and vet each other more quickly, buoyed by information run through high-performance computing clusters that calculate risk in a given context.
Data for good begins on a grassroots level
When I reflect on my professional journey over the past 25 years, I owe much to my early years working in a tiny startup. I developed collaboration skills there, by wearing multiple hats so I could view a problem from different angles. Most productive technologists and data scientists can probably trace their success back to sharpening their ability to examine data critically and coming up with platforms, tools, and methods to aggregate and link the data quickly, meaningfully, and accurately. Such skills are more necessary than ever today as we encounter new challenges and data that require new tools and methods.
Harvesting actionable data insights for the greater good starts in one's own organization or community. Innovation and meetings of the minds between cross-functional areas are critical to nudge a theory into a practical and useful deliverable. Our company holds internal symposia, where we share what we've learned about the data sets and tools we are working on. This confluence of ideas across departments is innovation in the making. For instance, one person's hypothesis about certain individuals' access to government benefits in correlation to certain assets that the person owned was a catalyst that led to new tools for the prevention of fraud, waste, and abuse.
The discovery of such linkages between entities (such as research papers) can save time and eliminate lengthy processes. Recommendation engines powered by these kinds of techniques, for instance, can transform a search for the right information into a real-time suggestion. Recently, a scientist, desperate for one last piece of information to connect the dots, turned to Elsevier's Science Direct and instantly discovered exactly what he was looking for. His Twitter feed expressed his satisfaction: "I'd like to buy the maker of that recommendation engine a beer!"
Connections made at the personal or local level can fuel tremendous opportunities. For instance, US municipalities are aggregating crime rates, utility information, population rates, and other data to create "heat maps" that help homebuyers make purchasing decisions and governments address infrastructure and funding issues. The data has always been there, but depicting patterns in a visual way lets users act on it in unprecedented ways. Now individuals are helping fix communities, inspired by the ability to examine information in a way that reveals new possibilities for change.
Forging a path forward
Harnessing data for actionable insights requires talented data scientists who see non-obvious linkages in data. That could be one reason that no single approach to training creates a good data scientist; the next data scientist sitting beside you may be a former marine biologist. Data science is a mindset and a discipline, and new people are being drawn to the field. The use of data for good is happening at the local level, in businesses, and in the world at large. I encourage you to seize the opportunity to be a part of this movement.
If you just look at vendor financials, the enterprise storage business seems stuck in neutral. However, flat revenue numbers mask a scorching pace of technical innovation, ongoing double-digit capacity growth in enterprises, and dramatic changes in how and where businesses store data. Get the 2014 State of Storage report today. (Free registration required.)