Browse by year:
February - 2014 - issue > CEO Spotlight
Convincing the Enterprises to Collaborate Data A Challenge
Gurjeet Singh
Wednesday, February 5, 2014
Analysts estimate that enterprises spent $34 billion on big data investments in 2013 and it is believed that data holds immense potential. Unfortunately, we are nowhere near ready to unlock its potential as most enterprises are simply applying the same thinking and technologies in newer packages to solve their problems. We most certainly have advanced our abilities to store and process data. What are holding us back are people problems. We rely on people to ask the right questions of data and identify the important connections between millions of data points which could take years and millions if not billions of dollars.

Our Topological Data Analysis (TDA) software is helping the worlds biggest and most sophisticated organizations discover breakthroughs that will change how we all live and work. Over the last few months, major financial institutions like Citibank have found previously unknown sources of fraud. Research hospitals (Mt. Sinai and UCSF) and pharmaceutical companies have uncovered new insights around traumatic brain injury, autism, and e-Coli. And GE, the world’s oldest company has adopted Ayasdi’s technology as a centerpiece for GE’s Industrial Internet strategy to become a data-driven company and unlock billions on cost savings and new revenue opportunities.

Challenge of Collaboration

In our space, one of the challenges is convincing those who own the data to collaborate. In most enterprises, the data generated by a functional area ends up being the property of that group. This leads to two problems. First, it is difficult to get a "complete" view of the data. Consider all the silos and systems that hold data: CRM, ticketing, bug tracking, fulfillment and the like. Getting all the relevant systems to even talk to each other is a huge challenge. Second, there’s significant cultural dissonance within organizations. Typically, each group controlling a data silo ends up caring more about their power and place in a department rather than the success of the organization as a whole. Organizations need to pool their data to find the answers to and get a complete view of their data.

Taken a step further, research institutions work on parallel or at least similar studies to solve the same problem but will not share their data. When you consider the possibilities of gaining insights into cancers, brain injuries and other diseases, the potential of mining large, longitudinal data sets is a powerful idea that could benefit millions of people.

The Wall of Communication

Another big hurdle is the lack of communication between data scientists and business users. Said another way, the analytical gap between a data scientist and a business user is so wide that even communicating insights poses a problem. Anything that does not make intuitive sense is often regarded with skepticism, or not fully understood, by business users, which can lead to missed opportunities. Entrepreneurs need to build solutions that can bridge this gap and enable domain experts to work like data scientists.

Share on LinkedIn