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*I frequently get asked questions about Data Science, so in the interest of helping as many people as possible, I’ve started this blog to answer those questions as simply as possible. This is a robust topic, and if you want a more in-depth discussion, please revisit my blog, where we will be going into greater depth at another time.

Data literacy is a valuable skill for businesses to invest in and will continue gaining importance in the future. It can lead to growth and innovation and helps companies maintain their competitive edge in a tech-focused world. This information will teach you why data literacy is critical and provide tips for training a more data-driven organization.

Data literacy is the ability to read, analyze, work, and communicate with data. These skills empower workers to better understand data and machines. Data literacy can also help them ask the right questions, make educated decisions, and communicate essential findings to others.

Data literacy is a valuable skill in the tech and data-driven world. What makes data literacy crucial, and how can you leverage this skill within your organization? Here is what you need to know.

 

 

Table of Contents

What is Data Literacy?

Why is Data Literacy Important?

#1. Allows for Data-Driven Decisions

#2. Better Customer Knowledge

#3. Competitive Edge

#4. Increased Innovation and Productivity

#5. Increased Employability

How To Achieve Data Literacy

#1. Assess the Current Level of Data Literacy

#2. Develop Goals and Objectives

#3. Identify Any Data Experts

#4. Invest in Training

#5. Allow Opportunities for Employees to Use Their Skills

Essential Data Literacy Skills and Concepts

#1. Data Analysis

#2. Data Wrangling

#3. Data Visualization

#4. The Data Ecosystem

#5. Data Governance

The Data Science Team

The Future of Data Science

Conclusion

 

What is Data Literacy?

Data literacy describes the ability to read, understand and utilize data in various ways — like standard literacy of the written word. To achieve data literacy, you don’t have to be an expert or a data scientist. You only need to demonstrate a basic understanding of data concepts, such as:

•   Types of analysis
•   Data Hygiene
•   Tools and techniques
•   Common data sources
•   Different types of data

“Data literacy involves critical thinking skills that allow you to interpret data, make decisions based on findings and convey its significance to others.”

Data is a significant driver of innovation in businesses and society as it allows organizations to make data-driven decisions based on facts and numbers rather than intuition.

However, having access to data isn’t enough to achieve data literacy. You need to know how to leverage data to reap its benefits truly. This is why there is an increased demand in the job market for data scientists and individuals with data literacy skills.

Why is Data Literacy Important?

In a world where everyone has increased access to data regularly, it’s critical to understand how to use it. Data literacy can improve decision-making, innovation, productivity, and other vital factors. However, data literacy isn’t just valuable to businesses.

Data literacy can also be a valuable skill. It allows teams to learn, identify problems, communicate with colleagues, and increase their value as an employee. Information is everywhere. Without a data-literate workforce, you could limit your organization’s ability to grow.

There are countless reasons why data literacy is critical to your organization. Some of these include:

•   Allows for data-driven decisions
•   Better customer knowledge
•   Competitive edge
•   Increased innovation and productivity
•   Increased employability

#1. Allows for Data-Driven Decisions

Data literacy is essential in making more data-driven decisions. In a world full of data, making decisions based on it is a beneficial practice. Data-driven decisions are generally more effective and reliable than those that aren’t based on data.

For example, say you’re looking to deploy a new social media marketing campaign to reach your young, middle-class female consumers.

“Instead of guessing what that audience would respond to, you can refer to buyer behavior and demographic data to decide on the most effective marketing plan.”

Translating data into workable insights is a vital part of data literacy. Data-driven decision-making is effective and grants you a competitive edge over organizations that aren’t data literate. It also ensures you aren’t wasting time and resources on intuition-based business decisions.

#2. Better Customer Knowledge

Odds are that you’re constantly gathering data on your customers or clients. This can include things like their purchase behaviors, whether they’re on mobile or desktop, and other demographics like their age, income, and geographic location.

Depending on the size of your customer base, this could produce overwhelming amounts of data. However, it’s all precious. Leveraging consumer data allows you to form insights on whom you’re targeting and how to reach them better.

