Josh Birkholz

Redefining fundraising for the 21st Century.

Posting on analytics, technology, visualizations, fundraising, and other unrelated things I find interesting like Doctor Who, sci fi wierdness, crazy new ideas, and interesting people.

Author of Fundraising Analytics
Principal at Bentz Whaley Flessner

Founder of the analytics group donorcast

Acting Debut Top Chef Donorcast

Fan Favorite Data Hoarders Video

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What does it take to make the 1% in NYC?

From McKinsey

The University of California, Berkeley, recently announced an online Master of Data Science degree, and, in August, IBM unveiled a Big Data educational partnership with more than a thousand colleges and universities. Such academic forays into data science are noteworthy because they are exceptional. Over the long term, we’re hopeful that these sorts of initiatives will prove to be the first of many and that they will at least begin to meet the demand for data science talent.

The most effective Big Data specialists are “translators” capable of bridging different business functions and effectively communicating between them.

For now, however, many companies are trying to fill their ranks with candidates holding degrees in computer science, industrial engineering, and statistics. But there are just not enough of them, so employers need to improvise.

Read the entire article here

To learn more about staffing your fundraising program with analytics staffing, contact BWF.


5 Techniques to COAST through Prospect Development reporting.

My brilliant colleague, Bond Lammey, and I recently wrote this article for Advancing Philanthropy Magazine.  Check it out and let me know what you think.

Read the article here

Learn more about our counsel and services in prospect development at

Great reading list.  Several of these are favorites of mine.
Want to know more about the business, sociology, or nitty—gritty of data science? Here are some great books on the discipline to get you on your way…

See the list here

Thanks cloudofdata for this summary. 

Derrick Harris takes a look at the ongoing debate about data science and data scientists.

We also touched on this at the Big Data Breakfast I moderated in London earlier this week. Coverage in Computing highlighted comments about the exaggeration of the data science skills gap, and also stressed the importance of teamwork.

There clearly are rockstar data scientists out there, individuals with a deep grasp of the technologies, awesome powers of communication, and a solid grasp of the business landscape within which their organisation operates. But there aren’t very many of them. The real point coming through from everyone on the panel was that you shouldn’t let this worry you. Not everyone needs to be - or to employ - a rockstar. Solid teams are often good enough (maybe even better, as they’re more sustainable).

And in many (perhaps most?) lines of business, true data-driven transformation may be an expensive or otherwise unattainable distraction. So building a data science capability in those businesses may be a task for another day…

Disclosure: Rackspace covered the cost of my participation in this event.

Read more

Thanks vedha for describing this approach.  Everyone, have a read…

To move from “data” to “insights” you have to look at more than one metric. However moving from an “insight” to telling a “story” requires understanding the synergies between metrics — just like a plot has multiple characters in play and the story comes to life through the interwoven relationships…

Read it here

By Nicole Wallace

A revolution has begun: Data are transforming the nonprofit world.

The new number crunching is fundamentally changing the way charities make decisions about programs, solicit contributions, and push for social change.

Read the article here

Kevin Slavin at PopTech on Debunking Luck. Discussing The Monte Carlo Theory - we don’t need to have the theory, the data can offer us a different way in. And how computational efficiency turns what we perceive as chance and luck into something controllable and beatable. And what this in turn does to our world.

Worth watching.  Most enjoyable!


Interesting list.  I would add Tableau to it.  But, this article is worth a scan.

Click here to see the article and list

According to one projection, the sales of big-data-related products and services grew to more than $18 billion in 2013. Companies can now map your genome, find the best fit for clothing, and improve students’ grades, to name a few examples. Consumers, meanwhile, value privacy more than ever.

See the list here