Data Literacy and How Thinking Like a Business Delivers Valuable Insights
Published on: November 1, 2023
In today’s data-driven world, organizations across every industry are recognizing the business value of team members with data analytics skills, who can derive insights, facilitate informed decision-making, and drive meaningful outcomes. Data literacy is a foundational skill for data analysts, allowing them to speak the language of data in a way that others can understand. Let’s explore what data literacy is, its role in data analytics, why it’s important, and how you can prepare yourself for a career in this field.
What is Data Literacy? Data Literacy Meaning
Data literacy is the ability to understand, interpret, analyze, and effectively communicate with data. As you develop data literacy, you become proficient at reading, interpreting, and drawing insights from charts and graphs, but beyond that, you understand concepts like data collection, quality, analysis, scrubbing, and data-driven decision-making.
Role in Data Analysis and Decision Making
Organizations are often most interested in data analysts because they help them analyze data and use the insights leveraged from it to make informed decisions. They can only do this if they possess data literacy, or the ability to transform raw data into a story that means something to organizational leaders. Whereas any business leader can see from the graph that website conversions have decreased, only an analyst with data literacy can evaluate their behavior and tell you why your customers aren’t buying.
Data literacy helps analysts (and other professionals who have an interest in learning):
- Identify and understand what data is needed, where to find it, and how to evaluate its relevance and quality
- Apply appropriate analytical techniques, identify patterns and trends, and draw meaningful insights from data by exploring and analyzing data effectively
- Assess potential biases, errors, or limitations in data and make informed judgments about its reliability
- Translate complex findings into clear and compelling narratives that can be understood by audiences at all levels from entry-level to executive
- Integrate insights derived from data into the decision-making process, evaluate different options objectively, and assess the potential impact of various decisions, reducing reliance on ‘gut feelings’ or emotions
Organizations that rely on data – and leverage the skill sets of data analysts – have better conversations, improved outcomes, and greater success.
Why is Data Literacy Important?
Just like we would never release a nurse who couldn’t start an IV in the field, we should never release a data analyst who isn’t proficient with data literacy in the field. Data without literacy is dangerous.
Let’s look at the website conversion example from earlier.
Without data literacy, a lack of website conversions (that’s a lot of website traffic but few online sales) could mean one of many things:
- The product is not appealing to the customer
- The customer likes the product but it’s not worth the price
- The product is worth the price but the price is not within the customer’s means/budget
- The checkout process is too burdensome/requires too many clicks
- The customer doesn’t trust the checkout process/it doesn’t look reputable
- Your website doesn’t have reviews online or reviews are not favorable
- The customer encountered technical issues trying to check out or doesn’t have the technical skills they need to navigate the checkout process
- The product was not available in the right size
- The customer was not happy with the color options
Of course, there could be other reasons. Without data literacy, the organization is left with this piece of data (lots of people come to our website but few buy) that doesn’t tell them much of a story and they must figure out what to do with it. Should they offer more sizes? Use a more reputable payment processor? Make the checkout process easier? Lower the price? Offer incentives for customers who give a five-star review? They don’t know. And all these efforts require time and money and may or may not solve the problem.
Data literacy is important because it helps us understand the story the data is telling so we can make decisions that will move the dial in the direction we hope it goes. More specifically, data matters in business because it’s our future, it drives educated decision-making, and it’s central to business and other uses.
The Future is Data
Any individual or organization who doesn’t utilize data to their advantage will fall behind in the next few years. Businesses are using data to understand how to attract and retain talent, how to convert customers, and how to gain market share. Leaders are using data to better understand how employees think and behave so they can better support and empower them .
Data literacy empowers you to make informed decisions based on evidence. By understanding how to use data ethically, you can go beyond anecdotal information and rely on facts to make decisions.
Additionally, data literacy promotes critical thinking and problem-solving skills. It allows you to analyze and interpret data, identify patterns, trends, and relationships, and use that information to address challenges and make data-driven recommendations. This helps foster a systematic approach to problem-solving and encourages teams to think critically and use data as a tool to solve complex problems.
Other Business Uses
Although not often discussed, data literacy can take the sting out of difficult conversations. When conversations become emotionally charged, bringing the discussion back to the data can help keep emotions in check and focus on the facts and overall business objectives.
