We need to rethink the way we do data training if we truly want to make it accessible to everyone.
Photo from our StackOverflow Hackathon in 2019
“We expect that, by 2020, 80% of organizations will initiate deliberate competency development in the field of data literacy, acknowledging their extreme deficiency.” — Alan D. Duncan, Vice President at Gartner
The recent rise of big data and data science has been a boon to data specialists. But to those without formal training, data remains as elusive and intimidating as ever.
It’s no surprise then, that great companies (e.g. AirBnB, NYT) are now striving to make their entire organizations better with data. The trend has been referred to as “improving data literacy”, or even “establishing a data culture.”
Either way, companies want to solve the following problem: How do I get my employees to use data better so that my data team has time to do more valuable things?
For the last 2 years, we’ve been asking companies how they make their data more accessible. As a team, we’ve got our own battle scars from championing data in companies big and small, high- and low-tech. From all that research and experience, we’ve found most data training programs look the same:
1- or 2-week long intensive training
that covers specific tools like SQL, Excel, and/or Python
using demo data (company data if applicable)
The objective of these sessions is for people to be able to query the data sources themselves and get the info they need. Unfortunately, the actual outcomes are that within a few months:
Attendees have forgotten the training because they haven’t practiced
The data structure has changed significantly (or has been made inaccessible to most parts of the business)
The tool that was originally taught has been replaced by something else
So most attendees end up in the same place they were a few months earlier, except everyone’s a little more cynical.
We think there’s another way.
We’ve been running our own data training sessions for the last 6 months now. With over 500 people trained and many of them taking the material back to their own companies, we‘ve collated a few things that could make your data training program the one that sticks:
Instead of saying “let me teach you…” try “how can I help you…?”
By starting a “data literacy initiative,” you’re making your colleagues feel like it’s all their fault. You’re essentially saying “if you guys knew a little more about data, it would make everything better,” which, while maybe true, is not particularly inspiring. How would you react if someone called you illiterate in something?
Most people in your company will agree they would love to do more with data, and likely feel a strong sense that they should for their careers. So instead of focusing on remedying deficiencies, make it about the benefits and opportunities that come from learning more about data.
Suddenly, the tone of the session changes from “you have to learn this” to “let’s see what we can do together.” It’s a simple, but powerful change that can get even the fiercest data curmudgeon onboard.
Instead of running a training session on how to write SQL, run one about asking data-driven questions.
You will not get everyone in the company to love data as much as you do. You will not even get people to stop asking you for reports all the time.
But, if you focus on it, you can make significant changes. Obviously, each company will have its own initiatives, but one I think every company should have is: asking good questions. Instead of getting vague questions like “can you send me last month’s sales data?”, you can receive more actionable and targeted questions like, “I’d like to see if our new social media campaign hit our target of 10% increase YoY in leads.” The former is vague and devoid of any business significance. The latter is specific and demonstrates the requestor knows exactly what they’re looking for. More importantly, an analyst can add value to the second statement by recommending considerations to take with the data or help with the analysis.
The bottom line is: the best companies ask the best questions.
Excerpt from our Data Training Presentation
Instead of a 2-week intensive, try weekly lunch-and-learn sessions.
Weeklong intensive sessions are certainly appealing when considering this type of training — they create a focused environment that almost always delivers tangible results. However, the long term effects of these programs are reduced if regular, cultural changes don’t follow.
The opportunity with these types of sessions isn’t just to make the business user more competent with data, but to make the business better with data. This means the more time the data teams and the business teams work together, the better.
For this, we suggest making data a more expected part of people’s lives. Have quarterly KPI reviews, or optional lunch and learn sessions where people can ask their data questions. Be creative with it, but make it last!
Making data more accessible in your company has incredible potential to transform your business, and we believe it is definitely worth the investment. Before you get going designing a program, consider your company’s and your participants’ objectives, and the find the best way to meet them. Challenge yourself to make it more than a 2-week SQL course, and instead something that makes a lasting impact on your company and culture.
For the last 2 years, we’ve set our sights on making data more accessible to everyone. We’re building some tech and some training materials that we think can help. If you’re interested in accessing the training materials, you can sign-up for updates here! And we’re in Beta! You can register for access here.
 S. Hippold, CDOs Must Take the Lead to Improve Data Literacy (2019), Gartner
 J. Stober, How Airbnb is Boosting Data Literacy With ‘Data U Intensive’ Training (2018), Medium
 L.R. Cook, How We Helped Our Reporters Learn to Love Spreadsheets (2019), Medium