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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...

Python Default Argument is Self Why do We Need it

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Python self as default argument, here is the reason. Below, you will find an example and the importance of self-argument. Structure of a class The default argument is self. The self-argument states the function belongs to the class that we refer to here. Access to class members' details of one member to another is possible through self-argument. So self-argument is mandatory. class <name of the class>: def <function name>(<arguments>): ... <members> Self Argument A python class consists of methods these also called functions. The default self-argument you need to supply in all the class methods . Python class with self argument class employee:      def getdata(self):           self.name=input('Enter name\t:')           self.age=input('Enter age\t:')     def putdata(self):           print('Name\t:',self.name)          ...