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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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Internet of Thing Awesome Basics You Need to Read Now: Part 5

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Internet of things can be applied to both Vertical and Horizontal of things: Applications of the Internet of Things (IoT) have spread across an enormously large number of industry sectors. The development of the vertical applications in these sectors is unbalanced.

It is very important to sort out those vertical applications and identify common underpinning technologies that can be used across the board, so that interconnecting, interrelating, and synergized grand integration and new creative, disruptive applications can be achieved.

IoT part 5
IoT part 5
One of the common characteristics of the Internet of Things is that objects in a IoT world have to be instrumented 

Why we need IOT is a fundamental change in the way information is generated, from mostly manual input to massively machine-generated without human intervention.

To achieve such 5A (anything, anywhere, anytime, anyway, anyhow) and 3I (instrumented, interconnected, and intelligent) capabilities, some common, horizontal, general-purpose technologies, standards, and platforms, especially middleware platforms based on common data representations just like the three-tiered application server middleware, HTML language, and HTTP protocol in the Internet/web arena, have to be established to support various vertical applications cost effectively, and new applications can be added to the platform unlimitedly.

Four pillars of IOT
  • RFID - The internet of devices.Example,Radio wave, NFC,IC cards
  • WSN-The internet of transducers. Examples Wireless mess, Bluetooth,Networks, ZigBee
  • M2M - Machine to machine. Examples, Cellular, Fixed networks, WAN, GPRS
  • SCADA-The network of controllers. Example-Wired Field Buses, CanBus,BacNet

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