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Big data on AWS (Amazon Web Services) refers to the utilization of AWS services and infrastructure for storing, processing, and analyzing large volumes of data. AWS provides a comprehensive set of tools and services specifically designed to handle big data workloads efficiently and effectively.
Curriculum Designed by Experts
• Overview of big data concepts and challenges
• Introduction to AWS cloud computing services
• Understanding the AWS big data ecosystem
• Architectural considerations for big data on AWS
• Overview of AWS storage services (S3, EBS, EFS, Glacier)
• Designing data storage solutions for big data workloads
• Data ingestion and data transfer methods
• Data lifecycle management and versioning
• Introduction to AWS compute services (EC2, EMR, Lambda)
• Batch processing with AWS Elastic MapReduce (EMR)
• Real-time processing with AWS Lambda and Kinesis
• Serverless computing for big data workloads
• Introduction to AWS data warehousing services (Redshift, Athena, Glue)
• Designing and optimizing data warehouse architectures
• Querying and analyzing big data with AWS services
• Integration with business intelligence (BI) tools
• Introduction to AWS streaming services (Kinesis, Kafka)
• Real-time data ingestion and processing pipelines
• Real-time analytics with AWS services (Kinesis Analytics, Amazon Managed Streaming
for Apache Kafka)
• Monitoring and scaling real-time analytics solutions
• Introduction to AWS orchestration services (Step Functions, Data Pipeline)
• Designing and managing big data workflows on AWS
• Automating data pipelines and ETL processes
• Error handling and fault tolerance in data workflows
• Understanding data governance challenges in big data
• Data security and compliance considerations on AWS
• Identity and access management (IAM) for big data workloads
• Encryption and data protection mechanisms on AWS
• Overview of data visualization tools and services
• Integrating AWS big data solutions with visualization tools (QuickSight, Tableau)
• Designing interactive dashboards and reports
• Data storytelling and effective visualization practices
• Cost optimization strategies for big data workloads on AWS
• Selecting the right AWS services based on cost and performance requirements
• Monitoring and optimizing resource utilization
• Scalability and performance tuning techniques
• Advanced analytics with AWS machine learning services (SageMaker, Comprehend,
Rekognition)
• Big data processing with AWS serverless technologies (Glue, Athena, Lambda)
• Exploring emerging trends in big data and AWS services
• Industry use cases and best practices
refers to the utilization of AWS services and infrastructure for storing, processing, and analyzing large volumes of data. AWS provides a comprehensive set of tools and services specifically designed to handle big data workloads efficiently and effectively. Some of the key services offered by AWS for big data include:
These are just a few examples of the many AWS services available for handling big data. AWS provides a scalable and flexible platform for storing, processing, and analyzing large datasets, allowing organizations to leverage the power of big data for various purposes, including business intelligence, machine learning, and predictive analytics
Mastering Big Data on AWS is crucial in today’s data-driven world. This course covers in-demand skills like data storage, processing with Amazon EMR, analytics using Redshift, and real-time insights with Kinesis. Enroll to gain practical expertise and propel your career in cloud-based data management and analytics.
The Big Data on AWS course opens doors to roles like Data Engineer, Big Data Analyst, and Cloud Architect. With expertise in AWS tools like EMR, Redshift, and Kinesis, you’ll be equipped to drive data solutions. Enroll to build a career in the fast-growing field of cloud-based big data analytics.
Accelerate your Cloud Adoption journey with our comprehensive BIGDATA ON AWS Course Training! Gain hands-on expertise in managing and processing massive data sets with AWS tools, enhancing your skills in data analytics, secure storage, and real-time insights. Enroll today to master essential cloud-based Big Data skills, designed for modern data professionals.
Achieve unparalleled Scalability and Flexibility with our BIGDATA ON AWS Course Training! Dive deep into AWS tools that empower you to handle vast data sets, adjust seamlessly to workload demands, and drive impactful insights. Enroll today to gain essential skills for scalable, adaptable data solutions in the cloud.
Master Cost Management with our BIGDATA ON AWS Course Training! Learn strategies to optimize spending, maximize AWS resource use, and manage Big Data workloads efficiently. Enroll now to gain essential skills for cost-effective data solutions on AWS, empowering your cloud journey. Join us today!
Enhance Security and Compliance with our BIGDATA ON AWS Course Training! Gain in-depth knowledge to secure vast data, ensure regulatory compliance, and safeguard cloud infrastructure. Enroll now to master essential AWS security skills for managing Big Data with confidence. Join us today for a secure future!
At Radical Technologies, we are committed to your success beyond the classroom. Our 100% Job Assistance program ensures that you are not only equipped with industry-relevant skills but also guided through the job placement process. With personalized resume building, interview preparation, and access to our extensive network of hiring partners, we help you take the next step confidently into your IT career. Join us and let your journey to a successful future begin with the right support.
At Radical Technologies, we ensure you’re ready to shine in any interview. Our comprehensive Interview Preparation program includes mock interviews, expert feedback, and tailored coaching sessions to build your confidence. Learn how to effectively communicate your skills, handle technical questions, and make a lasting impression on potential employers. With our guidance, you’ll walk into your interviews prepared and poised for success.
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Infrastructure Provisioning
Implementing automated infrastructure provisioning and configuration management using Ansible. This may include setting up servers, networking devices, and other infrastructure components using playbooks and roles.
Applications Deployment
Automating the deployment and orchestration of applications across development, testing, and production environments. This could involve deploying web servers, databases. middleware, and other application components using Ansible
Continuous Integration
Integrating Ansible into CI/CD pipelines to automate software. build, test, and deployment processes. This may include automating the creation of build artifacts, running tests, and deploying applications to various environments.