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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 jobs Booming in Technology area

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The Internet of Things helps enable proactive data access from any connected device.The Internet of Things represents an evolution in which objects are capable of interacting with other objects. Hospitals can monitor and regulate pacemakers long distance, factories can automatically address production line issues and hotels can adjust temperature and lighting according to a guest's preferences, to name just a few examples. 
Iot advantages
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Furthermore, as the number of devices connected to the Internet continues to grow exponentially, your organization's ability to send, receive, gather, analyze and respond to events from any connected device increases as well. IBM solutions can help put the Internet of Things to work for you by giving you the ability to: 
  • connect millions of objects and millions of events.
  • unlock information in systems of record. 
  • support new systems of interaction with people, mobile devices, sensors, machines and applications. 
  • optimize business results with local decision making. 
  • conduct business virtually anywhere and anytime, using almost any device. 
  • receive and respond to events in near-real time. Read more at IBM-here

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