Spread the Good

It warmed my heart (and it was extremely cold here this a.m., in FLORIDA, so I needed that warmth) to hear a piece on NPR regarding math degrees and BIG DATA. Reportedly, mathematicians can make sense of this data for businesses. No doubt this is true, and “intense curiosity to understand what’s behind the data is a common trait amongst such mathematicians.” I would argue people with BIG LOVE of research (like us – that is, a love of prospect research and data mining) all have this trait as well, with or without math degrees. How many nonprofits and higher ed foundations look for (and hire) mathematicians? Perhaps you should share this NPR story with your HR department, to adjust the requirements for certain development positions. Hey, I’m not suggesting you stop hiring those of us with library science, information studies, history, and/or English degrees. Read on and see why math majors should be included, too.

McKinsey released their results of a study earlier this year about the impact of big data across many different industry sectors. Among their findings, a retailer using Big Data to the full could increase its operating margin by more than 60%. Another – “access to data is critical – companies will increasingly need to integrate information from multiple data sources, often from third parties, and the incentives have to be in place to enable this.” I know, you might be saying, “Lori, we are not a retailer” (I could argue that point, but that’s another discussion) OR “Lori, we are not a company” (and I could also discuss that point too…). So, instead, take a look at Big Data for the Common Good. Or take a looksee at Geoff Livingston’s piece on Big Data.

OK, you’ve waded this far in. Now let’s define big data. Well, go ahead – use Bing or Google. I’ll wait…

One piece about which I think everyone can agree: to handle Big Data, your organization, in addition to the appropriate personnel, needs a scalable solution. Business Intelligence (aka fundraising intelligence) will rely upon your organization’s ability to handle the explosion of data that has already happened not to mention the data being created right now as you are reading this. All you have to do is take a look at the conferences across the globe regarding Big Data. Take a look at the speaker lineup – notice the company names. What pattern do you see? You’ll recall David mentioned in an earlier post about unstructured data. Big Data solutions should be able to take into account the unfielded data all organizations (whether nonprofit or for-profit) capture. Think about those free text fields in trip reports. Think about those prospect profiles and thumbnail sketches.

If I still worked within a higher ed foundation, I would find my way – fast – to the math department. Your prospect research department, if your nonprofit is fortunate enough to have one, could learn a thing or Fk, k > 2: O(1/e2 m1-2/k).

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