17 Crucial Data Visualization Techniques for Professionals
The ability to convey information with clarity has become supremely important in today’s data-centric age. And even though numbers and raw data are significant, they tend to be missing impact when presented alone. This is where data visualization comes in. As a matter of fact, data visualizations, when executed well, not only inform users but are also able to persuade and inspire the decision makers in an organization. Data visualizations serve as the means to express and explain otherwise complex findings in short and succinctly at that. It must also be noted that they help put the spotlight on important insights and narrate compelling stories through data.
So, folks, time to talk about what this blog is about: no points for guessing, there. We will, today, talk about 17 different data visualization techniques for professionals to help you better engage with your data visualization services provider.
What Refers to as Data Visualization?
Data visualization is the most common way of making an interpretation of complicated information into visual form — — which are not difficult to understand. The idea of data visualization is to empower people to recognize patterns and connections that could, in some way or another, be missed. So, no matter if you are a professional in business or academia, or simply someone looking to make sense of data, mastering data visualization techniques can completely transform your approach.
Top Data Visualization Techniques You Must Know About
- Pie chart: Pie charts are a terrific choice for illustrating the components of a complete entity. These charts present segments in proportion to their share of the whole, making it easy to grasp each category’s share. Pie charts are ideal for showcasing a small set of categories.
2. Bar chart: Bar charts help compare quantities among different categories. They use bars of different lengths to depict the value of each category. The orientation, i.e. horizontal or vertical, will be based on factors such as label length and the number of categories being compared.
3. Histogram: Histograms focus on illustrating the distribution of one continuous variable. They put together the information range into bins, and show the frequency of data points falling inside each bin through bars.
4. Gantt chart: A Gantt chart is utilized in project management, visualizing tasks across a horizontal timeline, where the bars demonstrate the duration of each undertaking and their interdependencies.
5. Heat map: A heat map portrays information by applying a color gradient to a grid to picture complex information where there needs to be focus on either intensity or value.
6. Box and whisker plot: A box and whisker plot offers a succinct outline of the distribution of a solitary variable. It incorporates a box representing the interquartile range, with the median portrayed by the middle line. Whiskers stretch out to the lowest and highest data points inside 1.5 times the IQR.
7. Waterfall chart: A waterfall chart tracks the combined impact of both positive and negative contributions towards a final value. It uses stacked bars, whether positive or negative, to show how various factors influence the eventual outcome.
8. Area chart: An area chart highlights the magnitude as well as shifts over time or another continuous variable. It uses lines interconnected by smooth curves to form a filled area beneath the line.
9. Scatter plot: A scatter plot analyzes the correlation between two continuous variables. Each data point, referring to one observation, is plotted along horizontal and vertical axes corresponding to the two variables.
10. Pictogram chart: A pictogram chart uses miniature icons to symbolize data quantities, with the quantity of icons displayed aligning with the data point.
11. Timeline: A timeline showcases milestones, events, etc. arranged chronologically.
12. Highlight table: A highlight table unites a conventional tabular format with visual cues to put the focus on certain data points. It employs techniques like color coding, font variations, etc.
13. Bullet graph: A bullet graph compares a solitary performance metric with a target and highlights the expected value range. It uses a bar to denote the actual value and a horizontal line for the target.
14. Choropleth map: A choropleth map shows information about geographical locations and utilizes colors or patterns on a map to portray the information values related with every location.
15. Word cloud: A word cloud emphasizes words based on their frequency within a given text. Words that occur more frequently are depicted in larger fonts.
16. Network diagram: A network diagram helps visualize the connections among entities or nodes within a network. This technique is employed to visualize different interconnected systems.
17. Correlation matrices: A correlation matrix shows the correlation coefficients among different variables in a tabular layout.
That’s about it, folks. Which of these data visualization technique(s) will you set to work for your project?
