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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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JSON Material to Download Now

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JSON or JavaScript Object Notation is a lightweight is a text-based open standard designed for human-readable data interchange. Conventions used by JSON are known to programmers which include C, C++, Java, Python, Perl, etc.

JSON Quick Guide for legacy developers
Photo Credit: Srini

JSON Material to Download Now.

  • JSON stands for JavaScript Object Notation. This format was specified by Douglas Crockford. This was designed for human-readable data interchange JSON has been extended from the JavaScript scripting language.
  • JSON filename extension is .json . JSON Internet Media type is application/JSON
  • The Uniform Type Identifier is public.json.

JSON Quick Guide to Download

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