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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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How to Modernize Software Applications with AI (2 of 3)

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Creating like human intelligence in devices, the software also called artificial intelligence. Ambient intelligence because of its interactivity with the user is an attractive medium to advertisers. Some examples:
IoT Devices
Human Intelligence
Adswitch

This could be a large step forward for the advertising industry as not all adverts are able to reach their potential customers and now advertisers can target the correct market as the advert will adapt to the changing environment.

Ambient Intelligence
  1. The application of Ambient Intelligence in the Home Automation field is likely to continue as it can be simply allowed to disappear into the environment without homeowners having to notice it carrying out the complex instructions that would make lives easier.
  2.  It is also likely that newer methods of interacting with the interfaces will be a hot area for some time to come as speech and touch have specific limitations. It can be argued that one of the main reasons that ambient intelligence has not been implemented widely today is due to the constraints that come with it. 
  3. For instance, to have every object made intelligent requires mass-produced nano components yet nanotechnology is complex and hard to work with, the time it takes to develop devices with nanotechnology is much longer due to the fact that everything that is in the design must be built on a very small. 
  4. There is also the aspect of security with Ambient Intelligence and if people are not willing to trust the ambient technology then it will fail. In Ambient Intelligent environments, information not only resides in one node but is distributed between many therefore every single node within the system needs to be protected.
Wakeup Alarm

Some of these products are at the early stages and some are in niche markets. Take, for instance, the award-winning 'Philips Wake-Up Light'.
  • This alarm clock with a 300 lux light bulb can be used by anyone to help them wake up more naturally (by dawn simulation - so replicating waking up as nature intended - by sunlight). This means people feel more refreshed and ready to hit the day rather than being woken abruptly by a loud, sudden beeping.
  • In fact, you can set it to 3 natural sounds (morning birds, seashore, pond) or your favorite digital FM radio station. What is the relationship between Ambient Computing and an alarm clock? Well, the clue may be in the manufacturers of this product ‥‥Philips.
  • One such Intelligent Advertising project is a switch that is designed to change when someone approaches the advert as their gender and age will be determined to evaluate an advertisement suitable to the user. 
  • For instance, as the elderly woman moves to the head of the queue, she is shown the advert for retirement homes and when the teenage boy heads the queue, some computer games adverts will play. Ambient intelligence is beginning to have an influence on the marketplace today.

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