FACT: I am a Data Wrangler, with a Serious Data Scavenging Addiction
By Jeff Mard, Vice President, HMG Company
“The best way to use a person’s data is to return it back to them as a useful product.”
DJ Patil, Chief Data Scientist @ United States of America
On the heels of my note on ‘Big Data’, I’ve started thinking about data on a more micro level. Whether we realize it or not, every one of us is a data scavenger or data wrangler of sorts, depending on how we are using the data and to what end. Humans are creatures of curiosity. It’s in our nature.
Data scavengers (where most of us fall) are the information curators, the aggregators and the purveyors. They use data as a way to build interpersonal connections and solve problems. Conversely, data wranglers are tasked with looking at large sets of data in their native form and manipulating them to uncover patterns and predict behavior (what we commonly refer to as a Data Scientist).
Why bring this up for a LinkedIn post? Well, because I think it is very important that you pause and think about how data is acquired via a zillion methods and then consider how you can use it to talk to your target audience. I believe that understanding how a person ‘acquires data’ has the potential to make a profound effect on how the data should be presented (err, paid to be presented).
Not to create a moment of inception, but think about the data you capture when you start to build your data strategy. Do not collect data if you have no use for the data… only collect the data when you know it can be put to good use.
Hmm, so let us think about the different personas that make us up today’s #DataAddicts:
- Lurker – Passive enough that they feel comfort in seeing other addicts’ data shared. Often times, this addict keeps their data close to their vest. HINT: gotta do the double opt-in here.
- Entertainer – Wishes to gain popularity among peers with Internet trends and fun facts. Might post a video of a skateboarding bulldog to see how many ‘likes’ it will get. HINT: all about the meta data in content.
- Educator – Searches for and shares information others might find useful, or to advance a cause (e.g. emails a news article about the latest presidential debates). HINT: reputable sources like Harvard Business Review.
- Innovator – Takes what they’ve learned and observed and creates solutions to an organization’s challenges (e.g. suggests volunteer incentive program to boost employee morale). HINT: Check places like PSFK and Next Web.)
- Digger – Mines and analyzes disparate data sets to draw conclusions (e.g. analyzing voice-of-customer to make recommendations to improve a company’s product or service). HINT: look at popular trade shows (Tech Crunch Disrupt, webinars, reverse engineer how they gain traction/participation.
Companies like SavvyRoo have even found their niche by developing visual mapping tools to aid all these data consumers and spur The Next Big Idea. And wrangler tools from Trifacta and Google Open Refine promise to cut down on the time it takes to prepare data for analysis. However, one theme remains consistent thru the equation… there is an immense power behind our discoveries and ideas and the motivations that we have to share.
I’m continued to be fascinated by data. Like to get a better feel for the data ecosystem… then check out this visual from Lukas Biewald @ Computerworld:
So go on… create great data and wrap in a vessel that is most appealing to your audience. Then go on and get some data and as DJ Patil said… return the data back to the user as a useful product!
Thank you for reading my post. If you have thoughts, love to discuss in comments below… or email me. If you like it… well you know what to do… like it, share it… rinse repeat. Cheers!