Why Is Data Literacy Important for Businesses?

Some may think the ability to interpret data is only useful if you’re working in analytics, but data literacy is an important skill for many professionals. As data and data collection continues to increase, data literacy becomes more vital to your future.

Learn more about the growth of data and how to improve your data literacy in the workplace.

What Is Data Literacy?

Data literacy is the ability to critically understand and evaluate data and the information gleaned from it. Those who are data literate have the basic ability to comprehend sets of data and convey its meaning to their audience. As more businesses make decisions driven by data, they need more people to work with it.

Chenyao Zhang, information technology faculty at Purdue Global, says data literacy has two aspects.

“The first is the practical side,” he says. “That means that you can at least do basic data crunching, create simple visualizations, and interpret and convey your message clearly to your audience. Then there’s the mindful aspect—that whatever decision you take regarding the data has a ripple effect on the upstream user and the downstream user.”

>> Read more: Rise of the Data Analyst—What’s Behind the Boom?

How Business Data Is Gathered and Analyzed

Being able to analyze data helps companies get the information they need to make better predictions and business decisions. Gartner calls data literacy “an explicit and necessary driver of business value.”

There are four main categories of customer data:

• Attitudinal data: This measures customer satisfaction, product desirability, purchase criteria, and more.
• Behavioral data: This measures transactions, including product usage and personal histories.
• Engagement data: This is how people interact with ads, apps, emails, social media, websites, and more.
• Personal data: This includes personally identifiable information such as gender and Social Security number, plus other non-identifiable information, such as web browser cookies, one’s IP address, and more.

With this type of data, businesses can then gain more insight about customers and operations. For example, they can:

• Predict customer behavior: With the right information, companies can adjust purchasing and inventory for optimal use.
• Measure the performance of advertising campaigns: Knowing what works and what doesn’t refocuses campaigns and helps companies spend their advertising dollars more wisely.
• Identify trends in seasonality: This also becomes important in planning and purchasing so resources are deployed with insight.
• Plan ahead for potential supply chain delays: With insights into ordering and shipping, companies can avoid product shortages.
• Diagnose the cause of data breaches and cyber attacks: Preventing disruption to websites and databases is important to keep businesses up and running.

Fostering a culture of data literacy across departments can reduce roadblocks. According to Gartner, promoting data sharing and breaking down data silos is linked to high-performing data and analytics teams.

“If you have a data issue and you are not taking any action, it may prove to be costly,” Zhang says. “If everybody takes time to even understand the basics of the data life cycle, this communication cost will be cut down significantly.”

How Can You Improve Your Data Literacy in the Workplace?

Some tips include:

1. Create Data Charts in Excel

Building charts helps you visualize data and organize it in a useful way. Excel is one of the most used programs for graphs and charts, so having a working knowledge of it is basic.

“Most people can immediately start using Excel to import data from a website, or from a text file—whatever the data source,” Zhang says. “They can import data into Excel and start to create some of the simpler charts, like a bar chart, pie chart, arrow chart, or line chart.”

HubSpot has a step-by-step guide to building data charts in Excel.

2. Explore Different Data Visualization Tools

Excel is a go-to resource, but there are other data visualization tools you might use. They support a variety of visual styles, are simple and easy to use, and can handle a large volume of data.

Try out these programs:

• ChartBlocks
• Chartist
• Datawrapper
• FusionCharts
• Google Charts
• Grafana
• Infogram
• Tableau

3. Collaborate With Your Analytics Department

Find out what kind of data they work with, what tools they use, and how you can come alongside them to learn.

If your company offers training for data, even if that’s not your department, take advantage of these sessions to increase your knowledge.

>> Read more: Data Analytics Career Guide: Is Analytics for You?

4. Brush Up on Programming Skills

Some coding may be required when analyzing data. Among the programming languages you may use are:

• C++
• HIVE
• Java
• Julia
• MATLAB
• Perl
• Python
• R
• Ruby
• Scala
• SQL
• Swift

Codecademy is one of many free online sites where you can begin to learn coding.

Pursue Educational Opportunities in Data Analytics

Finding the right degree for your needs will help you become more data literate. Purdue Global offers several degrees to help you in your journey. You can advance your career with convenient online education that provides access anywhere on a flexible schedule. Explore the following programs:

• Online Bachelor of Science Degree in Analytics
• ExcelTrack^® Online Bachelor of Science Degree in Analytics

We also offer a Purdue Global + Google Data Analytics Certificate. To get started, request information or apply today.