New research by Self-Service Data Analytics firm Alteryx has found that data and analytics are among the most important new skills an employee can have today, with 26% of UK business leaders citing it as the most important skill or competency a potential new employee can have. Overall, 60% said they consider data and analytics skills one of the top two skills, behind only industry experience, which was cited by 69%.
This thirst for analytics skills is reflected in the salary. In the US, the average annual salary of a data scientist is, according to Glassdoor.com, $119,000. Indeed, data analytics knowledge in any role will provide a significant boost to your wage. Stuart Wilson, VP EMEA, Alteryx, Inc, said, ‘Our research found that UK business leaders would be willing to offer a 30% higher salary to someone who is data proficient over one who isn’t.’
The capability for all employees to engage with data and leverage it for insights is being significantly improved as the tools become more user-friendly, requiring less coding and less of a mathematical/computer science background. While practitioners still require some knowledge if they are to truly become involved in data analysis, they do not necessarily need to be ‘boffins’ with a number of PhDs if they are going to enter the field.
We asked six industry professionals how they got into data analysis, and received a variety of responses:
George Sadler, Former Senior Director, Marketing Analytics, eBay:
‘I fell into it, really. I was doing operational strategy and BI work when Dell started heavily investing in social media marketing. They soon ran into the tough ROI questions, and since there were no ‘quants’ in corporate marketing at the time, they looked to the BI teams in the regions. And so, a colleague and I started the social media analytics team (I was employee #2 of what was eventually a 20 person team). Then I inherited a newly consolidated market research team with the logic that listening to customers in social is similar to listening to them in primary and secondary research. This team soon grew its charter again, as Dell launched its first enterprise brand campaign, and we got into econometric models, growing into what is now the marketing sciences team at Dell.’
Dr. Robyn Rap, Business Intelligence Analyst, Indeed.com:
As I was finishing up my doctorate at UT Austin, I realized that my sociological training could be applied to complex business problems beyond academia. It was around then that I was recruited by Indeed to help build out their rapidly growing Business Intelligence team. I love that I get to empower people to help them make better, data-driven decisions; and that my impact is immediate and palpable.
If there is one piece of advice I can give to someone who is interested in a career in Business Intelligence it's this: learn how to program and learn to be comfortable with advanced statistical methods. OK, maybe that's two pieces of advice, but the point still stands. Self-service tools can only get you so far, and knowing the ins and outs enough to build your own tools like we've done at Indeed gives you and your end users a lot more flexibility.
Joel Shapiro, Executive Director of the Program on Data Analytics at Kellogg's School of Management at Northwestern University:
After I majored in physics in college, I took a 'quant-detour' by going to law school and briefly working as an attorney. I was completely a fish out of water. One senior partner asked me to help assess how our clients would benefit from the big tobacco settlement in the late 90s. I created a cool probabilistic model that was really quite elegant, and – when I presented it to him – he swore and threw the memo at me. He wanted the 'one right answer,' and I knew that there was a range of possible answers. At that point, I knew I needed to find a field that embraced data and the uncertainty inherent in using data for decision-making. I ended up going back to school for a PhD in policy analysis and loved it – it wasn’t easy to go back to school after just completing three years of law school, but it turned out incredibly well for me.
Matt Kautz, VP of Business Intelligence at Machinima:
I got into BI as a business user first. My background is in marketing management, and early in my career I figured out that budget approval was always dependent on telling a compelling story with data. I was also an early adopter of social media, and became fascinated with finding ways to use it to improve decision-making across the organization.
Saurabh Bhatnagar, Senior Data Scientist at Rent The Runway:
My background was Mathematics and Computer Science. This was 2000. My first job was as a C++ software programmer working on database systems (CA-Ingres). I switched to data architecture and data science roles over time as I tried to find work that fulfilled both my Maths and Computer Science aspirations. This later came to be known as Data Science, but I didn't know that at the time.
Dominic Williamson, Facebook's Marketing Science Lead:
As a psychology graduate, I saw clear parallels between Marketing Analytics and the wider study of human behavior. I began on the media owner side with JCDecaux and then moved to analysis consultancy, dunnhumby. I was immediately attracted to the wealth of data available at the consumer level and this led to a role on the client-side with eBay (and even more data). I quickly recognized the value of people level measurement and moved over to Facebook where this is core to the philosophy of the company.