By Bob Renner, CEO, Liaison Technologies
In my last post, I detailed the differences between application-centric and data-centric IT models. To recap, continuing with my solar system analogy, in an application-centric model, applications are the star around which IT functionality revolves. In a data-centric model, data is the star and applications the planets. Data-centric IT models recognize that data in its purest form should be allowed to drive business strategy without being artificially constrained by the often-arbitrary requirements of applications.
In all likelihood, your organization’s IT architecture is currently application-centric. Most are as this is the traditional model that has only recently begun to break down due to the explosion of data. So how do you begin the interstellar voyage from one ‘star’ to the other?
The exact nature of your mission will be different from any other. But there are some universal commonalities that you can begin to ponder. For example, start thinking about the journey of data across your organization and the operations that need to happen along the way in order to make the most of this resource.
I like to organize these data operations into three basic classifications, which I call the ‘taxonomy of data.’ In a data-centric IT environment, the three basic data operation classifications are:
- Data capture
- Data management
- Data analysis
Let’s take a closer look at each one of these data operations.
Data capture is the collection of data. In a data-centric IT model, this operation can be performed by any number of loosely coupled applications chosen for their ability to serve the unique needs of the data. To borrow from big data’s 3V concept, these unique needs can encompass a multitude of variables including high volumes of data, data coming in at high velocity, or data variety (i.e. unstructured data).
Data management is the transportation and refinement of data. A source-agnostic utility or platform accepts and consolidates the data; performs value-added services on the data such as integration, harmonization, and cleansing; and then provides access to or emits enhanced, aggregated data sets. This operation is increasingly being outsourced to third-party data management providers, like Liaison, as businesses realize the value in leveraging IT architectures built exactly for this purpose, rather than embarking on the not-insignificant effort of building and maintaining in-house systems.
Data analysis is the transformation of data into value (i.e. actionable insight). In this operation, the consolidated and enriched data is consumed and converted into value by data analysis tools such as information portals or BI software. You may not unravel the mystery of the universe’s origins, but you could discover how trending YouTube videos affect sales, how weather influences food consumption at sports stadiums, or the real-time hotspots of illegal deforestation.
Obviously, your voyage to data centricity isn’t going to happen overnight. But if you begin realigning your IT environment now as opportunities arise, you’re sure to get there before NASA’s newest spaceship, Orion, delivers astronauts to Mars.
Intrigued? I invite you to attend our upcoming webinar on this topic: