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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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How to learn Tableau best way with self Study tutorials

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#Tips To Mastering Tableau Self Study Video Tutorials
#Tips To Mastering Tableau Self Study Video Tutorials
The Tableau training website offers a multitude of resources for Tableau users with many of the videos being brief and addressing specific topics. This self-study syllabus organizes those videos to help you find the training you need on specific topics quickly. Tableau 9 for Data Science Engineers.

 To learn any Software Tool, you need to follow these steps:
  1. Tutorials - Either on-line or class room
  2. Books -Read theory from the scratch
  3. Hands on Training - Just practice what you learnt
  4. Materials -Written by experienced developers
  5. Blogs/Websites/Forums give you much insights
The below link contains valuable video tutorials. You can learn Tableau quickly in a just few days.

Take Video Lessons Here

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