AWS Certified Big Data Specialty Training

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Unlock the Power of Big Data with AWS - Join Multisoft Systems' AWS Certified Big Data Specialty Course! Discover the keys to managing and analyzing expansive data sets, and become a certified expert in cloud-based big data solutions. Learn from industry professionals, leverage real-world projects, and elevate your career in the growing field of Big Data. Enroll today and step into a future where data drives decisions!

The AWS Certified Big Data Specialty course offered by Multisoft Systems is an in-depth training program designed to empower professionals to leverage the full potential of big data analytics on the AWS platform. This course is geared towards individuals who perform complex big data analyses and validates their ability to implement AWS services for data processing.

The course commences with an introduction to AWS Big Data Classification and architecture, setting the foundation for the more complex elements. Participants will then delve into various AWS services, including Amazon Kinesis, AWS Glue, Amazon Redshift, and Amazon QuickSight. The curriculum equips participants with a thorough understanding of the processes involved in collection, storage, processing, analysis, visualization, and security of big data on AWS. Additionally, participants will gain hands-on experience through multiple real-world projects, enhancing their practical understanding of AWS big data tools and services. On completion of the course, participants will be adept at handling big data workflows on AWS and ready to take the AWS Certified Big Data Specialty exam.

With its blend of theoretical knowledge and practical exposure, Multisoft's AWS Certified Big Data Specialty course ensures participants are well-equipped to manage big data operations on the AWS platform and make data-driven decisions effectively. The AWS Certified Big Data Specialty certification validates a professional's ability to design, implement, and maintain Big Data solutions using AWS cloud services. It signifies expertise in data analytics, demonstrating the skills to turn complex datasets into insights using AWS's robust Big Data tools. This certification is ideal for individuals performing complex Big Data analyses or data scientists.

AWS Certified Big Data Specialty Course Objective

Develop an understanding of AWS Big Data services and learn how they fit in the data lifecycle of collection, storage, processing, and visualization.
Gain proficiency in managing and converting big data into useful insights using AWS tools.
Learn to use Amazon S3 and DynamoDB for data storage and retrieval.
Understand how to use Amazon Kinesis for real-time big data processing.
Become proficient in data processing using AWS Lambda, Amazon Glue, and other AWS data processing services.
Learn how to use AWS analytics tools such as Amazon Athena, Redshift, and QuickSight for complex data analysis.
Understand how to secure your data using AWS data encryption methods and secure data governance tools like AWS Lake Formation.
Gain hands-on experience in managing and analyzing big data with AWS through real-world projects and case studies.
Prepare for the AWS Certified Big Data Specialty exam and understand the exam format and question types.
Develop the confidence to solve complex Big Data problems using AWS cloud solutions.

AWS Certified Big Data Specialty Online Training

Recorded Videos After Training
Digital Learning Material
Course Completion Certificate
24x7 After Training Support

Target Audience

Data Professionals
IT Professionals
AWS Solution Architects
Professionals preparing for AWS
Big Data Specialty
Exam Cloud Enthusiasts

AWS Certified Big Data Specialty Course Prerequisites

AWS Knowledge: Basic familiarity with AWS services is crucial since the course will focus on specialized big data services offered by AWS. Prior experience with AWS core services like S3, EC2, IAM, etc., can be particularly useful.
Big Data Experience: Having some experience or understanding of big data concepts can significantly aid your learning. Knowledge of data lifecycles and big data frameworks, like Hadoop or Spark, is beneficial.
Data Analytics Understanding: Familiarity with data analytics concepts and tools will be advantageous as the course will cover AWS data analytics services.
Coding Skills: While not mandatory, knowing how to code can be helpful as it allows you to interact with AWS services more flexibly. Python, Java, or Scala are common languages used in big data processing.
Certification in AWS Cloud Practitioner or any Associate-level AWS certification: While not a strict prerequisite, this can provide a solid foundation for understanding AWS services and architecture.

AWS Certified Big Data Specialty Course Certification

Multisoft Systems provides a globally recognized training certificate after successful completion of AWS Certified Big Data Specialty Training Course.

