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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 Things Top Communication Protocols

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The IoT envisions hundreds or thousands of end-devices with sensing, actuating, processing, and communication capabilities able to be connected to the Internet. These devices can be directly connected using cellular technologies such as 2G/3G/Long Term Evolution and beyond (5G) or they can be connected through a gateway, forming a local area network, to get connection to the Internet.

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The latter is the case where the end-devices usually form Machine to Machine (M2M) networks using various radio technologies, such as Zigbee (based on the IEEE 802.15.4 Standard), Wi-Fi (based on
the IEEE 802.11 Standard), 6LowPAN over Zigbee (IPv6 over Low Power Personal Area Regardless the specific wireless technology used to deploy the M2M network, all the end-devices should make their data available to the Internet. 

This can be achieved either by sending the information to a proprietary web server accessible from the Internet or by employing the cloud.

#The role of protocols in IoT
#The role of protocols in IoT

Online platforms such as ThingSpeak.com or Open.Sen.se, among any other alternatives, are virtual clouds able to receive, store, and process data. Besides acting as remote data bases, M2M clouds also offer the following key services:

1. They offer Application Programming Interfaces (API) with built-in functions for end-users, thus providing the option to monitor and control end-devices remotely from a client device.

2. They act as asynchronous intermediate nodes between the end-devices and final applications running on devices such as smart phones, tablets or desktops. Our paper focuses on the protocols that handle the communication between the gateways, the public Internet, and the final applications (Figure 1). They are application layer protocols that are used to update online servers with the latest end-device values but also to carry commands from applications to the end-device actuators.

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