Data Model

In software engineering, the term data model is used in two related senses. In the sense covered by this article, it is a description of the objects represented by a computer system together with their properties and relationships; these are typically "real world" objects such as products, suppliers, customers, and orders. In the second sense, covered by the article database model, it means a collection of concepts and rules used in defining data models: for example the relational model uses relations and tuples, while the network model uses records, sets, and fields.
Posts about Data Model
  • 5 Prescriptions For A Healthy Customer Data Plan

    … When I say the words “marketing data” what’s the first thing that comes to mind? If you’re like most marketers – it’s probably math, numbers, analytics; basically the statistical information that provides us insight into becoming more effective. Yuk. It’s like medicine – hard to swallow but we know we need to take it to get better. But it’s…

    Robert Rose/ Content Marketing Institute- 15 readers -
  • How Facebook Sped Up News Feed on iOS

    … News Feed is the starting point for most Facebook users’ journeys through the social network, but it began slowing down on the flagship iOS application due to steps that were taken to speed up other components of the app. iOS developer Adam Ernst explained what steps were taken to quicken the loading of News Feed in a post on the Facebook…

    David Cohen/ AllFacebookin Social Facebook How To's- 5 readers -
  • VIDEOS: Facebook’s @Scale 2014, Data Track

    Anshul Jaiswal, Engineering Manager at Facebook; Weizhe Shi, Software Engineer at Facebook and Will Wirth, Product Analyst at Facebook Facebook has grown tremendously on mobile. In this talk we’ll discuss how realtime mobile analytics helped accelerate the growth by enabling faster feedback loops du ...

    David Cohen/ AllFacebookin Facebook YouTube- 4 readers -
  • RTB’s fatal flaw is it’s too slow

    … Google figures out what ad to show in search. The quality of the decisions these systems make is reliant on: 1) more static data sets with higher signal-to-noise ratio to help train the models and 2) the ability to learn based on outcomes. That means the most intelligent systems must use first-party data and backend data that will be looped back…

    Digidayin Google Facebook Twitter- 7 readers -