Covering Disruptive Technology Powering Business in The Digital Age

 The mantra echoes from classrooms to boardrooms. The topics range from health policy and healthcare transformation to the Panama papers—“it is all about the data.” Unprecedented proliferation of data particularly by ways of mobile and cellular technologies creates business opportunities every day. Single automobiles for instance are expected to generate gigabytes of data every second; auto manufacturers are increasingly attempting to tackle this growth in demand for internet of things—data transmission, storage, and processing capacity.

These datawaves are the new cyberstead—real estate for the taking on an opening cyber frontier. Here vendors scramble for a piece of the action, name and rename stuff for sales and marketing purposes. Big Data—Clouds, Lakes—the entire landscape with Peaks and Valleys probably looming on the horizon, all designed to convince buyers that existing skills and technologies cannot handle the Yodabytes deluge. The race is on to manipulate market forces and differentiate product offerings to attempt to ensure competitive advantage and survival. The carnival barkers promise the holy grail of push-button system solutions and cradle-to-grave data capture, storage, structuring, integration, security, maintenance, and good-looking reports—for a modest fee!Beyond the hype and noise is very little meat, said Abhay Parasnis, Adobe Systems’ chief technology officer, at the company‘s annual Data Science Symposium in San Jose at Adobe’s offices in May. There is power in these data assets, he said, and along with the multipoint mobile world and the cloud, they represent a paradigm shift and a disruption in all industries. Data science—previously known as statistics—provides the skills required to capitalize on these assets, to clean them and cluster. Adobe‘s strategy is to create a tool for businesses that transforms what Harvard Business Review called the sexiest job of the 21st century into data scientist in a box or Data Science as a Service. To build that foundation, the company has teamed up with academia and created and funded roughly 200 hundred internships. Half of these internships and collaborations with academic researchers are having direct impact on Adobe‘s business. The symposium, the third of its kind, brought together presentations of some of the research projects.

Marketing and marketing professionals are Adobe‘s target market for these efforts. The firm has added a marketing cloud to their product platform and say they are in the process of building a standardized data model for marketers and marketing applications. In his prophetic 1994 book, The Naked Consumer,Erik Larson writes about the principles of data collection and data use in marketing, about the power of zip-code cluster analysis to predict consumer tastes and behavior, and sell them to advertisers. Advertising is king, Adobe‘s Senior Engineering Director Sandeep Nawathe told EE Times, advertising is what pays everything today.

In healthcare, the peddling of Data Science and Big Data is still somewhat along the lines of solutions in search of a problem. This industry has its share of ambitious evangelists who promise more data will make medical costs public and transparent and Big Data will pave the way for Precision Medicine with treatments tailored for individual patients based on their genetic makeup. Claims that are perhaps inevitable in due time, yet others point out all the digital low hanging fruit in healthcare is gone and all new cutting edge projects and initiatives will be hard to execute, require colossal investment in time and money, and demand rethinking of medical care.

The predicted impact of Big Data on Population Health—the improved health of all humans—at Big Data and Healthcare Analytics Forum last month organized by the Healthcare Information and Management Systems Society  and Healthcare IT News also evoked sentiments of the ever elusive paradigm shift. However, a recurring theme at the forum rejected the notion of a Big Data label as productive means to an end. Participants in “genius” panel discussions described clinical data as deep or broad and clinical intelligence hence a function of rigor and accuracy rather than statistical probabilities and cluster analyses of Big Data. The panelists urged thinking about the spectrum of data in healthcare rather than size. The healthcare story is one of variety where small data for that matter is critical for daily medical practice.

In spite of increased digitization of Electronic Health Records (EHR) and a surge in implementations of EHR systems around the country, analysis of EHR data hardly exists industrywide.  Jeanne Huddleston, a professor of medicine and an industrial engineer who led a major quality improvement program at the Mayo Clinic, offered a sober observation. “We can make things worse,” said Dr. Huddleston, “trying to find cool things in the data.  It is important to find out what is missing in the data but it takes more than the purity of the data to make this thing work.  If care givers only started reading each other notes.”  Perhaps then their last patient on the hospital rounds might not succumb to sepsis because they had not read he had the symptoms, and perhaps medical errors might move down the list as the third leading cause of death in the United States. That is big.

This article was originally published on www. eetimes.com and can be viewed in full