Big data on AWS Training
Big data on AWS Course:
In this course, you will learn about cloud-based Big Data solutions such as Amazon EMR, Amazon Redshift, Amazon Kinesis, Amazon Glue, Amazon Athena, and the rest of the AWS Big Data services. We will show you how multiple services on AWS can be leveraged to provide end to end data pipelines. Other than individually looking into theses services we will also see how to leverage best practices to design Big Data environments for security and cost-effectiveness.
Big data on AWS Course Curriculum
Fundamentals of AWS Services
AWS Web console
Data Collection systems
optimize the operational characteristics of the storage solution
appropriate data structure and storage format
Amazon S3 Standard for frequent data access
Storage classes
S3 Cross-region Replication
S3 pricing concerns
Hosting a Static Website on Amazon S3
IAM Roles for S3 Access
S3 Data Management
AWS Database services
Connecting to RDS Aurora
Securing RDS
Read replicas
Features and usecases of DynamoDB
Redshift Architecture
Loading the data
Table design
Workload Management
Overview of Redshift Spectrum
IAM Permissions for AWS Glue
Environment to Access Data Stores
AWS Glue Console Workflow Overview
Authorizing Jobs
ETL Programming
AWS Big data Ecosystem
EMR Architecture
Spark on EMR
Kinesis streams
Kinesis Producers and consumers
AWS Athena Overview and Setup
Integration with AWS Glue
Working with Source Data
Querying Geospatial Data
Handling Schema Updates
Integration with Redshift
Data visualization
Identify how to ensure data integrity
Data Pipeline
Industry Best practices on Big Data
Frequently Asked Questions
This "Big data on AWS" course is an instructor-led training (ILT). The trainer travels to your office location and delivers the training within your office premises. If you need training space for the training we can provide a fully-equipped lab with all the required facilities. The online instructor-led training is also available if required. Online training is live and the instructor's screen will be visible and voice will be audible. Participants screen will also be visible and participants can ask queries during the live session.
Participants will be provided "Big data on AWS"-specific study material. Participants will have lifetime access to all the code and resources needed for this "Big data on AWS". Our public GitHub repository and the study material will also be shared with the participants.
All the courses from zekeLabs are hands-on courses. The code/document used in the class will be provided to the participants. Cloud-lab and Virtual Machines are provided to every participant during the "Big data on AWS" training.
The "Big data on AWS" training varies several factors. Including the prior knowledge of the team on the subject, the objective of the team learning from the program, customization in the course is needed among others. Contact us to know more about "Big data on AWS" course duration.
The "Big data on AWS" training is organised at the client's premises. We have delivered and continue to deliver "Big data on AWS" training in India, USA, Singapore, Hong Kong, and Indonesia. We also have state-of-art training facilities based on client requirement.
Our Subject matter experts (SMEs) have more than ten years of industry experience. This ensures that the learning program is a 360-degree holistic knowledge and learning experience. The course program has been designed in close collaboration with the experts working in esteemed organizations such as Google, Microsoft, Amazon, and similar others.
Yes, absolutely. For every training, we conduct a technical call with our Subject Matter Expert (SME) and the technical lead of the team that undergoes training. The course is tailored based on the current expertise of the participants, objectives of the team undergoing the training program and short term and long term objectives of the organisation.
Drop a mail to us at [email protected] or call us at +91 8041690175 and we will get back to you at the earliest for your queries on "Big data on AWS" course.
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