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AWS Certified Big Data Specialty Course Objective

Develop an understanding of AWS Big Data services and learn how they fit in the data lifecycle of collection, storage, processing, and visualization.
Gain proficiency in managing and converting big data into useful insights using AWS tools.
Learn to use Amazon S3 and DynamoDB for data storage and retrieval.
Understand how to use Amazon Kinesis for real-time big data processing.
Become proficient in data processing using AWS Lambda, Amazon Glue, and other AWS data processing services.
Learn how to use AWS analytics tools such as Amazon Athena, Redshift, and QuickSight for complex data analysis.
Understand how to secure your data using AWS data encryption methods and secure data governance tools like AWS Lake Formation.
Gain hands-on experience in managing and analyzing big data with AWS through real-world projects and case studies.
Prepare for the AWS Certified Big Data Specialty exam and understand the exam format and question types.
Develop the confidence to solve complex Big Data problems using AWS cloud solutions.

AWS Certified Big Data Specialty Online Training

Recorded Videos After Training
Digital Learning Material
Course Completion Certificate
24x7 After Training Support

Target Audience

Data Professionals
IT Professionals
AWS Solution Architects
Professionals preparing for AWS
Big Data Specialty
Exam Cloud Enthusiasts

AWS Certified Big Data Specialty Course Prerequisites

AWS Knowledge: Basic familiarity with AWS services is crucial since the course will focus on specialized big data services offered by AWS. Prior experience with AWS core services like S3, EC2, IAM, etc., can be particularly useful.
Big Data Experience: Having some experience or understanding of big data concepts can significantly aid your learning. Knowledge of data lifecycles and big data frameworks, like Hadoop or Spark, is beneficial.
Data Analytics Understanding: Familiarity with data analytics concepts and tools will be advantageous as the course will cover AWS data analytics services.
Coding Skills: While not mandatory, knowing how to code can be helpful as it allows you to interact with AWS services more flexibly. Python, Java, or Scala are common languages used in big data processing.
Certification in AWS Cloud Practitioner or any Associate-level AWS certification: While not a strict prerequisite, this can provide a solid foundation for understanding AWS services and architecture.

AWS Certified Big Data Specialty Course Certification

Multisoft Systems provides a globally recognized training certificate after successful completion of AWS Certified Big Data Specialty Training Course.

AWS Certified Big Data Specialty Training Course Content

Module 1: Introduction

Exam Blue Print
How Was This Course Created
Disclaimer - This Course Will Not Guarantee That You Will Pass Your Exam
What You’ll Need, To Do This Course
Generating a Dataset

Module 2: Collection

Kinesis Streams Introduction
Kinesis Streams Core Concepts
Kinesis Streams Emitting Data to AWS Services
Kinesis Firehose
SQS
oT
Data Pipeline
Getting Data into AWS

Module 3: Storage1

Glacier
DynamoDB Introduction
DynamoDB Partitions
DynamoDB GSI/LSI
DynamoDB Streams and Replication
DynamoDB Performance Deep Dive Part 1
DynamoDB Performance Deep Dive Part 2

Module 4: Processing

EMR Introduction
Apache Hadoop Part 1
Apache Hadoop Part 2
EMR Architecture Part 1
EMR Architecture Part 2
EMR Operations Part 1
EMR Operations Part 2
EMR Operations Part 3
EMR Operations Part 4
Using Hue with EMR
Hive on EMR
HBase on EMR
Presto on EMR
Spark on EMR Part 1
Spark on EMR Part 2
EMR File Storage and Compression
EMR Lab
Lambda in the AWS Big Data Ecosystem
HCatalog
Glue
Glue Lab

Module 5: Analysis

Introduction to Redshift
Redshift Architecture
Redshift in the AWS Ecosystem
Columnar Databases
Redshift Table Design - Introduction
Redshift Table Design - Distribution Styles
Redshift Table Design - Sort Keys
Redshift Table Design - Data Types
Redshift Table Design – Compression
Redshift Table Design - Constraints
Redshift Table Design - Review Design
Redshift Workload Management
Redshift Loading Data Part 1
Redshift Data Loading Part 2
Redshift Loading Data Part 3
Redshift Loading Data Part 4
Redshift Maintenance and Operations Part 1
Redshift Maintenance and Operations Part 2
Redshift Lab
Machine Learning Introduction
Machine Learning Multiclass Classification Model
Machine Learning Binary Classification Model
Machine Learning Regression Model
Machine Learning Lab
Elasticsearch
RStudio
RStudio Lab
Athena
Athena Lab

Module 6: Visualization

QuickSight Introduction
QuickSight Visualization
Big Data Visualization
Microstrategy

Module 7: Security

EMR Security
Redshift Security
Module 8: Good Luck!
Exam Strategy
Good Luck!

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