For example, based on your data, you may realize that a large portion of your audience is in their 20s, on mobile devices, making less than $30,000 a year. With that information, you may create specific business plans or marketing efforts to reach them and drive more profits from that portion of your consumer base.

Data literacy allows you to form better connections with your audience. Better relationships yield more sales and profits for you. They can also let you get to know your customers and serve them better — granting you a market advantage.

#3. Competitive Edge

In business, maintaining a competitive edge is critical. It separates you from other companies and makes potential customers choose you over them. Data literacy skills allow you to make solid, data-driven decisions and connect with your base, creating a competitive advantage for your business.

#4. Increased Innovation and Productivity

A lot of work involving data is tech-based. It uses data analytics tools like software and applications to manage input and output. Investing in data literacy and using analytics tools can improve workplace productivity.

Data skills and tools allow your team to streamline the process and draw meaningful conclusions. It simultaneously provides effective means of organizing the information. Data literacy skills also lead to more incredible innovation. Thus, training your team to become data literate can help keep your business ahead of the curve in an ever-changing market.

#5. Increased Employability

On an individual level, pursuing data literacy can significantly increase your employability and help advance your career. Data literate employees often report performing better at work than the wider workforce. As an executive in charge, transforming existing workplace cultures and shifting toward data literacy can benefit the business and individual workers.

As businesses pivot, there’s an increased need for data-savvy employees. Workers with data literacy can often contribute more to their organizations as those without the skills struggle to match their performance. Businesses aren’t necessarily looking for a professional data scientist to fulfill their data literacy needs. Simply being able to identify trends and patterns in data and understand what they could mean will often suffice.

How To Achieve Data Literacy

Knowing why data literacy is essential and how it can benefit your business may push you to consider building organization-wide plans. Data literacy within your organization will depend on your current workplace culture, your employees, and various other factors that can differ from one company to another.

However, there are a few basic steps to take to get you started:

•   Assess the current level of data literacy
•   Develop goals and objectives
•   Identify any data experts
•   Invest in training
•   Allow opportunities for employees to use their skills

#1. Assess the Current Level of Data Literacy

Before you determine what you want to achieve by building data literacy and investing in training, you should assess your organization’s current level of data literacy. How many of your managers can create data-based projects? Do any of your employees regularly use data in their daily work?

You can gather this information by interviewing employees individually or through an organization-wide survey. You could also give everyone a short data literacy test to assess their current skill level and how well they understand data.

#2. Develop Goals and Objectives

Once you know what level of data literacy you’re working with, you can develop specific goals and objectives revolving around increased data literacy skills. What areas of your businesses would benefit from increased use of data? Focus on those first.

For example, maybe you want to train your marketing team to utilize data to build consumer profiles you can target. This will help you ensure your data literacy training is practical and hits all the necessary marks.

#3. Identify Any Data Experts

“Hire a data scientist to oversee the training and ensure the data literacy programs are built effectively.”

You may realize you have a few data experts in your organization that you didn’t know about. The people who are already comfortable using data can be the models for the rest of your employees during training. You can promote these individuals to help lead the activities or create a new position.

#4. Invest in Training

Once all the preliminary work is done, it’s time to invest in training. You can set up an in-house training program that provides all the primary information employees need to fill knowledge gaps and get up to speed. Training programs should be flexible to accommodate different learning styles and paces while providing time for employees to practice their learning skills.

Also important is to include follow-ups in your training program so you can check in with employees and track and monitor their progress. This will let you know if your data literacy training is working and on track to meet your goals and objectives. Plus, it provides insights on whether the program could benefit from any changes to make it more effective.

#5. Allow Opportunities for Employees to Use Their Skills

When training your employees, you must provide real-time opportunities to use their data literacy skills. You can do this by assigning specific projects and tasks that require employees to put their new skills to work. Providing these opportunities allows you to see your investment at work. You can also determine if training seems to be working or if there are still existing knowledge gaps you need to fill.

