Despite the majority of businesses understanding the importance of big data analytics, and how they can help in the short- and long-term, a recent survey found that most organizations have yet to successfully deploy big data analytics.
According to Lavastorm’s second annual analytic usage, trends, and future initiatives report, 75 percent of businesses have yet to reach big data production, even though 65 percent have invested in analytics services and technologies.
Lavastorm CEO Drew Rockwell explained that far too many companies are struggling with how to maximize big data, and properly incorporate the results into something substantial.
“These survey results underpin how investing in analytics is just the first step,” Rockwell said. “It’s organizations that go the next level by removing complexities from the analytics process and empowering others in the organization, namely business analysts, that are going be able to turn data insights into actionable business enhancements for long-term success.”
Lavastorm reportedly interviewed 495 C-level executives, business analysts, and data scientists and analytics professionals.
Results showed that the investment in analytics was growing rapidly. Specifically, 64.4 percent of those surveyed said that their firm is investing more in analytics this year. However, just 12.6 percent of respondents said their company has completed several big data projects that are now in production.
Eliminating Big Data Concerns
So, if the majority of organizations understand the potential benefits, what could be preventing them from moving forward?
According to the Lavastorm survey, the number one concern for executives that are just experimenting with big data is a shortage of expertise in the field to draw on. With a lack of big data skills, organizations are reluctant to take the plunge since a clear ROI immediately available.
A recent white paper by Ontario Information and Privacy Commissioner Ann Cavoukian, highlighted similar big data concerns. Cavoukian said that it is possible to have big data, while also keeping any sensitive information secure.
“We can protect the privacy of personal information while using data analytics to unlock new insights and innovation to move our organizations forward,” the commissioner wrote in an executive summary accompanying the white paper.
Cavoukian then highlighted several strategies that organizations can adopt in order to advance privacy while pursuing data analytics activities.
One such strategy was data minimization, which “eliminates privacy risk at the earliest stage of the information life cycle.” Essentially, no personally identifiable information is collected until a specific reason is defined.
Big data analytics is not likely to disappear anytime soon, which is why businesses should conduct their own research and see what options best fit their needs.
For example, SiSense is a startup that hopes to make big data analytics accessible to ordinary business users. The company recently announced that it had raised $30 million in C-funding led by DFJ Growth.
SiSense “changes the architecture” of how a user processes big data requests. SiSense uses “In-Chip Elasticube” processing, which is different than previous approaches to looking through cloud-based data solutions, reports TechCrunch.
“That gives users the ability to process terabytes of data from machines with less memory at hand – something that comes in handy in the new generation of computing where people are using devices like tablets and smartphones and pared-down computers to do their work,” the news source said. “That then gets filtered down to dashboards that business analysts and others who are not necessarily trained in data science or engineering can comprehend.”
Last month, PYMNTS.com highlighted a conversation between ShopVisible co-founder and CEO Sean Cook and 3M’s global digital marketing leader Keith Haig. The two explained the importance of businesses – specifically those in the B2B sector – being willing to deconstruct themselves. Without being open to a little disruption, organizations will have a much more difficult time adapting to changing consumer mindsets.
Perhaps the same can be said for technological innovations. Without a willingness to change, businesses could be left behind.