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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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3 Top Books to Read for Data Analytics

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The financial domain has openings for analytics jobs. The top financial domains are Banking, Payments, and credit cards.  The skills you need to work in data analytics are SAS, UNIX, Python, and JavaScript. I have selected three books for beginners of data analysts. The Best Books are on: SAS UNIX Python  3 Top Books to Read for Data Analytics 1. SAS best book  I found one best book that is little SAS . This covers examples and complex macros you need for your job. The best-selling Little SAS Book just got even better. Readers worldwide study this easy-to-follow book to help them learn the basics of SAS programming. Now Rebecca Ottesen has teamed up with the original authors, Lora Delwiche, and Susan Slaughter, to provide a new way to challenge and improve your SAS skills through thought-provoking questions, exercises, and projects. 2. UNIX book The  basic commands you will get everywhere . The way of executing Macros or shell scripts is really what you nee...
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