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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...
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AWS Certified Developer: Eligibility Criteria

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The below is complete eligibility criteria is as follows- One or more years of hands-on experience designing and maintaining an AWS-based application.

In-depth knowledge of at least one high-level programming language. Understanding of core AWS services, uses, and basic architecture best practices.
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Proficiency in designing, developing, and deploying cloud-based solutions using AWS.

Experience with developing and maintaining applications written for Amazon Simple Storage Service, Amazon DynamoDB, Amazon Simple Queue Service, Amazon Simple Notification Service, Amazon Simple Workflow Service, AWS Elastic Beanstalk, and AWS CloudFormation.







Related: AWS Basics for Software Engineer

The requirement for Developer Exam

  • Professional experience using AWS technology
  • Hands-on experience programming with AWS APIs
  • Understanding of AWS Security best practices
  • Understanding of automation and AWS deployment tools
  • Understanding storage options and their underlying consistency models
  • Excellent understanding of at least one
  • Understanding of stateless and loosely coupled distributed applications
  • Familiarity developing with RESTful API interfaces
  • Basic understanding of relational and non-relational databases
  • Familiarity with messaging & queuing services These training courses or other equivalent methodologies will assist in exam preparation:
  • Developing on AWS (aws.amazon.com/training/developing)
  • In-depth knowledge or training in at least one high-level programming language

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Comments

  1. infosavvy0July 29, 2020 at 5:20 PM

    Nice post! It is really very helpful for us. If anyone want to know the details about AWS

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