The concept of data gravity has been around for several years. Dave McCrory first wrote about the idea several years ago and currently maintains a phenomenal blog called Data Gravity where he goes into detail to describe the concept. It is a great read and well worth your time if you are interested in data and data science concepts.
The high-level notion of data gravity is that data is more valuable as it grows in terms volume and context to other data sources, such as software applications and connected devices that record and store data. Take for example the wearable market that has exploded over the last couple of years. The data that those devices collect and store, by itself, may not be that valuable. However, when it is combined with additional context like who you are, your age, weight, blood pressure and what activity you were doing to cause the data to be captured and all of a sudden that data grows in importance and relevance.
Another example is one of the large SaaS platform Salesforce.com. Many of the Fortune 500 use Salesforce as a SaaS-based sales management tool. The ability to massively scale to support thousands of concurrent users and capacity to integrate the data with many other sources of data is one central value proposition of platforms like Salesforce. You can enrich data with other sources of data such as Hoover’s information, custom data sources and the fact that you can integrate your Salesforce data with others that are in your firm’s supply chain make it a treasured tool for these enterprises. This use case is another prime example of the construct of data gravity. This data, all living in the Salesforce cloud (because most all of it does not live in your firm’s data center) is extremely valuable. However, if you decided to leave Salesforce and move to another solution or perhaps to an in-house solution, the data all of a sudden loses much of its context. It is no longer as valuable as it was in the Salesforce cloud where it had an ecosystem of other data with which to add additional context to it. Sales data, marketing data, external market and trend data, the list goes on. You pull that data out, most likely in a comma separated file, and it instantly loses value.
As applications and connected devices continue to proliferate closer to those who use it, data gravity will continue to grow in importance. This movement of applications and associated data to the cloud is often referred to moving to the “edge,” or closer to the consumer and supporting applications and out of the traditional four walls of a data center.
The movement of data and applications to the network edge requires new ways of looking at network architecture. Security is of paramount importance as well. The response time of applications and their ability to consume, process, and render information about all of this data becomes more important and more sensitive to application latency. The firm I work for, Equinix, is solving for this new network and application paradigm with something known as Interconnection Oriented Architecture (IOA). IOA provides a roadmap for firms that are moving their workloads to the cloud and are looking for a roadmap of how to execute on this journey to the secure, interconnected cloud.
In subsequent posts, I will share some of my insight and use cases on how this IOA Architecture is helping firms make their move to the cloud and the business value they realize from it.