You’re a database administrator. How can you get the most out of your data visualization tools?

1 Know your audience

Before you create any data visualization, you need to understand who your audience is and what they want to learn from your data. Different audiences may have different levels of familiarity, interest, and expectations with your data. For example, if you are presenting to senior executives, you may want to focus on the key takeaways and recommendations, while if you are presenting to technical peers, you may want to show more details and analysis. Knowing your audience will help you decide what type of data visualization to use, how much information to include, and how to tailor your message.

2 Choose the right format

Data visualization tools offer a variety of formats, such as charts, graphs, maps, dashboards, and interactive elements. Each format has its own strengths and weaknesses, and you need to choose the one that best suits your data and your purpose. For example, if you want to show the distribution of a variable, you may use a histogram or a box plot, while if you want to show the relationship between two variables, you may use a scatter plot or a line chart. You also need to consider the size, shape, and layout of your data visualization, and make sure it is readable and attractive.

3 Follow the design principles

Data visualization is not only about presenting data, but also about designing it. To make the data visualization clear, consistent, and compelling, you need to consider several design principles. Colors, fonts, and shapes should be appropriate for your data and audience. Labels, titles, legends, and annotations should be used to explain the data and message; simple and concise language should be used. Scales, axes, and grids should be used to show the context and range of data; they should not be misleading or distorted. Filters, sorting, and grouping can be used to highlight and compare relevant data; however, too much or too little data should be avoided. When applied correctly, these principles can help ensure that your data visualization is effective.

4 Test and refine

The final step of creating a data visualization is to test and refine it. You need to ensure that the data visualization is accurate, complete, and reliable, as well as effective, engaging, and persuasive. To do this, ask yourself questions such as does your data visualization answer the question or problem you want to address and does it show the data and message you want to convey? Additionally, consider if the data visualization appeals to your audience's needs and preferences, as well as follows best practices and standards of your field and organization. Moreover, get feedback from others such as colleagues, clients, or users to see how they react to your data visualization. Utilize their feedback to improve and optimize your data visualization.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?