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4/2/2013
07:58 AM
Doug Henschen
Doug Henschen
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7 Insights On Hiring Data Gurus

Our newest salary survey shows analytics and data-management professionals are in big demand. Whether you are hiring or job hunting, consider these pointers for your search.

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Big Data Analytics Masters Degrees: 20 Top Programs
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Despite the weak economy and zero growth in many IT salary categories, business intelligence (BI), analytics, information-integration and data warehousing professionals are seeing a slow-but-steady rise in income.

Our InformationWeek 2013 U.S. IT Salary Survey reveals that the median BI/analytics staff salary for 2013 is $90,000, up 1.8% from last year, according to 334 respondents in this category. The median BI/analytics manager salary is $119,000, up 2.2% from last year, according to 230 respondents. The full BI/analytics and information management salary report will be published April 19.

In the data integration/data warehousing category, the median staff salary is $104,000, up 1.7% from 2012, according to 152 respondents, and manager salaries are $118,000, up 1.8% from 2012, according to 90 respondents in this category.

[ What comes after big data? Read Big Data, Meet Long Data. ]

Very few of the 22 IT categories we cover have been doing as well or better than these data-savvy professionals in recent years. The exceptions include hot categories such as cloud computing, mobile/wireless and Web security specialists.

Our survey doesn't cover big data scientists as yet, but reports we've seen have these PhD-level analytics experts earning anywhere from $117,500 to $145,000.

Keep in mind that these are median salary figures, and many factors will determine whether you'll pay (or be paid) more or less.

Here are seven insights to keep in mind when hiring or taking a new job.

1. Location matters.

The top pay levels are earned in the Pacific, Northeast and South Atlantic regions, in that order, followed by the Midwest, South Central and Mountain regions. This regional order applies to staff and managers alike, and in both cases the difference between the Mountain and Pacific pay scale is at least $20,000.

2. Age and gender matter.

Older males earn more. It's easily defensible that workers tend to earn more as they move up from the "25 or less" age bracket to "55 and over" because they're gaining experience. But is it fair that women consistently earn less? Female staff in the combined BI/analytics and data integration/data warehousing categories earn $91,000 while their male counterparts earn $100,000. Female managers in these categories earn $110,000 while their male peers earn $133,000. That's just wrong.

3. Creative types earn more than administrators.

It's not spelled out in our data, but employers and consulting firms tell us they don't pay big bucks for keeping the lights on. The top salaries go to those who "know how to manipulate data, look at it in different ways and help customers either impact the bottom line or come up with new offerings," says Ahmar Abbas, VP of global services at Disys, a global IT staffing and services firm with about 4,000 employees. About 10% of these professionals specialize in data warehousing and analytics, and over the last two years Disys has also built up a team of about 140 specialists in big data analysis.

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DAVIDINIL
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DAVIDINIL,
User Rank: Strategist
4/3/2013 | 7:24:29 PM
re: 7 Insights On Hiring Data Gurus
The author writes: But is it fair that women consistently earn less?

It might be fair it might not be. We don't have enough info to make that call. Perhaps the males have more relevant experience. Perhaps the man have more tenure. Example: Women by necessity have to take time out to have children. Men cannot as yet do this. Women typically have less OTJ experience than men for this reason.

We do know that it is well documented that men are better at asking for more money, on an average basis. Could the pay difference be accountable to the idea that men simply ask for more money?

I do know that most people in the business world are rational creatures. They make decisions based more in facts than emotion. I have to believe there is more to the story than businesses simply electing to pay females less. That is just not rational, let alone fair.

The rational business owner in this case would be eagerly snapping up these underpaid females. In fact they would staff the entire company with females exclusively. According to your data and just about every other survey, the females are much less expensive than the males. As a business owner, I would be miles ahead of the competition by hiring females only.

On a superficial level, the data seems to point to unfairness. But the real world is more complex than that. there is more to this story than what we are seeing on the surface.
kburg070
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kburg070,
User Rank: Apprentice
4/2/2013 | 7:13:30 PM
re: 7 Insights On Hiring Data Gurus
I've recently read some research that indicates companies (at least in insurance) are citing "difficulty of finding staff" as the main reason for not being farther along with big data-related initiatives. Doug, do you think that's a valid concern or kind of an excuse?
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