From the course: Introduction to Career Skills in Data Analytics

Developing data fluency

From the course: Introduction to Career Skills in Data Analytics

Developing data fluency

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- Is your organization data literate, data fluent, or none of the above? Let's break these terms down. Data literate means that you could read it, converse about it, and understand it. Let me give you an example, your bank account. It's all about your finances, right? And if you really look at it, it's just all your data through transactions. Can you read your balance? Can you tell me when something is there that shouldn't be? And if it is, can you call the bank and explain it? That means you're literate about your banking data. Now to the meaning of fluent. Fluent means you can create something with it that shows skills outside of just being able to read it and use it. We know people who speak other languages. They are either literate or fluent. Someone who is literate can, again, pick up on the common things with the language and speak in simple sentences, but a person who is fluent can carry on conversations and author stories in that language. Just like these terms apply to language, they apply to data. Let's go back to our banking example. If you are fluent with data, you can then turn your banking data from last year into insights that will allow you to build a budgeting system and a finance tracking system. To really build your data skills, you must begin to think about how that data skill applies to your everyday life. If you are data fluent, and at work someone hands you information, and it's the first time you've ever seen it, you will have an approach that lets you learn that data, and you will have questions that seem natural for you to ask. Approach is everything, and building an approach or identifying it can start today, right now even. Start thinking about every time you have a new data set in front of you, what do you do? That's your approach. If your approach is to stare at it and wonder, well, that tells you where to begin. Now there are degrees of data literacy and data fluency that are appropriate in the workplace. And I would argue that everyone should be data literate. The ability to read, speak, listen, and understand the data, or at least the data that applies to them. Could be time sheets or even paychecks. An organization that only has a small percentage of data fluent people means they do not have enough people to do the exploring and building that might just be the tool that takes their company to the next level. Becoming data literate and then transitioning to data fluent can be a game changer in your career. You can go from reading and basic understanding to producing insight and data tools for your organization or maybe for yourself.

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