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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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10 Excusive Steps You need for Web Scrapping

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Here're ten Python technics to clean the scraped data. The scraped  Text has unwanted hidden data . So, as part of cleaning it try to remove these ten in your data. 10 Steps for Web scrapping Data is prime input for  text analytics projects . After cleaning, you can feed to Machine/Deep Learning systems. Removing HTML tags Tokenization Removing unnecessary tokens and stop-words Handling contractions Correcting spelling errors Stemming Lemmatization Tagging Chunking Parsing 10 Technics to Clean Text in Python 1. Removing HTML tags The unstructured text contains a lot of noise ( data from web pages, blogs, and online repositories.)when you use web/screen scraping.  The HTML tags, JavaScript, and Iframe tags typically don't add much value to understanding and analyzing text. Our purpose is to remove HTML tags, and other noise. 2. Tokenization Tokens are independent and minimal textual components. And have a definite syntax and semantics. A paragraph of text or a text documen...
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