Data and analytics is a trending, ever-growing field. (Hey, you picked the right career! Nice job.) According to LinkedIn’s 2018 Emerging Jobs Report, the need for “data scientist specialists” grew 5x in 2017. People from all corners of the world pontificate about the future of analytics, handing out advice, hacks, and talking about emerging trends, like artificial intelligence and machine learning. As interesting as it can be to listen to thought leaders, it’s surprisingly difficult to uncover real gems of information that will help you advance your career (and love what you do).
How do you cut through the hype and uncover advice that’s actually useful? Here are our top five secrets for analytics success that we wish everyone knew:
1. Code-Free is Real.
Yes, data science is a complex blend of math, computer science, creative thinking, and a dash of art. Not everyone is cut out for that type of work. But you know what the biggest barrier to entry is? Thinking you need to know code. You don’t. R and Python are valuable skills, but with an Analytic Process Automation platform, they aren’t requirements for success since you can perform predictive and prescriptive analytics on a drag-and-drop canvas.
It doesn’t matter what your background is — if you’re hungry to learn and are equipped with a self-service APA platform, the fields of opportunity are wide open for you.
Let’s dive into an example:
In 2017, SCAN Health Plan began to suspect a Lidocaine scheme because members kept receiving unwanted ointments in the mail. Using code-free network analysis, they analyzed claims data and began finding connections between members, pharmacies, and unwanted ointments. The result? SCAN Health Plan saved $1.5 million in the first year.
2. No Ph.D. Required.
Ok, now that you’re on board with the idea of code-free, code-friendly data science, let’s bust another myth: you don’t have to have a Ph.D. in mathematics or statistics to be able to derive advanced insights from your data. Again, if you’re a math whiz, great! You’re ahead of the game. But if you stopped taking math classes after undergrad, that’s totally fine, too. As long as you’re detail-oriented and blend creativity, curiosity, and logical thinking, you’ll be able to navigate the world of self-service data analytics like the champ you are.
3. Everyone Can Have Personalized Visualizations.
A picture is worth a thousand words, so creating charts can dramatically improve a person’s understanding of your analysis. There’s just one problem — creating charts is often a time-consuming, headache-inducing process. After spending days or weeks on an analysis, you finally export your hard work to a visualization platform … only to discover previously unseen errors or the fact that your data doesn’t translate well visually.
With self-service data platforms, you can check your work, visually, as you go. Tweak something here, turn the dial there, then watch how those changes affect the visualization. Pretty cool, huh? Rather than leaving visualization to the bitter end, integrate it throughout the entire process to understand your data better, creating better analytics and better results.
Another aspect to charts that can trip analysts up is knowing every question they need to answer for everybody. Dashboards, where you can place multiple charts for consumption, are a great way to give stakeholders what they need — let them interact with your analysis on their own and answer their specific questions. And, you can make sure those dashboards are constantly up-to-date with the latest information from your repeatable workflow.
Finally, let’s talk about the holy grail of charts — batch production. What if you could be like Oprah: “You get a chart! You get a chart! And you get a chart!”? Personalized charts are available with the click of a button. With the use of self-service data analytics, a senior manager at Coca-Cola was able to send out more than 600 personalized inventory optimization reports to franchises across the United States.
4. Automation Unleashes Creativity.
No, automation won’t steal your job. In fact, it will free you to do more of the fun work and less of the … let’s say, “not-fun work.” You know, those monthly reports that repeatedly steal your time? Or the manual ETLs you continually perform? If you automate the boring, time-consuming stuff, you’ll have time to do what you actually love — working on fascinating problems and delivering more value to your organization.
Every job has tedious tasks, but analysts are particularly bogged down by repetition — as much as 80% of their time is spent pulling data from disparate sources. Imagine if you could automate some of that hard work?
Now what do you think of automation? Not so scary after all! In fact, we think it’s positively liberating.
5. IT Should be Your Friend.
Don’t roll your eyes at this one. Yes, IT definitely should (and can!) be your friend. The way many analytic systems are currently set up in organizations pits IT against analysts and data scientists. Analysts find themselves handcuffed by IT since IT controls access to data and versions and IT gets annoyed by the ad-hoc requests that have nothing to do with their pressing priorities. Self-service platforms allow IT to create governance and permissions that then enable analysts and data scientists to be more autonomous. It’s a win-win for everyone.
No matter what field you’re in, if you work with data and analytics, it’s important to keep your eye on the future. But don’t get caught up in meaningless trends. Share these five secrets with your friends and colleagues — they’re the hacks that really matter.