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Big data ‘must be made more accessible’
One of the key challenges facing data scientists working with large volumes of information in the coming years will be to make sure these resources are also able to be utilized by other members of staff without expertise in analytics.
It was noted by Mare Lucas, chief operating officer at Serendipity, in an article for Wired that while these specialists will have an important role to play in the future of big data analytics, it will be important for companies to also look at how they can ‘consumerize’ their solutions to make them easier for anyone to use.
For instance, it would be highly beneficial for individuals to be able to ask a query in natural language and have the analytics platform interpret that, look at its large data sets and provide an answer in the most relevant way possible, with visualizations that can be understood by non-IT professionals.
This could be an important next step, as Gartner has predicted that by 2016, 70 percent of the world’s leading vendors of business intelligence solutions will have incorporated spoken work and natural languages capabilities.
“Improving natural language queries is essential to the consumerization of big data, as it better enables everyday business users to ask questions of their analytics tool in an intuitive format and receive the most relevant and meaningful visualization results,” Ms Lucas stated.
Gartner predicts that the progression of the technology will move to voice-enabled commands first, before moving on to natural language for spoken or text SQL queries.
While this will not diminish the role of skilled data scientists, who will still be required to analyze large data sets in-depth, enabling business users to ask simple questions quickly and without specific training can deliver large benefits to enterprises.
As a result, Ms Lucas observed the solutions are becoming a fixture in parts of organizations where the use of analytics may never have been considered in the past.
For example, chief finance officers are interested by the prospect of being able to pick apart financial data and view it in ways not previously imagined, while marketing executives are using the information to better study customer buying behavior and feedback.
However, in order to see these benefits, individuals across a company need to appreciate what big data can do for them. Therefore, vendors and IT professionals need to demystify the technology and help business units gain a greater understanding of what the technology can do for their departments.
“Organizations that have relied on relational databases may be hesitant to embrace open source big data platforms such as Hadoop,” Ms Lucas said. “Providers must work with enterprise customers to educate the user base on big data so that pessimism doesn’t undermine deployment before it even gets off the ground.”
Getting this right is likely to be essential for any company that wants to make the use of big data a success. Recent research from KPMG suggested many firms are not currently meeting the full potential of this because they do not know how to make the leap from being a gatherer of data to a user of insight.