Data is generated by every click, swipe, and interaction we have online. It is collected by businesses, governments, and organizations to understand their customers, markets, and operations. It is analyzed both manually and automatically by tools, AI algorithms, and models to generate insights, predictions, and recommendations.
It’s easy to get caught up in all the noise. To make the most of data, we need data literacy. Data literacy is the ability to read, understand, create, and communicate with data. It is a skill that empowers us to ask the right questions, find the right answers, and make the right decisions with data.
Data literacy is essential for any organization that wants to optimize its data culture. Data culture is the way an organization values, uses, and shares data across its teams and functions. It is collectively the mindset and behaviors that enable an organization to become more data-driven and hopefully more innovative.
Assess Your Data Literacy Level
Before you can improve your data literacy level, you need to assess where you are now. There are different ways to measure your data literacy level, depending on your objectives and resources.
One way is to use a self-assessment tool or questionnaire that covers different aspects of data literacy, such as:
- Data awareness: How familiar are you with the types, sources, formats, and quality of data available in your organization?
- Data understanding: How well can you interpret, analyze, visualize, and summarize data using basic statistics and tools?
- Data creation: How proficient are you in creating new data sets or variables from existing or external data sources?
- Data communication: How effectively can you communicate your data insights and findings using appropriate tools, formats, languages, and narratives?
- Data ethics: How aware are you of the ethical principles and practices related to data collection, storage, usage, and sharing?
Another way is to use a performance-based assessment that tests your data literacy skills in a realistic scenario or task. For example:
- You are given a dataset related to your business domain and asked to perform some basic analysis on it using a tool of your choice.
- You are given a business problem or question related to your domain and asked to find relevant data sources and methods to answer it.
- You are given a data insight or finding related to your domain and asked to present it in a clear and compelling way using a common tool such as Microsoft Power BI.
You can also use a combination of both methods to get a more comprehensive picture of your data literacy level.
How to Improve Your Data Literacy Level
- Learn the basics of data. Data literacy requires a foundation of basic concepts and terminology related to data, such as types of data, data quality, data formats, data structures and data manipulation. You can learn these concepts through online courses, books, videos, or podcasts.
- Practice your data skills. Data literacy also involves practical skills that allow you to work with data effectively, such as finding, collecting, cleaning, analyzing and visualizing data. You can practice these skills by using various tools and platforms that enable you to access and manipulate data easily. For example, you can use [Modern] Excel [with Power Query] for spreadsheet analysis, Power BI for data model and report creation, and Python for working with code in a notebook.
- Develop your data mindset. Data literacy also requires a mindset that embraces data as a valuable asset and a source of insight. You can develop your data mindset by cultivating curiosity, critical thinking and creativity with data. You can do this by asking questions about the data you encounter, challenging assumptions and biases, exploring different perspectives and scenarios, and finding new ways to communicate your findings.
- Foster a data culture. Data literacy also depends on the culture and environment that surround you. You can foster a data culture by engaging with other people who share your interest in data, such as colleagues, mentors or peers. You can do this by joining online communities, forums or groups that discuss data-related topics, attending webinars, workshops or events that showcase best practices or case studies with data, or participating in projects, competitions or challenges that involve working with real-world data.
- Make data-driven decisions. Data literacy also implies using data to inform your decisions and actions. You can make data-driven decisions by applying a systematic process that involves defining your problem or goal, gathering relevant data, analyzing the data for patterns and insights, presenting your results in a clear and compelling way, and evaluating the impact of your decision. You can use this process for any kind of decision-making scenario, whether personal or professional.