AWS Data Analytics Certification e-learning

AWS Data Analytics Certification e-learning

Prepares you for the AWS Certified Data Analytics - Specialty (DAS-C01) exam.

The AWS Data Analytics certification training prepares you for all aspects of hosting big data and distributed processing on the AWS platform. Our AWS Data Analytics course is aligned to the AWS Certified Data Analytics Specialty exam and will help you pass it in a single attempt. Developed by industry leaders, this AWS Certified Data Analytics training course explores some interesting topics like AWS QuickSight, AWS lambda and Glue, S3 and DynamoDB, Redshift, Hive on EMR, among others.

AWS Data Analytics Certification course overview

In this AWS Big Data certification course, you will familiarize yourself with the concepts of cloud computing and its deployment models. This AWS Big Data training covers Amazon's AWS cloud platform, Kinesis Analytics, AWS big data storage, processing, analytics, visualization and security services, machine learning algorithms, and much more.

Key features

• Course and materials are in English
• 12 months of e-learning access (self-paced)
• 14 hours of total video content
• 40 hours of recommended study time
• Practical project at the end of the course
• Official exam is not included, but the course is aligned with the AWS Data Analytics Speciality
• Certification of completion

Learning outcomes

• Leverage Amazon EMR to process large data sets using Hadoop ecosystem tools, enabling efficient data analysis and transformation.
• Use Amazon Kinesis to ingest and process streaming data in real-time, facilitating timely insights and decision-making
• Create interactive dashboards and perform ad hoc queries with Amazon QuickSight, enhancing data-driven storytelling and business intelligence capabilities.
• Gain knowledge of AWS big data storage solutions and implement security best practices to ensure data integrity and compliance.
• Develop the knowledge and skills required to successfully pass the AWS Certified Data Analytics - Specialty (DAS-C01) exam, which validates your expertise in AWS data analytics services

Target audience for the training

The AWS Data Analytics Certification Training is ideal for a wide range of professionals and individuals aiming to build or advance their careers in data analytics and cloud computing. Below are the target audiences:

• Data Analysts
• Data engineers
• Data scientists
• Cloud architects and engineers
• System administrators
• Backend engineers

Prerequisites

Although there is no formal requirement to enroll. The prerequisites for enrolling in the AWS Data Analytics Certification Course are designed to ensure that participants have a basic understanding of cloud and data analytics concepts. Here are the key requirements:

Basic knowledge of cloud computing

• Familiarity with cloud computing concepts, such as virtualization, cloud storage, and networking.
• Previous experience with AWS services (e.g. EC2, S3) is recommended but not mandatory.

Understanding of data analytics concepts

• Knowledge of basic data analytics principles, including data storage, transformation and visualization.
• Experience working with databases, data warehouses or big data tools is helpful.

Skills in programming

• Basic knowledge of a programming language, such as Python, Java or SQL, is an advantage for working with AWS data tools and scripting tasks.

Previous practical experience

• Hands-on experience in data analysis, data engineering or related technologies is beneficial but not a requirement.
• Familiarity with tools such as Hadoop, Spark or similar data processing frameworks may be helpful.

Course content

1. introduction

2. collection

• Amazon Kinesis
• IoT
• AWS database migration service
• AWS direct connection
• AWS Snow family
• Amazon MSK: Managed streaming for Apache Kafka

3. storage

• Amazon Simple Storage Service
• Amazon DynamoDB
• Amazon ElastiCache

4. Processing

• AWS Lambda
• Glue Hive and Extract Transform and Load (ETL)
• AWS Glue Studio
• AWS Glue DataBrew
• AWS Lake Formation
• Amazon Elastic MapReduce (EMR)
• Apache Spark
• Apache Pig and HBase on Amazon Elastic MapReduce (EMR)
• AWS Data Pipeline

5. Analyzing the data

• Kinesis Analytics
• Amazon Elasticsearch
• Amazon Athena
• Amazon Redshift
• Amazon Relational Database Service (RDS) and Aurora

6. Visualization

• Amazon QuickSight
• Types of visualization
• Other visualization tools

7. security

• Encryption
• AWS key management service
• AWS CloudHSM
• AWS security features
• Identity federation
• AWS CloudTrail
• Virtual Private Cloud (VPC) endpoints

8. Everything else

• Integration of AWS services
• Instance types for Big Data
• Amazon Elastic Compute Cloud

9. preparing for the exam

• Tips for the exam
• Review of the exam