"Business managers want to choose the technology that best meets their needs and to have the freedom to walk away from that technology to move on to the next thing," says Cullen. In a world where execs will one day have the power to provision cloud-based resources for a new business initiative by clicking through a couple of configuration screens, the need for enterprise architects who are glorified implementers will wane. The job of the business architect is to arm managers with the knowledge they need to choose wisely.
In some organizations, enterprise architects with the right experience and disposition may simply take on the business architect role, whether or not they change titles. Nonetheless, says Cullen, "If you want to know about a hot role for 2012, it's definitely business architect."
Big data -- that is, the glut of unstructured or semi-structured information generated by Web clickstreams, system logs, and other event-driven activities -- represents a huge opportunity. Buried in that mountain of data may be invaluable nuggets about customer behavior, security risks, potential system failures, and more. But when you're talking terabytes that double in volume every 18 months, where do you start? That's where the data scientist comes in.
On the business side, data scientists can open up new opportunities by uncovering hidden patterns in unstructured data, such as customer behavior or market cycles. On the dev side, a data scientist can use deep data trends to optimize websites for better customer retention. Within the IT department, a skilled data scientist can spot potential storage cluster failures early or track down security threats through forensic analysis.
"There's now an intellectual consensus in business that the only way to run an enterprise is to use analytics with data scientists to find opportunities," says Norman Nie, CEO of Revolution Analytics, which produces the first commercial application to bring the R data analysis programming language into the business world. Because of the immense opportunity for strategic insight buried in all that data, says Nie, "corporations now have an unlimited demand for people with background in quantitative analysis."
The R programming language is just one tool in the data scientist's toolbox. Others range from business analytics software from established providers like SAS Institute to IBM's new InfoSphere platform to analytics technology acquired in EMC's recent acquisitions of Greenplum and Isilon Systems. Just last May, EMC Greenplum hosted the first ever Data Scientist Summit.
According to Nie, data science jobs will require workers with a spectrum of skills, from entry-level data cleaners to the high-level statisticians, yielding a range of opportunities for newcomers to the field. As the business world gets increasingly social, the demand for people to plumb the depths of all that social networking clickstream data will only increase. The cliché going around is that "data is the new oil." A career in refining that raw material sounds like a good bet.