Image from: Ermek/Shutterstock
Think back, way back…. to the days when you filled out those multiple choice bubble surveys for school to figure out what you were going to be when you grew up. While those days are long behind us, I’m sure that there was no clear path between those penciled in tests and our current career choices. Regardless of how we arrived in our current data-centric careers it’s an extremely exciting time to be working with data. That said, I have been seeing some very exciting data-centric trends across a number of industries that I’m excited to share.
Data gets its own conference!
Data is getting attention in a big way, so much so that O’Reilly has sponsored a bi-coastal conference called StrataConf around it. If you’re looking for insight into the ways in which data is becoming more important in roles across industries, just take a look at the who should attend page: Who should attend Strataconf. Notice how decision makers, programers, designers, product managers, and even journalists and sociologist are featured in the list? As our ability and inclination to measure information increases, we’ll need to scale this with groups of people educated to interpret and act on insights within those data sets.
Speaking of Careers
In the recent past we’ve started to think of marketing as a left-brained practice, just as much as a right brained one. If you take a look at the charts below, furnished by indeed.com (a job search company) you’ll notice that there has been significant growth in job descriptions looking for individuals specializing in data fields and with large increases in job postings for data scientist, analysis, competitive analysis, and competitive intelligence. How cool is it that younger generations now have new job titles related to data oriented fields like, “data scientist”? You have to admit that, “I want to be a data scientist, when I grow up.” has a really nice ring to it!
If you take a look at the charts below you’ll note that these terms are exploding in frequency within postings as well as increasing in number. With uncertainty in markets it seems these trends are likely to continue, likely in parallel with the pressure to perform better with less resources companies will look to get an edge with competitive data.
data scientist jobs
Competitive Analysis jobs
competitive Intelligence jobs
Image from: sellingpix/Shutterstock
While growth in data-centric and competitive analysis careers is extremely exciting, it leaves us all susceptible to making mistakes typical of young and rapidly growing industries. Some of the trends that are of particular concern include our obsession with shiny new technologies, not understanding our data sources and not supporting weak sources with supplemental information when needed.
While the method of delivering data in real-time is exciting, it’s not always the most actionable. We get obsessed with this idea that we need to operate in the instant, which does not account for the time it takes to analyze the best approach for action. Real-time data one day will have it’s day in the sun, however our beginning approaches will mostly result in attempting to compute relevant results from raw data streams full of noisy information. While we’re making progress in this area, it’s important to keep in mind that real-time does not equate more actionable or better. Just because information is collected and reported on over time doesn’t mean it isn’t highly valuable.
Know your source
I often encounter two types of individuals in my line of work. Those that must understand their data sources, and those that do not have a firm grasp on the data sets they source and interpret. I’m certain it’s not difficult to surmise which type typically has more successful results, but I’d like to go a step further and talk about a concerning habit.
We can often be blind sided when our data sources become biased – which is why knowing how the information you’re looking at is collected and being able to speak to the source is important. Particularly when looking to have data trends tell a story, it’s valuable to know the weaknesses of your sources so that you can support your hypothesis with supplemental information. What is concerning is how rarely I see this happening and even more rarely do I hear people talking about this as a problem. It’s almost as if we’ve adopted a line of thinking that there can only be one “true” and “correct” source. Most data sets, no matter how painstakingly collected, can not be considered “perfect” or “complete” because typically some assumptions are made in the process of making sense of the information collected that can inherently influence the data being interpreted.
Supplement your sources
One of my personal pet-peeves is when bloggers and journalists proclaim a source weak before the jump, only to continue to comment on it without due research diligence. Positioning your data source as weak ultimately harms your credibility, because you find it necessary to waste your audience’s time and validate a source deemed weak with unsupported commentary. We should be cognizant of when we do this, in both our internal and external communications and thus make a habit of supporting sources when needed.
If you’ve had a chance to take a look at the StrataConf videos you’ll see that there are plenty of people thinking creatively about what we can do with data sources. While it may seem like data oriented studies are left-brained logical pursuits, I’m certain there is plenty of room for creatives. As our roles within our companies become more data focused it’ll be important to effectively and creatively communicate our ideas. I think that it’s for this reason that infographics have been so increasingly popular recently, but let’s not limit our selves to visual communication. Data or information can be an extremely powerful and influential tool, and if applied creatively it can impact the world. As practitioners we should look to push ourselves to research, implement, and test a disruptive or non-intuitive approach to a difficult problem from time to time. While I outlined some concerns above about the future, what could most impact our ability to innovate is the inability to expand ourselves outside of our comfort zones.
In closing as people in data-centric careers, may we always think creatively, fail quickly, and push ourselves to improve from the lessons of our mistakes every day.
“Sometimes when you innovate, you make mistakes. It is best to admit them quickly, and get on with improving your other innovations.” – Steve Jobs
This post was inspired by SmartData Collective’s Analytics Blogarama so I’d encourage you to visit them and check out the other posts.
Lindsey Mark works in Client Relations at Compete and is responsible for the strategic development of client retention and support policies for compete.com, with a focus on education and training efforts. She graduated from Rochester Institute of Technology in Rochester, NY so she's a certified technology junkie and open source advocate. When she's not thinking about marketing or training digital 007's at compete, she's doing yoga & blogging about gluten-free diet and lifestyle. Find Lindsey on Twitter as @linji, Google Plus as Lindsey Mark or connect with her via LinkedIn.