How to Achieve Real-Time Value from Big Data

As of the present time, it is no hidden secret anymore that organizations have to move beyond conventional practices of analytic cycles that are limited to schema management and data transformation. The need of the hour is to bring together business analytics with production operations to create value and benefits in real time. And this is what Hadoop technologies purport to do. It wouldn’t be wrong to say that the revolution in data-driven business has been powered by Hadoop.

It should be noted that real time value isn’t just about big data or fast data separately, both of them have to go hand-in-hand. The question to ask is whether there is any architectural approach that can facilitate this.

To throw some light on this issue, some retrospection will be required. Data formats have been largely dictated by applications, However, it has become imperative for data to support different computer engines, freely. While ETL (Extract, Transform, Load) is better suited for quickly growing data formats which follow a load and go philosophy, there have to be efforts to remove latency from systems plagued by it.

This kind of approach will require overhauling the management of the entire hardware in the data center, and not just those associated with Hadoop. Besides the hardware, resources have to be managed globally as well. Then a cohesive system of data storage is needed which any application can access.

The architectural overhaul leads us to think what kind of data cycle should the organization work with. Well, the dynamic nature of real time demands a data-to-action plan, just data-to-insight wouldn’t be sufficient for a business plan that looks at what happened 10 minutes ago to know what action it has to take in the next 10 minutes.

In a nutshell, it is the time for businesses which can find actionable analytics in real time. And this will be achieved by bringing together analytics and operations on the same table, eliminate latency, speed up scalability and integrate capabilities with SQL, BI, and the likes.

Business owners also need to keep in mind that a complete facelift of the business doesn’t just mean ramping up the tools they work with, but, to keep reinventing the business process, to rethink how to use the tools in the best manner possible. This is because once users get to experience operations on the basis of big data in real time, they will only be wanting more and faster of it.

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