AWS Data Engineering

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AWS Data Engineering
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Course Curriculum

AWS Data Engineering course:

  1. Introduction to Data Engineering on AWS:

    • Overview of data engineering concepts and principles
    • Introduction to AWS services for data engineering

  2. Data Storage and Data Lakes:

    • Amazon S3 for data storage and data lakes
    • Data ingestion strategies and best practices
    • Data partitioning and bucketing
    • Data security and encryption

  3. Data Processing with AWS Glue and AWS EMR:

    • Introduction to AWS Glue for ETL (Extract, Transform, Load)
    • Data cataloging with AWS Glue Data Catalog
    • Data transformation using AWS Glue Jobs
    • Introduction to AWS EMR for big data processing
    • Working with Apache Spark on AWS EMR
    • Using Presto for interactive data querying

  4. Real-time Data Streaming with Amazon Kinesis:

    • Introduction to Amazon Kinesis for data streaming
    • Working with Kinesis Data Streams
    • Real-time data ingestion and processing
    • Integrating Kinesis with other AWS services (e.g., S3, Lambda, Redshift)

  5. Data Warehousing with Amazon Redshift:

    • Introduction to Amazon Redshift for data warehousing
    • Designing and setting up Redshift clusters
    • Data loading and querying with Redshift
    • Performance optimization techniques
    • Redshift Spectrum for querying external data sources

  6. Serverless Data Processing with AWS Lambda:

    • Introduction to AWS Lambda for serverless computing
    • Building serverless data pipelines with Lambda
    • Data transformation and enrichment using Lambda functions
    • Integrating Lambda with other AWS services (e.g., S3, DynamoDB)

  7. Data Orchestration with AWS Data Pipeline and AWS Step Functions:

    • Introduction to AWS Data Pipeline for data orchestration
    • Building data processing workflows with Data Pipeline
    • Introduction to AWS Step Functions for workflow automation
    • Using Step Functions for complex data pipelines

  8. Data Analytics with Amazon Athena:

    • Introduction to Amazon Athena for interactive querying
    • Working with structured and semi-structured data in Athena
    • Optimizing query performance in Athena
    • Integrating Athena with other AWS services (e.g., S3, Glue)

  9. Data Quality and Data Governance:

    • Data quality assessment and validation techniques
    • Data lineage and metadata management
    • Data governance best practices on AWS

  10. Monitoring, Logging, and Security:

    • Monitoring data engineering workflows and services
    • Logging and troubleshooting data pipelines
    • Data security and access control on AWS

  11. Advanced Topics:

    • Machine learning integration with data engineering pipelines
    • Advanced analytics using AWS services (e.g., Amazon Forecast, Amazon QuickSight)
    • Optimizing costs and resource utilization in data engineering solutions

Course Overview

AWS (Amazon Web Services) offers a variety of services and tools for data engineering. These services are designed to help with the collection, storage, processing, and analysis of large volumes of data. Here are some key AWS services commonly used in data engineering:

  1. Amazon S3 (Simple Storage Service): S3 is an object storage service that provides scalable storage for data in the form of objects. It is often used as a data lake or data storage solution for data engineering workloads.

  2. Amazon EMR (Elastic MapReduce): EMR is a managed big data platform that allows you to process and analyze large amounts of data using popular frameworks like Apache Spark, Apache Hadoop, and Presto. It provides an easy way to spin up and manage clusters for distributed data processing.

  3. AWS Glue: Glue is a fully managed extract, transform, and load (ETL) service. It helps automate the process of preparing and loading data for analytics. Glue offers capabilities for data cataloging, data transformation, and job scheduling.

  4. AWS Lambda: Lambda is a serverless computing service that allows you to run code without provisioning or managing servers. It can be used for event-driven data processing or to perform small data transformations or enrichment tasks.

  5. Amazon Redshift: Redshift is a fully managed data warehousing service that enables you to analyze large datasets using SQL queries. It is optimized for online analytical processing (OLAP) and can handle petabytes of data.

  6. Amazon Kinesis: Kinesis is a real-time data streaming service. It allows you to collect, process, and analyze streaming data at scale. Kinesis offers various components, such as Kinesis Data Streams for real-time data ingestion, Kinesis Data Firehose for data delivery to destinations like S3 and Redshift, and Kinesis Data Analytics for real-time data processing.

  7. AWS Data Pipeline: Data Pipeline is a web service for orchestrating and automating the movement and transformation of data across different AWS services and on-premises data sources.

  8. Amazon Athena: Athena is an interactive query service that allows you to analyze data directly from S3 using standard SQL queries. It is a serverless service, so you don't need to manage any infrastructure.

  9. AWS Glue DataBrew: DataBrew is a visual data preparation service that makes it easy for data engineers to clean and transform data for analytics and machine learning. It provides a no-code interface for data profiling, data cleansing, and data transformation tasks.

These are just a few examples of the AWS services available for data engineering. Depending on your specific requirements, you may also use other services like AWS Batch, AWS Step Functions, Amazon DynamoDB, and others to build robust data engineering pipelines on AWS.

Faq’s

  • There is no specific technology background required.

Our Trainers have highly experience in Support, Implementation and Rollout projects real time solutions on different scenarios and expert in their professionals. BESTWAY Technologies verifies their technical background and experience.

We  record each live class session you undergo through this training and we will share the recordings of each class.

Yes we will schedule a demo class as per the student convenient time by sharing live online streaming access either through Gotomeeting or Webex..

Trainer will provide detailed installation of required Software through Environment/Server Access to the students and we ensure practical real-time experience and training by providing all the utilities required for the in-depth understanding of the course. 

If you are enrolled in classes and you have paid fees, but want to cancel the registration for certain reason, it can be done within 48 hours of initial registration. Please make a note that refunds will be processed within 25 days of prior request.

