Data literacy is the ability to understand, analyze and communicate data in meaningful ways. There are other definitions, but that’s mine. Data literacy should be on every business professional’s resume or CV. Finance intern, software developer, marketing specialist, project manager, sales associate or editor-in-chief…it doesn’t matter. Data skills are as important today as basic computer skills were in the 1980s.
While in college (after the 80s but still last century), I worked in IT and data management for a social science research firm. It was one of my first “real” jobs. I was essentially a one-person IT shop and part-time data wonk.
When I wasn’t pulling Cat 5 cable and troubleshooting PCs, I was cleaning or analyzing data with SPSS, Microsoft Excel and Access. I would also help the full-time researchers write and edit our data-collection instruments, reports and visualizations (we called them graphs or charts back then).
After a few years, I left the world of quantitative research for a career in IT, tech media and process mining with Celonis. What never left me however, were the data literacy skills I learned in that first job. And, they have been invaluable in every position I’ve had since then.
On the help desk, I analyzed metrics like response time, resolution time and ticket distribution. In media, I used bar charts, histograms and frequency tables to track website and team metrics. I would even break out a crosstab or two if I felt like getting really fancy. I wasn’t doing SEM or using LISREL, but I was using my data literacy skills to track KPIs, make more-informed decisions and better navigate an ever-changing business landscape.
Making data-driven decisions isn’t just for managers, department heads or c-level executives either. I used data as a writer and editor trying to find out which stories were resonating with readers. I still do.
By now, you might be thinking to yourself, “I get your point, but the data journey of one person isn’t really evidence of a major career trend.” And, you’d be right. That’s why I brought a little data.
Data-centric jobs were among the most in-demand tech jobs for 2022 and are predicted to be as popular in 2023.
In its ranking of the 15 highest-paying IT jobs, Robert Half ranked big data engineer (#1), data architect (#6), database manager (#7), data security analyst (#8) and data scientist (#9). On Glassdoor’s 2022 list of 50 Best Jobs in America, data scientist ranked #3 and data engineer was #7. Data Scientist ranked #6 on U.S. News’ Best Technology Jobs of 2023 and data engineer ranked #3 on Indeed’s Best Jobs of 2023.
Not only are data-focused jobs hot right now, employers are looking to hire candidates with data skills. In a 2021 data-literacy survey conducted by Forrester Consulting on behalf of Tableau, respondents stressed the need for employees to have data skills.
For example, the 1,032 directors and above surveyed ranked basic data skills (87%) and advanced data skills (55%) as important or very important for the day-to-day tasks of the employees in their department. In fact, basic data skills was ranked higher than all the other skills on the list, including basic computer skills (83%), communication and collaboration skills (81%), research skills (71%), project management skills (69%), presentation skills (58%) and writing skills (40%).
The results were similar when the same group of respondents were asked which skills have increased in importance the most for employees in their department over the past three years. Basic data skills (51%) again topped the list followed by project management skills (43%), communication and collaboration skills (41%), basic computer skills (40%), research skills (39%), advanced data skills (37%), presentation skills (31%) and writing skills (19%).
There was a time when crafting a presentation required graphic design tools or filming a video required a production studio. Today, business productivity software makes it easy to pull a slide deck together…some would say too easy. As for creating videos, nearly all of us carry a movie-quality camera, high-end editing software and access to multiple distribution channels in our pocket. The same is true for data analysis.
Collecting and analyzing data used to be purely the domain of statisticians, economists, academics and researchers, but that is no longer the case. Thanks to business intelligence (BI) platforms, visualization tools, IT advances, data-focused programming languages, and technologies like process mining, data analytics permeates every aspect of the modern enterprise. Every business professional needs a basic level of data literacy.
However, you don’t need to be a data scientist to be data literate. As I said at the beginning, data literacy is being able to understand, analyze and communicate data in a meaningful way. If you know how to run a regression analysis, that’s a bonus, but not required.
Luckily, there are lots of learning opportunities to boost your data knowledge and skills. A quick internet search will yield hundreds of free and paid options, including offerings from the 700 academic institutions that are part of the Celonis Academic Alliance. And for those looking to blend data analytics with process mining and automation, Celonis Academy, our own online learning platform, has you covered.
For more information on Celonis Academy and the on-demand training courses, instructor-led classes and learning material available from Celonis, check out the following resources:
Process Mining: From Theory to Execution (free 10-hour, on-demand course developed by Celonis and the Process and Data Science (PADS) group)<!— htmlmin:ignore —>
What is Task Mining? (free 4-min video introduction to task mining)<!— htmlmin:ignore —>
Sustainability training: Free online courses from Celonis Academy<!— htmlmin:ignore —>
Learn PQL with these free online courses from Celonis Academy<!— htmlmin:ignore —>
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