{"id":8894,"date":"2017-05-30T14:09:28","date_gmt":"2017-05-30T12:09:28","guid":{"rendered":"https:\/\/chartmogul.com\/blog\/?p=8894"},"modified":"2023-08-10T12:58:27","modified_gmt":"2023-08-10T10:58:27","slug":"data-literacy-deficit","status":"publish","type":"post","link":"https:\/\/chartmogul.com\/blog\/data-literacy-deficit\/","title":{"rendered":"The data literacy shortfall: Are we data-driven, or data-duped?"},"content":{"rendered":"

At ChartMogul, we believe in data literacy as a core component of any healthy business. We\u2019ll be covering the topic in a number of ways over the next few weeks. Stay tuned for resources and guidance, including data vis input from industry experts!<\/em><\/p>\n

Don’t forget to\u00a0sign up to our SaaS Roundup<\/a> newsletter to make sure you get the latest articles from us.<\/em><\/p>\n

\n

I remember being taught\u00a0some form of data literacy at primary school (around age nine).<\/p>\n

We started to learn about how you could represent numbers with things like charts to show the relationship between different groups of data. Drawing a bar chart to compare the number of kids in class who like bananas to the number of kids who like apples \u2014 you get the idea. For the record, I was fully in the banana camp. 🍌<\/p>\n

For years, modern businesses have used data and metrics in almost every decision they make. If you want to argue for more budget for your particular project, you\u2019d better have some data to back up your reasoning.<\/p>\n

But more recently,\u00a0the use of data\u00a0shifted.\u00a0Technology companies\u00a0started to implement\u00a0Machine Learning and AI algorithms in tech products, to find highly optimized solutions to big problems humans weren\u2019t so good at. Machine Learning methods are by nature incredibly<\/i> hungry for data \u2014 they require training on huge datasets to be effective, and there\u2019s really no limit to what they can consume. The more data, the better.<\/p>\n

At this limitless scale, and with this technology, you can see why people are hailing data as the \u201cnew currency\u201d.<\/p>\n

\"Comic<\/p>\n

(XKCD: Machine Learning<\/a><\/i>)<\/i><\/p>\n

Why not just measure everything?<\/b><\/h1>\n

Fuelling this change even more, our ability to generate and gather data has increased greatly with the advent of the \u201cInternet of Things\u201d, always-on mobile broadband, and smartphones carrying more sensors than we\u2019d ever dreamed of 20 years ago. Data storage is also ridiculously cheap, so why not gather all the data we can \u2014 even if there\u2019s no immediate use for it?<\/p>\n

For professionals, there\u2019s no escaping the numbers and statistics present in our working day, regardless of your role \u2014 Marketers, Salespeople, Engineers, etc. \u2014 these people all use data to make decisions and do their everyday work.<\/p>\n

So we are all surrounded by data. But are we equipped with the skills and knowledge required to make sense of it? Secondly, do the people using such data for storytelling have adequate skills for effectively communicating and visualizing data for their audience?<\/p>\n

\n

Read more on data-driven culture\u00a0in our article\u00a0The Quantified SaaS<\/a>:<\/em><\/p>\n

\"\"<\/a><\/p>\n

\n

The dream of democratized data<\/b><\/h1>\n

A recent article in Forbes stated the following:<\/p>\n

\n

\u201cData in the hands of a few data experts can be powerful but data at the fingertips of many is truly transformational.\u201d<\/i><\/p>\n<\/blockquote>\n

Which hints at the true potential of democratized data in business. If we really can empower everyone to gather, interpret and use data to their advantage, the benefits promise to be huge.<\/p>\n

In the Enterprise sector, the dream is just as compelling (perhaps unless you\u2019re a data scientist): Kissing goodbye to the standalone BI team, and democratizing access to data that was at one point locked away behind layers of complex queries or software that required months of training. The death of the data warehouse is a welcome change in many agile fast-growing businesses.<\/p>\n

However, in the same Forbes article is the following statement:<\/p>\n

\n

\u201cThe data literacy divide will impede organizations from reaping higher rewards from their data investments.\u201d<\/i><\/p>\n<\/blockquote>\n

And here we reach the crux of the problem: Unlocking the power of data requires not only advanced technology but well-informed, data-literate people. And that\u2019s where the gap is growing.<\/p>\n

What\u2019s holding us back?<\/b><\/h2>\n

Spoiler: It\u2019s not the technology.<\/i><\/p>\n

To understand where we\u2019re lacking, it\u2019s worth clarifying what we mean by \u201cdata literacy\u201d. There are a few different definitions, but here\u2019s a simple one from Margaret Rouse of whatis.com<\/a>:<\/p>\n

\n

\u201cData literacy is the ability to derive meaningful information from data, just as literacy in general is the ability to derive information from the written word.\u201d<\/i><\/p>\n<\/blockquote>\n

She goes on to describe the skills defining data literate people:<\/p>\n