IT organizations need a clear understanding of what the data means to its users. Whether that data is obtained from a tablet, smartphone, or even a mainframe, data definition needs to be obvious and meaningful to everyone concerned.
Applications are written to manage data and to help transform data into knowledge. When designing data for an application, developers work from a vision of the data that the app will use and/or need to do its job. For example:
A data model, a blueprint of an application’s entities, attributes and relationships, helps to visualize those entities, attributes, and relationships and communicate how the data works together. Think of an entity as a physical object, such as a customer or a product (the tee shirt above), or something more abstract such as a flight reservation.
Attributes are the entity’s characteristics (like the tee shirt’s size), and relationships describe associations among entities, such as the relationship between a customer and the online customer service rep.
The challenge, of course, is designing applications that integrate with and add value to a company’s already existing portfolio of applications. When the business rules or end-user requirements of one department’s application differ from those in another department’s application, the applications’ data models are incompatible.
That’s when developers need to step back to gain a broader vision and establish corporate-wide data definitions. These definitions are essential in helping to enforce standards that facilitate application integration.
Chief Analytics Officer Spring 2017
15% off with code MP15
Big Data and Analytics for Healthcare Philadelphia
$200 off with code DATA200
10% off with code 7WDATASMX
Data Science Congress 2017
20% off with code 7wdata_DSC2017
20% off with code AIP17-7WDATA-20