Data: it's not just for the analytics team anymore. While data scientists are still in demand, the newest conundrum facing today's organizations concerns the rest of the staff. Data isn't used in a vacuum: it touches many other roles, and those employees need the literacy to handle it effectively.
Let's explore why data skills matter company-wide, what data literacy involves, and how anyone can start learning it to grow in their careers.
"Organizations need a broad set of data skills, and they need to be in various different roles across the organization," says Amy O'Connor, chief data and information officer at Cloudera. Greater amounts of data call for "new skill sets, and the ability to use different sorts of tools to look at that detailed data," she says.
Another factor is increasing automation in the workplace. And while in a lot of ways this is a good thing, it's also bringing new considerations to light. Notably, those in more "standard" business roles need to understand what data is being collected, what automatic processes are being performed, and how that affects their individual roles and the broader company.
"For anyone in almost any business role these days, there's an automation around that role," explains O'Connor. "For instance, on the sales side, it is important to look at your transaction systems. What can we see about what's happening on our interactions with customers? What processes are being automated, what data is being collected? You certainly don't have to be a 'data person' or know any SQL in order to do that. Just sort of cruising through user interfaces and seeing where are people entering data is a great place to start."
The same principles apply in other departments too, of course. Product teams need to understand customer needs and behavior to design new features. Marketing teams need to understand demographic data to develop effective campaigns. Customer service teams need to draw on data to best serve users.
The Fundamentals Of Data Literacy
Becoming data-literate isn't necessarily about tools, software, or programming languages. Rather, it starts with a holistic view of how to think about data and what questions to ask.
"Every business is different, and there are so many tools out there, but when you peel underneath it, a lot of the concepts are the same," says O'Connor. Data literacy starts "not from the perspective of the tool, but from the perspective of the data. What information is being collected? What can it be used for? Focus on becoming literate about the concept of data in general. Once you have the basic concepts down, you can explore more complex topics."
The second skill that will prove helpful: statistics. "With that much data out there, understanding the basics of statistics is really important," says O'Connor. "If you don't understand statistics, you won't be able to ask the appropriate questions to make sure that a useful answer that comes out."
Finally, O'Connor says, there's a great need for data "communicators" -- people who can take the information and make it visual and easier to understand. This specialty is known as data visualization and is one of the top in-demand tech skills this year. "For people who might not be the programmers or machine learning engineers, that's where you starting to bridge between the art and the science of data," says O'Connor. "Having people who can communicate about data results and visualize data results is vitally important."
How To Start Learning Data Skills
ThoughtSpot Chief Data Evangelist Doug Bordonaro recommends a mix of traditional learning and hands-on, experiential training.
Here are Bordonaro's tips:
"Take a basic statistics course. This will provide the foundational language and understanding of data concepts needed to really get value from analytics.
"Get access to your company's data. If you don't have it, ask for it. If you have access but don't know how to use it, ask for help.
"Get familiar with using data. Whenever a big decision is made, ask to see the data that backs up the decision. If you're making the decision, ask yourself what data you've used to arrive at that conclusion.
"Think of data literacy as a business issue, not a technical issue. With AI, most of the technical requirements for interacting with data are dropping away, making it more of a business need than before."
You can find introductory data analysis courses from online education platforms like Coursera, Udemy, and edX. Starting with Excel or data visualization will provide a great foundation.
No matter what department you work in, learning data skills allows you to add more value to your team, your company, and everyone your work touches.