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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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Networking in IoT age for big opportunities (1 of 3)

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Networking is common in the age of IOT. The basics I want to say are networking means connecting objects together. The networking is possible with wires and without cables. The without cables you can say as wireless.

How Computers Connected

  • Computers are connected by using fiber cables. Each computer is connected by cable to a central switch, which connects to the rest of the network  
  • The advantage of wireless networking is no cables required. In a wireless network, most cables and switches are moot. Radio transmitters and receivers take the place of cables.
  • Networking software must be installed. This drives networking functioning.

Benefits of network

  1. To share resources
  2. Sharing information
  3. Sharing applications

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