Can collaborative data modeling improve market research?
DECEMBER 27, 2011 – A major aspect of conducting market research is being flexible and learning to approach a problem from several different angles. This is true in the field of analytics too, according to the Spotfire Blog, and in order to find a fresh perspective, teams of researchers and analysts often brainstorm to find solutions to “even the most vexing issues.”
Enter collaborative data modeling. The blog points to Gartner’s prediction for 2012 that more organizations will be collecting huge quantities of data from social networking websites, and will be applying that insight to their strategic business decisions.
Yet learning how to properly process and act upon these insights will be a challenge, Gartner said, so organizations will need to learn how to foster teamwork, adopt collaborative data modeling and pool their resources.
The blog notes that online communities offer one solution to the problem of having more data than people to analyze it, allowing data scientists, visualization experts and others in the field to talk shop and share tips.
According to Spotfire, these new forums will offer more “opportunities for companies of all sizes to leverage the collective wisdom of the crowd.” The blog acknowledges that there is still a need for some refinement and development, since the sites are not perfect.
However, they still “offer data scientists a terrific chance to connect with each other across all corners of the globe to brainstorm on approaches to tackling vexing problems,” according to the news outlet.
In a March column cited by Spotfire, David Menninger discussed the revolution that is sweeping the business intelligence technology market. He also stressed the importance of collaboration between users to create better processes for communicating with and sending information to customers and partners.
“Technology exists today to apply analytics to all information regardless of volume, data type and origin,” Menninger writes. “However, organizations still struggle to evaluate alternatives for supporting large data sets including location data, event data and machine-generated data, all of which can contribute to more accurate analyses of their business processes.”
He points to mobile technology as one of the factors that is transforming enterprises, creating a higher demand for constant BI access and ever more data for companies to process. That, combined with social media, facilitates the conversation aspect in collaboration.
These tools will offer some solutions for sharing information and conversation tracking, he says, but companies will also have to push for more developments and innovations surrounding their methods of sharing and processing analytics.