The last thing organizations want is more complexity in their applications and data centers. That’s why the cloud migration can’t happen quickly enough.
We all have our personal center of gravity — that metaphorical place where we feel sure of ourselves and who we are. It could be a physical place or merely a state of mind, but one thing’s for sure — when your center of gravity shifts, everything shifts with it. That’s literally what’s happening with data in the enterprise.
A CTO named Dave McCrory is credited with coining the term “data gravity,” a concept that suggests the number of services and applications grows in parallel to the volume of information being managed by a particular organization. For companies considering their business intelligence (BI) strategy, data gravity deserves some major consideration, unless you’re willing to keep on building out your own data centers.
“While the data in the cloud environment continues to increase, migrating to the cloud without considering the length and strength of next application might cause issues in the future,” a recent article on Host Review pointed out.
“It’s always recommended to take into account long-term effects of your user base’s growth along with the amount of resources the application will demand. In addition, there are some crucial considerations that can’t be overlooked such as the effect data gravity will have on other applications; issues that will come up if the data cannot be migrated, and so on. Exploring different essential areas can help avoid problems later.”
Financial executives may see these kinds of things as the IT department’s problem, but you also have to consider the end results that BI tools offer. In ‘Solving Data Gravity Pain,’ Information Management suggests an interface that will be familiar to many CFOs will benefit from a thoughtful approach to using the cloud:
Most analytics projects are highly iterative in nature. Dashboards enlighten a decision maker that in turn sends action items for adjustment. The business process being monitored by a dashboard is continuously tuned for optimal performance at various points from various data sources. To effectively deliver iterative intelligence, data and added context flows rapidly back and forth between apps, data sources and the analytical assets regardless of where they live…on-premises or in the cloud.
A post on MinuteHack said much the same thing, calling out data gravity as a major tech trend for 2017. While hybrid environments (cloud applications as well as those on-premise) will still be in place for a while, it said, “cloud analytics will increasingly represent a faster and more scalable solution.”
Every organization will need to decide for itself how quickly it needs to manage this transition, but the quicker everyone understands data gravity, the better they’ll be able to gauge how strong its pull on your BI deployment will ultimately be.