It’s not surprising then that the November 2013 report ‘Big Data Analytics: Adoption and employment trends’, by e-skills UK and SAS, said over 90% of organizations believed boosting their big data analytics talent would help them reach profit. But, more than 70% of the businesses surveyed said they found it difficult to recruit the specialists they needed. The situation could well get worse. According to research group, Gartner, by 2015, there will be 4.4m jobs created worldwide that are related to Big Data, and even more will be created outside of IT.
But the skills picture for big data is confusing: on the one hand, doom-and-gloom merchants warn that we’re on the brink of a massive skills shortage. Others say we should just relax; the shortage will not be anywhere near that major.
It’s not surprising there’s some confusion. While all agree that big data is the new business IT paradigm, we’re still on the nursery slopes in working out what to do about it and every supplier will put their own spin on the issue. But whatever the supplier line, the important things is that before you begin to build the in-house skills, you need to be crystal clear what big data means to your business, what your strategy is to cope with it and how, what and who you need to action that strategy.
Analyzing big data can be complex, requiring gifted mathematicians coupled with deep business knowledge as well as programming expertise. That’s a rare mix of skills to find, and by no means an exhaustive list of attributes needed, making those individuals both expensive and highly poachable.
There’s also been a lot of hype surrounding a new breed of data guru, the data scientist, who supposedly has all the big data skills you require to weave their magic with your big data. But these might not be the right option for your organization.
Put simply, yes. While data scientists can help organization manage and analyze these vast quantities of data, the real value will be seen organizations can successfully democratize data.
By making data solely the purview of the data scientists, ironically organizations can be making siloes in the very places they need to remove them. If only data scientists can successfully analyze data and extract insight, organizations will simply be shifting the issues of time-consuming and labor-intensive reporting and analytics to another area of the business.
The true key to unlocking the value of data is to have the right tools in place to enable anyone in the organization to conduct analysis according to their needs, whether on a deep, technical level, or for a higher-level view.
By placing these tools in the domain of the many rather than the few, organizations can reap the benefits and get the best of both worlds as departmental knowledge and insight can be enriched with relevant data (“big” or not) to drive decision-making capabilities.
Big data will eventually lose the ‘big’ qualifier as coping with larger and larger volumes of data will simply be what everyone has to cope with. Data analysis is all about taking a fresh approach to data and seeing patterns and possibilities that others can’t. So take a fresh approach to your analysis teams.