What is Data Literacy and why is it important

What is Data Literacy

Data literacy, as defined by technology research firm Gartner, "Is the ability to read, write, and communicate with data". Is it essential to be data literate? In short, yes. Information is the lifeblood of any business enterprise. Virtually every organizational role involves creating, consuming, and communicating information. 

And more and more business roles are information or knowledge work, where data is the main thing people work with. When employees work with data, the organization becomes better, more intelligent, capable, and innovative. And when employees become better at improving and protecting data, the organization's data assets become more valuable. 

What are the attitudes and behaviours of a data-literate person?

First, being data literate means you respect data. That means recognizing its business importance and value. It also means using data regularly in work, seeking new data and combining data in new ways to improve outcomes. Respecting data also means following the recommended practices to safeguard data. Second, being data literate means, you also suspect data. That means you must be alert to its potential flaws. Ask questions. For instance, are things missing or inconsistent? Are data samples large enough to be realistic? Does the data come from reliable sources? And it means, too, being alert to potential flaws in how the information is used. For instance, has it been selected, summarized, or analyzed in a way that misinforms or introduces bias?

Essentially, being data literate means being attentive to the data around you and how it is, or sometimes isn't, working for you and your organization. 

However, data literate ultimately requires more than just using data effectively in your job. It requires some background knowledge and an understanding of how data is organized, processed, and managed. You need to have a solid understanding of some fundamental data concepts, starting with understanding the two key types of data: structured data and unstructured data.

What are the Type of data

Structured data

Structured data is what most people think of when they think of data, clearly defined data types: numbers, text fields, dates, and Booleans. It's typically organized in rows and columns, such as spreadsheets and conventional databases. As this data is entered into a database, it's made to conform to the predetermined structure.

Unstructured data

Unstructured data is – unstructured. It doesn't have any predetermined form. It flows continuously rather than being captured as discrete transactions. Unstructured data includes large text files, audio and video, and photos and images. It's pooled in data lakes or specialized environments instead of fitting into traditional structured databases. And it's processed differently, scanned, filtered, flagged, and excerpted in various ways. Another thing to be aware of is the concept of big data. This isn't a data type; instead, it's a phenomenon.

What is Big Data

Big data is essentially about the vast technological leap of late in the amount and variety of data organizations can work with and make sense of. It's not that there's been a massive increase in business activity. Instead, technology has advanced so much that we can now generate and use more data around the same level of business activity. Of course, there are many positives to this, but that data must be managed well. If not, we could be subject to more significant information overload than ever before. Although some big data is structured, a lot of the new big data we're generating is unstructured and processed with text, audio, and image analytics technologies.

When we talk about the challenges of big data, we can talk about the three V's: 

• the volume of data that can be processed, 
• the variety of data, both structured and unstructured, that can work together, and 
• the velocity of data movement, which leads to another critical term. 

And that's streaming data. This data is processed in real-time, so instead of being stored for later use, it's processed as it arrives. It includes continuous data flows from financial markets, customer interactions on websites, or social media posts. Lastly, to be data literate, you need to understand what's meant by the common phrase, "A single version of the truth".

It's often said that a goal of data management is getting a single version of the truth. This refers to the value of having one shared source or master copy of the data about the most critical business entities, such as customers. It refers, too, indirectly to the common problems that come with having multiple inconsistent versions of data and the inevitable disagreements about which data and conclusions are correct. A single version of the truth means having a shared and definitive copy of the data, with agreement on its structure– what attributes are in a customer record, how fields are formatted, what are legitimate entries, and perhaps how the data must be captured and checked. That's extremely valuable. But there's no single version of the truth about how the data can be usefully interpreted, combined, and put to work.

Different business functions might even have different working definitions of what a customer is while using the same master data. There are still many disagreements about what the data tells the business. While it's essential to understand unstructured and streaming data, it's also crucial to recognize that the bulk of the data used in everyday industry is in structured databases and data warehouses. Either way, being data literate means having a solid grasp of certain key data concepts. And it's important to understand these concepts so that you can be more effective when it comes to talking about, working with, and benefiting from data.

Closing comments

Businesses that want to be successful in the digital age need to make data literacy a priority. That means ensuring all employees have the ability to read, write, and communicate with data.

Luckily, there are plenty of resources available to help businesses achieve this goal.

The AICPA offers an excellent data analytics course that can help your employees become more data literate. With the right training, your employees will be able to use data to improve your business and protect your valuable data assets.

If you would like to know more about the course, feel free to contact our team