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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...

Top Differences Read Today Agile vs Waterfall model

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The Agile and Waterfall both models are popular in Software development. The Agile model is so flexible compared to the waterfall model. The top differences between Waterfall and Agile give you a clear understanding of both processes. Waterfall Model The traditional model is a waterfall. It has less flexibility. Expensive and time-consuming model. Less scalable to meet the demand of customer requirements. The approach is top-down. Starting from requirements one has to finish all the stages, till deployment to complete one cycle. With a small change in requirement, one has to follow all the stages till deployment. The waterfall model creates idleness in resource management. Agile Model The agile model is excellent for the rapid deployment of small changes The small split requirements you can call sprints Less idleness in resource management. Scope for complete team involvement. Faster delivery makes clients happy. You can deploy changes related to compliance or re...