In today’s scenario of fast changing business dynamics, successful organizations are keeping themselves well paced up to embrace that change and move ahead towards profitability and increased productivity.
In this scenario, Big Data has emerged as a big tool to create that differentiation. However, organizations must keep their flexibility intact in order to gain big from big data implementations.
Big data is about working with data towards the advantage of an enterprise, and achieve game-changing business agility with the help of capturing, analyzing, and acting upon vast amounts of diverse, fast-moving data sets.
And there are some key business practices which can enable enterprise to generate big advantage while utilizing big data all across their organization. Today’s big data implementations are extracting information from multiple sources of data coming from systems, and software, the key lies in deploying big data solutions keeping in mind, optimal performance, cost, and energy efficiency.
Data coming in from cellphones, tablets, phablets and other connected devices plus the social media data envelope is generating unprecedented volumes of data, and they represent only part of the global online population. Helping organizations in this regard, big data analytics is presenting unique opportunities to become the heartbeat of such data sets and continuously differentiate sound of business from the noise of clutter.
Additionally, we are already moving towards the “Internet of Things,” where a large number of networked sensors in shopping malls, businesses, homes, cars, and public places, take data generation to completely different levels of imagination. And hence creating business logic from big data is becoming all the more important today.
Business Mojo from Big Data
There are many ways to extract business value from big data implementations. And this is applicable across multiple set of enterprise verticals.
Big data techniques such as interactive querying and predictive analysis are creating that much needed differentiation for the enterprise to extract the right value from their big data implementations.
With today’s improved data warehousing improvements, real-time analytics of data can operate on much larger scale and more varied data sets can be involved, hence this is extending the value of existing BI investments and intelligently amalgamating it more effectively with new big data solutions.
Predictive analytics is another technique by which organizations can get better value addition from big data. Today’s next generation analytic techniques go beyond data mining and visualization to determine not only what has happened and why, but to predict what is likely to happen based on all available data, including real-time streams from external data sets and sources.
