A Guide to the Future of Analytics
The emergence of big data has been one of the main reasons behind the transformation of modern businesses. Big data has opened up new opportunities that would have seemed unimaginable only a few years ago. In these times, making the right investments in data and analytics can deliver the greatest business impact. Data as the main driver of digital transformation has gained much more strategic importance in an insight-driven business environment. IT companies have now finally started to take advantage of data’s full potential while looking to achieve the goals of a full-fledged data-driven organization. Against this backdrop, it seems today there is no lack of intelligent devices that are treating data analysis in a new light.
IBM has been a front-runner in the race to create smart systems, focusing primarily on predictive analytics and cognitive techniques. The technology leader recently unveiled a super-computer called which as the ability to ingest data at the rate of 67 million pages a second.
The purpose of this latest IBM innovation is to establish a question and answer dialogue between it and humans, whereby Watson will run unimaginable amounts of data and answer in plain speech and in real time.
Watson is a unique offering from IBM that aims to bridge the gap between humans and machines by applying Artificial Intelligence techniques. The next obvious question is how Watson would capture huge amounts of data and turn into an interface for human-machine communication. Perhaps, it should not be a surprise because analytics has made it possible to capture volumes of unstructured data from across the value chain.
Google has always been considered an innovator in this type of interaction. Google has long empowered data scientists to look beyond the complexities of traditional data management techniques. Moreover, Google technology initiatives have helped to build a greater understanding of data possibilities among IT organizations. The way NetSuite operates its cloud-based ERP system is another example which show how large volumes of data can be presented in a way that supports informed decision-making and human comprehension. 2017 could be the year of data analytics, and Data engineers can lead new approaches to data analysis by thinking more boldly about how to capture the missing human element in the field of analytics.