According to IBM 90% of all data has been created within the last two years, and 80% of it is unstructured: documents, videos, images, e-mails, etc. No wonder Big Data is a Big Topic of conversation these days.
This all sounds amazing, but to me it feels like technology is just catching up to reality. Most of the world’s data has always been unstructured: thoughts and memories in people’s minds; carvings on stone; or printed on a piece of paper. The concept of structured data came along when databases appeared and data was required to fit neatly within distinct fields. Numbers, dates, names, and addresses were welcomed. Notes, comments, and documents were exiled to live either outside of the database or in unsearchable (and often seemingly unreachable) places within it.
Every time you log-on to your favorite donor management system you experience the consequences of this “Unstructured Data NOT Welcomed†legacy. You search for a person’s name, and if that person is...
Next year will be the 30th anniversary of Marts & Lundy introducing the fundraising world to automated prospect screening. Their Electronic Screening® service, programmed by my old friend Charles Headley, changed forever how organizations found their best prospects.
The goal was simple: find people in your database who have the capacity to give more than they are now, and the propensity to make a gift. You would think the reaction to this was universally positive. After all, the classic peer review sessions were breaking down under the weight of the volume of people, and the growing diversity of wealth.
But it turned out the first thing people wanted to see was their current top prospects. If they were not at the top then it must not work. This is a challenge screening companies have faced ever since.
Grenzebach Glier came along and solved the problem by heavily weighting past giving as the measure of affinity. Voila! Your current best donors were your future best...
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...
So, here it is, two days post Thanksgiving weekend - yes, we've successfully prolonged this one-day holiday into an entire weekend, and if your school system is like ours, it's a 5-day weekend, according to my teenage son, which made yesterday quite the rude awakening for said teenage son. In reflecting on our holiday, and writing this blog post, I came across my dinner preparation to-do list, as follows:
Make cranberry sauce
 Start turkey
 Put turkey in oven no later than 2 p.m.
Mix together mama’s sweet potato casserole
Take rolls out of freezer
Start Brussels sprouts
Start pumpkin soup when turkey is resting
Open pinot noir
Make turkey gravy
Put in rolls and sweet potato casserole
Of course, as with all cooks, the recipes were tweaked to the tastes of the cook (moi) and the family members. We enjoyed our Thanksgiving meal in the evening, which is unlike my traditional family T-day schedule, a noonish feasting so one may graze the rest of the day. Why, you ask, did we...