  • We are one of the best AWS Data Engineering online training providers in the world, We have learning AWS Data Engineering customers from India, USA, Singapore, Canada, UK, UAE, Australia, New Zealand, Qatar, South Africa, Malaysia, Saudi Arabia, Mexico, Ireland, Denmark, Sweden and other parts of the world. We are located in India. Offering Online Training in Cities like Hyderabad, Bangalore, Delhi, Mumbai, Chennai, Pune, Kolkata, Ahmedabad, Patna, Jaipur, Lucknow, Kochi, Indore, Chandigarh, Bhopal, SÅ«rat, Kanpur, Coimbatore, Visakhapatnam, Vadodara, Gurgaon, Guwahati, Ludhiana, Allahabad, Nagpur, Noida, Mysore, Ranchi, Bhubaneswar, Faridabad, Raipur, Vijayawada, Jamshedpur, Hubli, Tirupati, Guntur, Kakinada, Rajahmundry, Nellore, Anantapur, Eluru, Warangal, Nizāmābād, Secunderabad, Salem, Trivandrum, kerala, Hubli, Bellary, Gulbarga, Hospet, Tumkur, Thane, Navi Mumbai, Kalyan, Nashik, Aurangabad, Solapur, Gandhinagar, Shenzhen, Hong Kong, Tokyo, Yokohama, Nagoya, Fukuoka, Kobe, Copenhagen, Osaka, Kyoto, Nairobi Kenya, Mombasa, Kisumu, Lagos Nigeria, Ibadan, Abuja, Benin, Sydney, New York, New jersey, Melbourne, Dallas, Adelaide, Perth, Brisbane, London, Paris, Berlin, Vienna, Barcelona, Rome, Madrid, Prague, Munich, Milan, Bucharest, Istanbul, Moscow, Birmingham, Seattle, Baltimore, San Jose, San Marcos, Franklin, Chicago, Philadelphia, Jacksonville, Towson, Minneapolis, Los Angeles, Davidson, Murfreesboro, Houston, San Francisco, Atlanta, Alexandria, San Diego, Washington DC, Sunnyvale, Santa clara, Carlsbad, Tacoma, California, St. Louis, Edison, Raleigh, Nashville, Bellevue, Austin, Charlotte, Garland, Raleigh-Cary, Boston, Salt Lake City, Orlando, Fort Lauderdale, Miami, Gilbert, Tempe, Chandler, Scottsdale, Peoria, Honolulu, Columbus, Plano, Toronto, Montreal, Calgary, Edmonton, Saint John, Vancouver, Richmond, Mississauga, Saskatoon, Kingston, Kelowna, Cape Town, Johannesburg, Durban, Dubbai, Abu Dhabi , Sharjah, Riyadh, Jeddah, Sanaa, Aden, Yemen, Muscat Oman, Kuwait, Doha, Brisbane, Wellington, Auckland, Kuala Lumpur, George Town, Jurong East etc… Hyderabad - Ameerpet, SR Nagar, KPHB, Gachibowli, Dilsukhnagar, madhapur, tarnaka, kukatpally, himayat nagar, Bangalore - Banashankari, Bannerghata Road, Basaveswara Nagar, BTM Layout, Domlur, Electronic city, H S R Layout, Indira Nagar, J P Nagar, Jaya Nagar, K R Puram, Koramangala, Krishnarajapuram, Madivala, Malleswaram, Marathahalli, Mathikere, R T Nagar, Rajaji Nagar, Ramamurthy Nagar, Richmond Road, Shivaji Nagar, Vijaya Nagar, White Field

yes all the training sessions will be a live online streaming using either through gotomeeting or Webex you will be shared with live meeting access while session starts.

Yes, there are some group discount available if group contain more than two.

 

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Reviews

AWS Data Engineering Rated 4.8 based on 5 reviews.

By: Devika Sharma, Rating:
I had a revelation after taking the AWS Data Engineering course. The programme stressed the value of data quality, security, and governance in addition to covering the technical components. The learning process was enhanced by the trainer sharing of real-world problems and solutions. I feel competent in creating salable, reliable data engineering on AWS after finishing this course. I strongly advise aspiring data engineers to take this course!

By: Rani Thakur, Rating:
With great hopes, I registered in the AWS Data Engineering course at Bestway technologies, and it did not dissapoint! A wide range of data engineering principles were addressed in the programme, and the hands-on labs were excellent for practical instruction. The instructor were helpful and competent, swiftly responding to all of our questions. I was comfortable building and putting AWS data engineering into use. Definitely a must-read for anyone interested in a career in data engineering!

By: Deepika Reddy, Rating:
I found the AWS Data Engineering to be of great value as a data professional. The information was current & compliant with best practises in the field. I gained the courage to use the knowledge in my projects right away thanks to the hands-on exercises with AWS tools. The trainer were gentle and entertaining, offering tailored advice as needed. The sessions on data streaming and analytics were my favorites. This course is the best option if you want to become an expert in data engineering.

By: Roshan, Rating:
The AWS Data Engineering Online Training in Hyderabad, India, led by Trainer Mr. Suresh, was exceptional! Mr. Suresh's expertise and teaching style were outstanding. The course content was comprehensive, and Mr. Suresh's guidance during practical exercises was invaluable. This training has significantly elevated my skills in AWS Data Engineering.

By: Abhishek, Rating:
I can't speak highly enough of the AWS Data Engineering Online Training in Hyderabad, India, with Trainer Mr. Suresh. His knowledge and passion for AWS Data Engineering shone through in every session. The course content was well-structured, and Mr. Suresh's real-world insights made a significant difference. This training has prepared me exceptionally well for AWS Data Engineering projects and certifications. Highly recommended!

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