Unraveling Data Fear: Essential Knowledge for Data Afraid Newcomers (7 Key Points)
In today's data-driven world, fear of data is a common challenge in the workplace, but it can be overcome with the right approach. Data literacy, the ability to read, work with, and communicate about data in proper context, is a valuable skill that can help individuals and organisations improve outcomes, including in a business context.
Data comes in various forms, with two main types: quantitative and qualitative. Quantitative data, also known as numerical data, can be divided into two main types: discrete and continuous. Discrete data, such as the number of people in a crowd, exists in distinct values, while continuous data, like length, exists on a continuum. On the other hand, qualitative data is descriptive, based on observations that cannot be measured, such as gender or language spoken.
Data collection methods are widespread, including surveys or questionnaires, interviews, observations, and experiments. However, it's important to ensure the data is high quality by checking if it's from a reputable source, if it shares information about how the data was collected, if it's open or restricted, and if it's the right data set for the job at hand.
Data management can be a team job and requires attention to detail and follow-through. One of the key aspects of data management is data visualisation, which helps translate numbers into meaningful insights for decision-making. For beginners looking to improve their data literacy by creating and understanding data visualisations, there are several simple templates and tools available.
Venngage offers simple templates to help beginners create data visualisations. Datawrapper is another free tool that provides simple and intuitive templates for creating maps and charts. Google Charts and Sheets also provide a range of templates for creating basic visualisations. For more advanced needs, tools like Tableau and Microsoft Excel and Power BI offer resources and guides for creating insightful dashboards and charts.
When choosing a template or tool, consider the type of data you want to visualise and the message you want to convey. Common types of visualisations include bar charts, pie charts, histograms, box plots, line graphs, and scatter plots. Remember, the key to effective data visualisation is to ensure that your visualisations are clear, concise, and accurately convey the insights you want to share.
In addition, it's important to be aware of outliers and anomalies in the data, as these can indicate errors in the data and/or places for further study and analysis. When sharing data, describe frequencies or percentages, distributions of the data, or comparisons in the data, but avoid equating correlation with causation.
Most organisations are lagging behind in data literacy skills, according to Gartner. To bridge this gap, it's crucial to keep learning and avoid misusing data to mislead others. Data-driven decision-making improves business performance, as stated in Harvard Business Review. So, let's embrace the power of data and start building our data literacy skills today!
[1] Venngage: https://www.venngage.com/ [2] Datawrapper: https://datawrapper.de/ [3] Tableau: https://www.tableau.com/ [4] Google Charts and Sheets: https://developers.google.com/chart/interactive/docs/gallery
In the realm of education-and-self-development, learning effective data visualization techniques is a valuable strategy for lifestyle improvement, especially in the technology-driven world we live in today. For instance, tools like Venngage, Datawrapper, Google Charts and Sheets, Tableau can help beginners understanding and creating data visualizations, with Venngage offering simple templates and Datawrapper providing free, intuitive templates for maps and charts. These skills are not only beneficial for personal data literacy but also contribute to a more data-driven lifestyle, enhancing decision-making in a variety of contexts, including business and lifestyle choices.
){kind=link}