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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 Write Python 'Hello World' Program Quickly and Run it

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The first Python program looks like the below.  I have explained the steps you need to write your first program in Python. My first program: odbchelper.py You can write your program as nameccheck.py module. if authorsFirstName == 'Irv':       teachingPython = True       print 'Pay attention to his wisdom' How to Run Your Python Program python namecheck.py Sample python program if authorsFirstName == 'Irv':      teachingPython = True    print 'Pay attention to his wisdom' The above if condition checks for first name.  In python '==', means equal to. It makes true to teachingPython .  You can start your python program quickly. Really useful for learning and to use it in projects.
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