Data Literacy Guide for Data Scientists and Analytics Leaders

Data literacy has become an important skill in today’s digital era where about 2.5 quintillion bytes of data is generated daily. According to Gartner’s research, companies with higher corporate data literacy scores will likely have a higher enterprise value of $320-$534. So, if you’re seeking a data science career, then you must understand the fundamentals of data literacy and drive it within your organization. 

What is Data Literacy?

Data literacy refers to the ability to read, write, comprehend, analyze, and communicate data. This significant skill allows enterprises and individuals to make effective and data-driven decisions. It is not just about learning programming languages or becoming a data scientist but also about understanding different sources and types of data, and determining what, where, and how to analyze to get meaningful and accurate data.

What Does Data Literacy Involve?

Data literacy includes the ability to read data in different forms like charts, reports, or graphs. For example, interpreting the annual financial reports of a company and comprehending its performance. It also involves working with data, which means gathering data or creating a survey to extract insights, and using and communicating with data to tell a story. For example, using customer data to develop a business case for the new product. 

Data Literacy: Importance for Organizations

Data literacy is fast emerging as a significant skill in the competitive data science job market. It provides a wide range of advantages to organizations and individuals alike including the following –

• Demanded by employers: Around 66% of employers are ready to provide higher salaries to employees with solid data literacy skills. 77% are prepared to propose a salary increment of 10-15%. (Source: DataCamp)

• Effective decision-making: Data literacy programs improve the quality and speed of decision-making by providing more information about how the market and customers are behaving. Accessing accurate data about product and service performance helps in making smarter choices.

• Better client understanding: An organization must have updated and comprehensive information about who is their target audience so that the right strategies can be planned and executed. It is important to gather data about the requirements and desires of potential clients to attract them. Understanding all this information requires an expert who has data literacy skills.

• Good ROI knowledge: Data literacy is beneficial for ensuring that strategic decisions are producing significant ROI. It allows understand all your data and uncover hidden truths to determine what is working efficiently and where you need to work further.  

• Strengthen responsible digital citizenship: The use of ChatGPT and DALLE-2 tools is constantly increasing for producing human-like images and text. However, sometimes these tools can be used to power misinformation. 

According to Salesforce’s Director of Data Science & Data Intelligence, these tools are more crucial for post-truth politics and deepfakes. Data literacy helps foster an engaged digital population by allowing people to ask significant questions about data.  

• Productive and happier employees: Data literacy helps create comfort and confidence in using organizational data. It helps every data-skilled employee to feel more competent and productive in their daily work and drive outcomes with data. 

Important Data Literacy Skills for Organizations

People having the ability to interpret data effectively are more successful than those who don’t possess this ability. Every organization must look for the following data literacy skills in their employees –

• Skill to read and understand the data to make sense of data-based findings.

• Data visualization to make data easier to comprehend.

• Statistical analysis to make informed decisions about an industry or business.

• Capturing, writing, and analyzing data to create useful visualizations. The skill to use predictive models is also important to make predictions about upcoming events.

• Data storytelling and understanding the concepts of data science, data engineering, and machine learning. 

• Presenting data-based insights clearly and concisely. 

• Data management to make confident decisions about the success and bright future of an organization.

What are the Different Challenges to Data Literacy?

Data literacy challenges are related to cultural, organizational, and technological factors. Key barriers include 

• Inability to realize how to get started.

• Lack of access to high-quality data, training, and skills.

• Poor understanding of data within organizations.

• Limited opportunities for people with varying backgrounds in management, business, and IT sectors to build skills together in an interdisciplinary manner. 

Tips to Develop and Improve Data Literacy

Organizations need a good data literacy strategy to leverage this ability for their growing performance. Here are some steps to develop and enhance data literacy within your organization –

1. Understand your expectations i.e. what you want data to do and how it will provide value for your organization.

2. Understand your data state and find investments required to allow your employees to achieve business objectives.  

3. Consider solutions that decrease data cleansing and improve data analysis and monetization.

4. Boost the self-confidence of your employees to ask the relevant questions and evaluate the suggested insights via data literacy training.

5. Be sure to continue to evaluate data tools for all roles to make sure they keep on delivering based on user needs.

Build Your Data Literacy Skills with the Best Certification

Since companies are quickly becoming more data-driven in today’s digital world, the demand for experts with data literacy skills will continue to rise. So, developing or boosting your data literacy skills can be a good decision. 

To get started, you can consider enrolling for the best data science certifications from reliable institutes or universities offering different resources, learning paths, and study materials in one place. The self-paced certifications keep learners on track by providing new essential knowledge of different topics and skill sets.  

Conclusion 

Organizations investing in organization-wide data literacy tend to report more transformational outcomes across several dimensions. For example, effective decision-making, better customer experience, satisfactory employees, etc. Anyone who wants to be more informed and confident about data in their life and organization such as managers, data scientists, executives, etc. can consider developing an important skill of data literacy.