Previous Entries in Everything Analytics
Tunnel Vision on Technical Ability
If you were to ask someone "What skills are the hallmark of a data analyst?" the answers consistently center around technical ability: SQL, Python, R, Tableau, Power BI. The same shows up on most job postings - technical ability listed first.
That means it's unsurprising when aspirational analysts focus heavily on "What technical skills / certifications do I need to be competitive for an open position?" To hammer the point home, I took a look at the Weekly Entering & Transitioning post at the Data Science subreddit. While not Data Analyst specific, there is a ton of overlap between people interested in Data Science and Data Analytics. Here are some excerpts:
"How are entry level prospects for someone with a bachelors in data science?"
"The main concern is that I don't have any basic knowledge in any C language."
"I have been teaching myself SQL/Python/HTML through CodeCademy pro"
This repeats week after week after week - never ending inquiries about the technical side of the job. In the words of Morpheus - what if I were to tell you...that technical ability will not win you an analytics job? This has held true both for me getting into analytics jobs, as well as interviewing many others for analytics positions.
There's far more to a well-rounded Data Analyst, as someone in that same Reddit thread rightly identified: "While it’s easy to find resources to learn technical/mathematical skills, which I have been doing. Are there any resources for practising problem solving in the context of data analysis"
The Two Axes of an Analyst
Below is a quadrant depiction of how analysts are assessed in interviews and in their day-to-day. "Technical Ability" isn't listed here.
Don't get me wrong - technical ability is absolutely important. If you have no technical ability you'll struggle to get the data you need to do your job.
But technical ability is just a means to an end. And it's the most teachable type of skill out there! Even if there's a gap, it's easy to overcome with training. Business Acumen and Soft Skills are much more difficult to uplevel. I learned this lesson firsthand:
The Smartsheet Director of BI interviewed me three years ago for a Senior Analyst position. At the end of a 45 minute discussion, I realized I hadn't been asked a single technical question. Not one check for SQL, or Python, or Tableau skill. So I asked, "Why didn't you discuss my technical ability? Are you just trusting I know my stuff?" The director sat back, chuckled, and replied, "I only need to know how you think -- if you have technical gaps we can fill those quickly."
Technical Ability as a Multiplier
So, what place does technical ability have if it isn't what analysts are measured on? It's a multiplier - a 21st century career rocket fuel.
There are countless business leaders who have excellent acumen and soft skills. The C-Suites and corner offices are filled with those individuals.
As a data analyst you leverage technical ability to multiply how well you apply your soft skills and business acumen. Suddenly you'll find yourself at tables you otherwise would never have seen, discussing critical business questions with C-Level individuals. Finding patterns in data requires technical ability, and data-driven stories are phenomenally powerful when wielded with strong soft skills.
There is a massive focus on technical ability when really that's just a multiplier for the core skillsets a data analyst brings to the table. As you read in last week's post, Data Analysts help the business make better decisions leveraging data. That involves connecting the data to business problems utilizing Business Acumen and effectively/persuasively communicating findings with Soft Skills.
Don't just take my word for it - perhaps at this point you're wondering "What are these soft skills and how do I develop them?". Jacob has just the post for you - see 4 Soft Skills to Amplify Your Analytics Career.