Big data is undergoing a revolution. The technology is coming to a point of maturation, in which users have suddenly realized the purpose of storing and analyzing huge volumes of data. That purpose is to put the data to action.
This might seem obvious, but the solutions for handling big data have largely focused on the mechanics of handling large volumes rather than how that data will inform business decisions. In the past, the main strategy has been to pull in as much data as possible, with the hope that the future will somehow make certain data relevant, even if it’s not clear how that will happen.
While it’s true that data often takes on new meaning when viewed in context, the resources to support these “data lakes” often seem to turn a blind eye to the reality of whether the data is ever deemed worthy of the investment. The problem is that the lake is becoming so deep and wide that companies can’t manage it.
A New Vision for Big Data
Business and IT leaders are coming to a place where they recognize that it’s time for a mindset shift. The focus must be on operational and transformative objectives that provide value from big data. Effective use of big data must include optimizing business processes, like automating manual tasks, as well as using it to create new business models, which is ultimately more likely to have an impact on future growth.
In essence, data has no value without action. It’s only in context that data has anything to offer, and this concept takes a bit of adjusting to for IT professionals. Data lakes are, in general, an IT-oriented technology. The approach to data needs to become business outcome-oriented in order for big data to have any value.
Data insights need to be processed to the point of action, and then delivered to the person in the organization that’s positioned to put them to action. When attempting to operationalize data for action, it’s important to approach it from a business perspective, not an IT perspective.
The eventual path many organizations hope to take arrives at artificial intelligence (AI). It’s important that as businesses progress down this path, they don’t miss opportunities to take action with data that will better inform AI initiatives. There’s the collecting of the data, but there’s also the middle step before taking action in which data is observed for patterns. That’s the critical step for AI being able to predict future behaviors and respond accordingly.
It’s becoming more and more clear that big data has the potential to drive business innovation, but it needs to be handled not in IT and mechanics terms, but in terms of business outcomes.
To learn more about leveraging big data for your business objectives, contact usat Enterprise Visions. We can help you access the right solutions that take your data from merely being stored for later use to taking action for future growth opportunities.