Here are some examples of how data can soften a difficult conversation:
- “Your productivity has always been at or above goal, but these last few months, you’ve fallen below your goal. What do you think is contributing and what steps can you take to get back to targeting your goal over the next two weeks?”
- “I’m hearing you say that your nurses are overworked, so I brought the census and acuity reports that are used to determine appropriate staffing levels. Can you look so we can identify the root cause and, if needed, evaluate our staffing algorithms?”
Key Aspects of Data Literacy
As you master data literacy, you’ll be working to become proficient in several key areas: data collection and storage, cleaning and organizing data, data analysis and evaluation, communication, and data-driven decisions.
Collection and Storage of Data
There are several ways to collect data, including through surveys, interviews, sensors, transactions, or digital transactions. Data literacy involves understanding the process of data collection, including identifying the advantages and disadvantages of each method of collection, identifying the most appropriate data source, designing data collection methods, and ensuring data quality and integrity throughout the collection process.
Once data has been collected, it must be stored in a structured way to facilitate retrieval, analysis, and future. Data storage is the way you organize and manage data in a system or database. Data literacy around storage includes understanding:
- Storage formats, including databases, data warehouses, and cloud-based storage
- Data organization, including tables, fields, and records
- Storage concepts, like database design, data modeling, and data normalization
Organizations also look to data analysts for knowledge around scalability, i.e., today we’re storing data for 100 employees or customers, but next year we hope to have 1,000 employees or customers.
Cleaning and Organizing Data
Another important aspect of data literacy is data scrubbing. Scrubbing refers to the process of identifying and correcting or removing errors, inaccuracies, or inconsistencies in datasets. When data is collected from various sources, it often contains missing values, duplicate entries, formatting issues, outliers, and other anomalies that – if unresolved – can impact the quality and reliability of the data.
As data analysts increase their data literacy, they become more comfortable identifying and resolving missing values, duplicate values, and inconsistent formats to ensure data is consistent, accurate, and representative of the population.
As an example, if a single dissatisfied customer leaves the same scathing review of your business on Yelp, Google, and Facebook, and you only received seven reviews in the measurement period, data scrubbing will change your dissatisfaction score from an inaccurate 33% to an accurate 14%.
Data organization involves labeling and categorizing data in a meaningful way to make it easier to identify and retrieve. When you’re data literate, you understand the significance of labeling, managing metadata, and documentation. You can organize data in a logical and intuitive manner, making it easier for both you and others to navigate and understand the data.
Data cleaning and organization skills help you ensure your data is accurate, reliable, and structured, so you can use it in the most meaningful way.
Data Analysis and Evaluation
Data analysis involves examining, transforming, and interpreting data to uncover patterns, trends, and actionable insights. In the scope of data literacy, this includes understanding the fundamentals of data analysis and being familiar with analytical tools and techniques.
Data evaluation assesses the quality, relevance, and reliability of data. It entails examining the strengths and limitations of the data, identifying potential biases or errors, and critically evaluating the credibility of the data sources and analytical methods. Data literacy includes understanding how to evaluate data and make informed judgments about its fitness for a specific purpose.
Communication and Data-Driven Decisions
Communication is the most critical component of data literacy; what good are all these skills if you can’t effectively convey the story your data is telling those who are charged with making changes and decisions? Data literate storytellers translate complex data into clear language, visualizations, or reports that resonate with the intended audience – and when that’s done well, it provides the information needed to make decisions based on facts rather than feelings or anecdotes. Data-driven decision-making drives measurable, positive organizational change.
Your Story Starts Here
A degree in data analytics can prepare you for a wide variety of roles across any industry, including Data Scientist, Operations Research Analyst, Computer Programmer, Market Research Analyst, Business Consultant, and more. Additionally, a Business Analytics certificate can be a powerful addition to your career in IT, project management, human resources management, or business administration.
Park University offers a variety of ways to improve your proficiency in Business Analytics, including:
- B.S.B.A – Business Analytics
- Certificate – Business Analytics
- Minor – Analytics
- Graduate Certificate – Business Analytics
- MBA – Business Analytics Concentration
- MHA – Business Analytics Concentration
- MPA – Information Systems & Business Analytics Concentration
- MS – Information Systems & Business Analytics
Whether you’re looking to advance your career or transform your own company into a data-driven organization for a more competitive edge, our program will empower you to leverage data effectively and drive innovation in any industry. Take your career to the next level by growing your data literacy at Park University today.