What is Giving Compass?
We connect donors to learning resources and ways to support community-led solutions. Learn more about us.
Giving Compass' Take:
• Adriana Paz takes a closer look at how a number of philanthropists and nonprofit organizations are using their resources to grow the pool of professional data scientists and support other nonprofits as they adopt data-informed decision making.
• How can donors invest in academic programs that train students to enter the workforce as data scientists?
• Here's why data science classes are a big hit in high schools.
In a world where 294 billion emails are sent daily, and roughly 3.8 million internet searches are performed every minute (Desjardins, 2019b, 2019a), there is no question about the power, importance, and value of data.
A huge proportion of the data we have is not purposefully created by users. Rather, it is passively generated and collected as a byproduct of everyday interactions with digital products or services, including mobile phones, credit cards, and social media. This trail of unconventional data reflecting users’ habits or behaviors is called exhaust data, or a digital footprint (Kirkpatrick, 2011). And as the world’s access to new and more sophisticated technology expands, this data is playing a much larger and more complex role in our lives and work.
[A]s the world’s access to new and more sophisticated technology expands, [exhaust] data is playing a much larger and more complex role in our lives and work.
Data science is the multi-disciplinary field that emerged from the increasing need to extract knowledge faster and more efficiently from both structured (i.e., organized and formatted) and unstructured data. The scientific methods, processes, and algorithms utilized in data science are not themselves new concepts. The main differences in their contemporary application come from current levels of computing capabilities and the massive amounts of data available for analysis.
Businesses were quick to embrace the power of data and data science to maximize profit. As a sector, they developed and implemented systems to convert their data into usable information to help create new products, optimize services, and reduce costs. The narrative, however, has been different for organizations that work for social change, as limited resources often keep them from taking full advantage of this data revolution.
Read the full article about data science for social impact by Adriana Paz at Johnson Center.