Essential Data Literacy Skills and Concepts

The field of data, and the idea of data literacy, is rather broad. There are many different types of data, methods of analysis, and other concepts to learn. It’s not necessary to be an expert in everything to have solid data literacy skills. Still, these are some of the critical ideas for businesses to explore:

•   Data analysis
•   Data wrangling
•   Data visualization
•   The data ecosystem
•   Data governance
•   The data team

#1. Data Analysis

Data analysis is about reading and interpreting information to draw insights. An examination can be done using algorithms and other tools and frameworks or by simply reviewing the data yourself. There are a variety of data analysis methods to use, but the four most common are:

•   Descriptive analysis: what happened
•   Diagnostic analysis: why it happened
•   Predictive analysis: what could happen next
•   Prescriptive analysis: actionable insights

#2. Data Wrangling

Data wrangling is taking raw data and transforming it into something that can be readily used. It’s also often called data munging or data cleaning. This process typically involves correcting or removing any errors in the data and filling gaps.

Data wrangling is critical because if there are errors in the data, it likely won’t be accurate. Several tools and algorithms are used to clean up data sets automatically. However, data literate employees are also responsible for ensuring their data meets specific criteria.

#3. Data Visualization

“Data visualization is vital to making information more accessible, especially to those without data literacy.”

Data visualization is valuable because it allows you to create graphs or other visual representations of the data to understand it better.

#4. The Data Ecosystem

Your organization’s data ecosystem consists of components that collect, store, and analyze data. This can include servers, cloud storage, code packages, and software. Each organization has a unique data ecosystem. It’s crucial to understand how the organization leverages data and identify any pain points or spaces for improvements.

#5. Data Governance

Data governance is your organization’s processes and practices to manage data assets. It’s like a rulebook for collecting data and ensuring everything is accurate and secure. Often, it’s referred to as a company data policy. Established data governance is important because it focuses on your organization’s data’s quality, security, privacy, and stewardship. Operations can get quite messy without it.

The Data Science Team

Data literacy training helps you get a sense of who your key players are and build a data team with them in mind. The structure and size of your data team will depend primarily on your organization’s size and how important data is to your day-to-day operations. Most data teams include:

•   Data scientists
•   Data engineers
•   Data analysts

The Future of Data Science

Data literacy is already a critical skill as many businesses are moving toward becoming more data-driven. However, some business leaders and employees believe that data literacy will be the most in-demand skill by 2030.

Data literacy can yield actionable, customized insights that can further innovate and grow a business in ways other methods can’t. To stay ahead in a tech-centric world, data is a must-have. Technological and data-driven advancements have transformed most workplaces, making the need for data-literate employees more apparent. The benefits of data literacy are too valuable to pass up, meaning businesses will likely be looking for a data scientist to enhance their workflows.

Conclusion

Data literacy is the ability to read, analyze, work, and communicate with data. These skills empower workers to understand data, ask the right questions, and build upon their knowledge. Data-literate employees make better decisions and communicate essential findings to others.

Data literacy is already a critical skill as many businesses are moving toward becoming more data-driven. Some business leaders and employees believe that data literacy will be the most in-demand skill within this decade, making data literacy a top priority to pursue.

 

About the Author

Tiffany Perkins-Munn orchestrates aggressive strategies to identify objectives, expose patterns, and implement game-changing solutions with the agility that transcends traditional marketing. As the Head of Data and Analytics for the innovative CDAO organization at J.P. Morgan Chase, her knack involves unraveling complex business problems through operational enhancements, augmented financials, and intuitive recruiting. After over two decades in the industry, she consistently forges robust relationships across the corporate spectrum, becoming one of the Top 10 Finalists in the Merrill Lynch Global Markets Innovation Program.

Dr. Perkins-Munn earned her Ph.D. in Social-Personality Psychology with an interdisciplinary focus on
Advanced Quantitative Methods. Her insights are the subject of countless lectures on psychology,
statistics, and real-world applications. As a published author, coursework developer, and
Dissertation Committee Chair Tiffany still finds time for family and hobbies. Her non-linear career path
has given her an exclusive skill set that is virtually impossible to reproduce in another individual.