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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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Python: Do While Loop Real Examples

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While it is one of the loops in Python. The specialty is it never be false. You already know that in my previous post I have shared For Loop in Python . The for loop can be false. I am giving here one best example: print("Help! My computer doesn't work!") while True: print("Does the computer make any sounds (fans, etc.)") choice = input(" or show any lights? (y/n):") In the above logic, while is always true. When in input user can give 'Y/N'. if choice == 'n': # The computer does not have power print (" Do not show lights") if choice == 'y': # It is power plugged in print ("show lights") So, while is always true. Based on input the while loop works. Python is having the below list of Keywords. Pythons Reserved Words The Python reserved words are: and, exec, not, assert, finally, or, break, for, pass, class, form, print, continue, global, raise, def, if,...
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