Teach Everyone To Think Like A Data Scientist

Data has become the foundation of our operational landscapes, and as we wade further into Industry 4.0, the dependence on data will only increase. As a result, the ability to interact with data isn’t a choice anymore, it’s a prerequisite for working efficiently.?

But in a time where new technologies are revolutionising the world of business optimisation, it’s easy to lose sight of the value that lies in fundamental skills like data literacy.?

Even though most employees will never interact with large concepts like Big Data, Machine Learning, and Artificial Intelligence, they will work with the data that fuels those technologies.?

So to ensure that they are able to stay a part of an efficient operation will require them to be literate in the world of data implications.?

Now while there are numerous data literacy courses available out there, from Coursera to Udemy, the change begins a lot closer to home.?

Understanding the true depths of data literacy

Gartner describes data literacy as follows:??

“...the ability to read, write and communicate data in context, with an understanding of the data sources and constructs, analytical methods and techniques applied, and the ability to describe the use case application and resulting business value or outcome.”

What it boils down to is your ability to read data like a book and incorporate the knowledge you’ve learned into your thought processes.??

Making readers out of us all

Literacy, in its more common literary form, allows people to read, interact with concepts and ideas, and make that knowledge a part of themselves.??

Now data literacy works much the same way. It allows you to interact with data and interact with it through different dynamics.

The culmination of events

From plotlines to themes to revelations, books often echo something you’ve encountered before. But in truth, even the first of these occurrences is an echo of thoughts and ideas that have been developed over decades and centuries of thinking and writing. Even authors such as Shakespeare and Cervantes (the writer of Don Quixote) are culminations of literary developments and not singular, instantaneous occurrences.?

Data events work just the same. There’s an entire history of references to rely on, to deepen our understanding of the data “texts” we’re reading right now. And the wider you read, the more you interact with other books (or data fields), and the more you see the connections between everything.?

Turning negatives into positives

The thing that often influences our reading the most is bad writing or convoluted endings that irritate us. And with data literacy, something similar occurs.?

It’s not only efficient datasets and analytical processes that influence our data utilisation. Often the pitfalls we’ve identified along the way and the shortcomings we’ve seen in our own datasets and processes are the aspects that help us most in our data interactions going forward.?

Staking your data claim

You don’t have to be a practised data scientist to try and emulate their way of thinking, just like you don’t have to be Noam Chomsky to appreciate a book's themes and prose style.?

What’s necessary is taking the time to actually pay attention to data and the story it tells and then use those insights to inform your next steps and to help you see the bigger picture.?

Seeing data events in context

Jordan Morrow, of QLik, has gone so far as to say that data literacy can even help people to identify “fake news”. And once you think about it, the claim is rather well-founded. A single point of data isn’t reliable. It’s only once it is seen within the greater framework of information that its reliability is proven.?

Now if we consider the prevalence of “fake news” in today’s media-drenched society and how inaccurate information spreads like a wildfire, it’s clear that considering the big picture isn’t in vogue right now.?

Keeping this in mind, data literacy training needs to encourage curiosity, cover how to ask data-related questions, and build a data scientist mindset.?

At the end of the day, data literacy isn’t about having all the answers, but rather about knowing how to ask the right answers and see the whole story.?

The art of data storytelling

Data storytelling is the act of portraying data in the most accessible form, telling the “story” behind datasets. Putting data into context allows you to convert data into these accessible stories.

At this point, not everyone speaks “data”. So the stories that are being unfurled, even in plain language, may not be fully grasped by their audience. That’s why it’s important to expand the data vocabulary of teams. Having conversations around data will help you to make it a part of your language, or rather you will learn to speak the language of data.?

Now there is something to be said about the lacklustre preparation that educational institutes offer in terms of data literacy. The problem extends to the way businesses themselves see data, and more specifically access to data.?

If we don’t talk about data, about the journey behind the results, and make it a part of our business landscape, we won’t ever reach a point where data literacy can make a difference.?

The journey toward data literacy?

The greatest advantage of data literacy is helping your entire workforce overcome data insecurity. Doubting your decision-making power limits intuitive productivity and the ability to think/act in the moment.?

When every decision has to be informed or approved by someone else, you never get to a point where knowledge is internalised and becomes part of your professional self.?

Here are a few key points to keep in mind on the journey to full immersion in data literacy.?

A change in culture

The road to data literacy begins with fostering a culture of curiosity, where critical thinking, creative analyses, and alternative perspectives are embraced.?

It’s this culture that empowers employees to put their training to practical use even when they’re only starting their data literacy journey. When employees are encouraged to turn insights into actions, they get to immerse themselves into their training immediately.?

Company-wide data access

We’re reaching a new era in business operations, one where people are no longer satisfied with merely getting the job done. People want to be a part of something bigger, contributing to the overall operational success and value offering of the business.?

To achieve that means offering data access to people at every level of the organisation, not only C-suite executives. Data optimisation is a collective journey. And to make optimised and intuitive decision-making possible at every level of your business, you need to include everyone in the quest.?

Commit yourself to the long game

Data literacy isn’t a once-off solution. It’s something that should be tracked and augmented over time for optimal efficiency.?

Tracking KPIs and how data literacy affects them over time is a vital part of data optimisation, you should also track adoption progress and find out how training can be augmented to better suit employees’ different operational landscapes.???

The added benefit of allowing data literacy to evolve over time like this is that you will be able to identify the best-suited technologies and training programmes for your infrastructure, instead of simply opting for what’s most popular.?

Incorporating data literacy into our business environment is a vital step in creating more efficient and productive operations. It’s a change that will help us alter not only the way we engage with data but also the way we interact with information in general.?

This is the change that EnterpriseWorx is dedicated to. And we look forward to guiding you on your data literacy journey and in the creation of inquisitive minds.