Not all data scientists need a math or economics background. It's time to think outside the box come hiring time.
While IT directors immerse themselves in data scientists' resumes, hiring budgets, and team structures with the goal of staying competitive, they may be missing a big piece of the puzzle.
Rather than just having teams of big data specialists who hail from the traditional backgrounds of statistics, theoretical math, applied math, and/or econometrics, a hiring tip for IT directors is to mix things up. Hire outside of the traditional box. That could mean a biologist, a psychologist, or a philosopher -- depending on the business needs and the kind of mind set that complements the other team members.
The promise of big data is alluring -- important, game-changing decisions can be analyzed and made based on quantitative facts that can be proven like never before. And businesses are right to be allocating a bigger part of their budgets to big data.
But IT directors and other business leaders shouldn’t get so lost in all that data and miss sight of diversity and creativity and different perspectives that have been known to drive innovation. While big data and analytics teams are certainly at the center of this proliferating trend, their successes depend on their ability to derive meaningful insights that ultimately impact the bottom line positively. And to do this, they need to interface effectively across other business divisions like marketing and sales.
Big data is only truly effective for business innovation if you know how to identify unexpected insights within the data. That's the trick question -- how do you make the most of big data without losing out on the secret spice that leads to breakthrough innovations?
For starters, we can look at the typical qualifications for a big data "scientist" who has the traditional background of statistics, theoretical math, applied math, and/or econometrics. Knowing the data scientist teams are full of these skills, IT directors can then look at other skills that the team lacks such as communications, project management, and planning.
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business won’t wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.