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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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UNIX Shell script to know input is integer or not

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Unix jobs, career
(Apply hot Unix jobs)
Unix Shell script to know input is integer or not.

$vi  prg1
clear
echo  "enter  a  number"
read  x
y='expr  $x  %  2'
if  test  $y  -eq  0
then
     echo  "Number  is  even"
else
    echo  "Number  is  odd"
fi



Running Script


$sh prg1
enter a number
11
Number is odd
$sh  prg1
enter  a  number
12
Number  is  even






































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