Big Data on AWS Course + Exam
Big Data on AWS Training
The Big Data on AWS course equips IT professionals and data engineers with practical skills to build scalable data architectures in the AWS Cloud. Throughout the training, participants learn to design, deploy, and manage big data solutions using core AWS services such as Amazon EMR, Kinesis, Redshift, and S3, with a strong foundation in best practices for performance, security, and cost.
With a blend of theory, hands-on labs, and real-world scenarios, the Big Data on AWS training immerses learners in workflows that cover data ingestion, storage, processing, and analytics. You’ll gain confidence in building data pipelines, optimising query performance, and integrating AWS analytics services, ensuring you’re ready to handle enterprise-scale datasets.
By completing the Big Data on AWS course, professionals will be prepared not only to implement robust big data solutions but also to pursue advanced certification like the AWS Certified Data Analytics – Specialty (exam code: DAS-C01), further validating their expertise in cloud data services.
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Prior experience with AWS core services such as EC2, S3, and IAM.
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Basic understanding of data analytics concepts including databases, data processing, and big data tools.
AWS Certified Big Data – Specialty (BDS-C00) exam has been retired.
The certification fee is not icluded in the course fee.
The skills gained from Big Data on AWS course are given below:
- Implementation of core AWS Big Data services
- Designing and maintaining Big Data
- Leveraging tools to automate Data Analysis
This course is likely to add to the employment related skills of the participants. The skills developed are likely to be used in the course of being an employee or working in a business.
The audience for AWS Certified Big Data Speciality Certification are:
- Big Data Solutions Architects
- Enterprise Solutions Architects
- SysOps Administrator
- DevOps Engineer
- Data Analysts
- Data Scientists
- Data Consultants
- Fit AWS solutions inside a big data ecosystem
- Leverage Apache Hadoop in the context of Amazon EMR
- Identify the components of an Amazon EMR cluster, then launch and configure an Amazon EMR cluster
- Use common programming frameworks available for Amazon EMR, including Hive, Pig, and streaming
- Improve the ease of use of Amazon EMR by using Hadoop User Experience (Hue)
- Use in-memory analytics with Apache Spark on Amazon EMR
- Choose appropriate AWS data storage options
- Identify the benefits of using Amazon Kinesis for near real-time Big Data processing
- Leverage Amazon Redshift to efficiently store and analyse data
- Comprehend and manage costs and security for a Big Data solution
- Identify options for ingesting, transferring, and compressing data
- Leverage Amazon Athena for ad-hoc query analytics
- Use AWS Glue to automate extract, transform, and load (ETL) workloads
- Use visualization software to depict data and queries using Amazon QuickSight
- AWS Technical Essentials
- AWS Business Essentials
- Media Essentials for IT Business Decision Makers
- AWS Cloud Practitioner Essentials
- AWS Solutions Architect – Associate
- AWS SysOps Administrator – Associate
- AWS Developer – Associate
- AWS Certified Advanced Networking – Specialty
- AWS Certified Data Analytics – Specialty
- AWS Certified Database – Specialty
- AWS Certified Machine Learning – Specialty
- AWS Certified Security – Specialty
- Advanced Developing on AWS
- Planning and Designing Databases on AWS
- Deep Learning on AWS
Get a Certificate of Attendance to prove your commitment to learning
Take the official certification exam at Logitrain, a local VUE test centre or online
Course material in digital format is included for flexibility and ease of use
Mock test is included in the full-time courses to assist with your preparation
Our trainers are highly skilled with expertise and extensive hands-on experience
Relax, we will beat competitor’s advertised price. Our course has no extra costs
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The supply of this course/package/program is governed by our terms and conditions. Please read them carefully before enrolling, as enrolment is conditional on acceptance of these terms and conditions. Proposed course dates are given, course runs subject to availability and minimum registrations.
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