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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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Print Dictionary Values Simplified Logic

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Here's for loop logic that says how to use Dictionary to get its data. I will present here how to use it as input In for loop. You can also call Dictionary as Map, Hash, or Associative array. Print dictionary values Below is my example. I have created a simple Dictionary called 'store.' Then, I will get its data using for-loop. Here's my previous post Python -  How to Lookup Dictionary By Key . Dictionary example Store = { "rao" : 1, "srini' : 2} For-loop logic for key in store:       print (key, store[key]) Laptop batteries can last longer if you charge them up to only 80% instead of the full 100%. - By Lifehack.org Real-time result The execution of for loop showed here. It's much simple. Just use the code as I did. You'll get the desired result quickly. References Python for Everybody: Exploring Data in Python 3 SOFT SKILLS for a BIG IMPACT: Banish Self-Doubt, Improve Workplace Ethics
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