (KMS) Working with Amazon Kinesis Getting started with AWS CloudHSM AWS Resources: Configuring HDFS Transparent Encryption in Amazon EMR Using SSL to encrypt a connection a Database Oracle Native Network Encryption (NNE) Encrypt and decrypt Amazon Kinesis Records using AWS KMS ...

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Amazon Key Management Service along with S3 and EBS data encryption Lab Overview Amazon Web Services Key Management Service (KMS) is a managed service that simplifies the creation and management of encryption keys used to encrypt/decrypt your data. Most storage related AWS services are supported by KMS, including: EBS (Elastic Block Store) S3 (Simple Storage Service) Redshift RDS (Relational ...

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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. CollectionFor domain one we explained the various data collection methods and techniques for determining the operational ...
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Big Data – Specialty Certification Preparation for AWS
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