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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 Tuple: Here're 2 Ways to Calculate Sum Easily

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Python tuple is nothing but a set of data. It can have an 'n' number of elements. Here, in my example, the tuple has 20 Elements. The below logic helps you to calculate the sum of its 20 Elements easily.  A tuple is simply a set, and it can have both positive and negative Elements. So, don't worry. You can calculate the sum even the tuple has negative numbers. Here are 2 Ways You can calculate Sum Display sum after adding each element Display sum at once   Python Logic: #1 Method - The Print Displays Sum in Vertcle after Adding Each Element my_tuple = (1,20, -30, 50, 10, 11, 6, 7, 22, 88, 10, 20, 565, 121, 211, 5, 2, 18, 20, 21) sum = 0 for index in my_tuple:             sum = sum+ index          print("sum of elements:", sum) Note*** Here the print statement is within the For Loop. You May Also Like: How to Use For Loop  in Python Complete Tutorial Python Logic: #2 Method - The Print Displays Total Sum at...
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