AWSDataEngineeringOnlineTraining

  Data Engineering: AWS Prescriptive Guidance AWS (Amazon Web Services) offers a plethora of services and tools that facilitate the collection, storage, processing, and analysis of data. AWS provides prescriptive guidance to help users effectively utilize its services for building robust data engineering pipelines. Here's a high-level overview of prescriptive guidance for data engineering on AWS AWS Data Engineering Online Training Understanding Requirements: Before diving into implementation, it's crucial to have a clear understanding of your data engineering requirements. This involves determining the sources of data, types of data (structured, semi-structured, unstructured), expected volume, velocity, and variety of data, as well as the intended use cases. Choosing the Right Services: AWS offers a wide array of services for data engineering, including: Data Ingestion: AWS Glue, Amazon Kinesis, AWS DataSync Data Storage: Amazon S3, Amazon Redshift, Amazon RDS, ...

  AWS Data Engineering Complete Roadmap AWS data engineering requires a combination of skills in cloud computing, data management, and programming. Here's a comprehensive roadmap to guide you through the essential steps AWS Data Engineering Training Institute Foundation: Understanding Cloud Computing: Learn the basics of cloud computing concepts, especially focusing on AWS services. AWS Fundamentals: Familiarize yourself with core AWS services like EC2, S3, IAM, VPC, etc. Basic Programming: Acquire proficiency in at least one programming language like Python or Java. Data Fundamentals: Data Structures and Algorithms: Develop strong skills in data structures and algorithms, which are fundamental for efficient data processing. Databases: Learn about different types of databases (relational, NoSQL, etc.) and how they are used in data engineering.                      ...