Have you ever found yourself staring at an extensive data set, attempting to extract a core narrative and arrive at actionable insights? Dealing with data laid out in rows and columns can prove daunting for comprehension and reaching meaningful conclusions, let alone making informed decisions. To facilitate effective decision-making, businesses must be able to extract, organize and present data in a visual format that resonates with decision-makers.
An advanced degree — such as the online Master of Business Administration (MBA) concentration in Business Analytics program from Carleton University — equips business professionals to use data visualization best practices for critical decision-making in any industry.
What Is Data Visualization?
Data visualization frames storytelling through a visual medium, using familiar visual elements, including graphics like charts, plots, infographics and even dynamic animations. By utilizing these visual depictions, intricate data correlations and insights derived from data analysis can be conveyed in a manner that simplifies comprehension. Data visualization software tools enable data analysts to communicate underlying patterns, emerging trends and notable deviations to put business decision-makers in a position to act decisively and confidently.
Enhancing Comprehension and Prompting Decisive Action Through Visual Information
Establishing dynamic visual dashboards that provide real-time data accessibility to various business units is pivotal for fostering focus, unifying diverse audiences, transcending expertise levels, encouraging shared understanding and elevating business performance. These statistics underscore the usefulness of visual information:
- According to the Massachusetts Institute of Technology (MIT), visual information constitutes 90% of data transmitted to the brain
- The human brain can decipher an image in a mere 13 milliseconds (per MIT)
- According to one paper in SSRN, 65% of humans are visual learners and need to see information to retain it
How do these insights translate into business analytics and data presentation? Research from Robert Horn at Stanford University, using studies from the Wharton School of Business, reveals that visualizations significantly enhance influence, believability, responsiveness, decisiveness and meeting effectiveness. The research also suggests that data visualizations can shorten meeting times by 24%.
Ultimately, the difference between verbally presenting data findings or visually presenting them is between merely influencing or effectively convincing an audience. Being convincing requires helping audiences to comprehend and interpret data findings accurately, see developing patterns, notice key correlations and then have strategic discussions that lead to intelligent decision-making.
Key Types of Data Visualization Tools and Techniques
Modern software seamlessly incorporates a range of data visualization tools, offering users intuitive interfaces to choose and create visualizations that suit their data and goals. With interactive dashboards and easy controls, professionals can effortlessly generate various visuals, enabling quick exploration of data insights and trends for informed decision-making. An analyst’s choice of data visualization tools and techniques hinges on the data type and objective. Some widely used examples include:
- Infographics: Streamline complex data into easily digestible formats.
- Bar charts: Compare different categories of quantities of data.
- Pie charts: Divide a circle into segments to represent the proportions of a data set.
- Line charts: Display data points as a series of data connected by straight lines.
- Fever charts: Track changing data trends over time.
- Histograms: Graphically organize data into frequency ranges.
- Network graphs: Visualize connections and relationships between entities.
- Box plots: Depict data distribution through a plot, showing median, quartiles and outliers.
- Graphs: Analyze time series relationships.
- Heatmaps: Leverage color to convey data faster than numbers.
- Scatter plots: Illustrate the relationship between two variables.
Proficiency with visualizations is developed through practice so that the creator recognizes the strengths and limitations of each type and learns how to select the most fitting tools for diverse purposes. While tables offer comprehensive detail, they hinder the observation of overarching trends. Bar graphs and line charts facilitate variable comparisons yet may lack contextual depth. Scatterplots and bubble charts unveil correlations, while pie charts delineate fractions within a whole.
Through practicing, visual tool creators refine their ability to present information in a digestible manner. This entails decisions on alphabetic, numeric or sequential formats. Left-to-right layouts enhance text legibility, and arranging numeric data in descending order fosters ease of comprehension. In line graphs, a balance of variables is paramount, with two or three being optimal.
Develop These Skills in the Carleton Online MBA Concentration in Business Analytics
Carleton University’s online MBA concentration in Business Analytics program is offered by the AACSB- and NIBS-accredited Sprott School of Business. One of the key concentration courses is Data Visualization for Analytics, which covers principles, techniques, technology and applications of data visualization for decision-making. These concepts are further explored throughout the curriculum.
If you want to become an influential analyst or aspire to other decision-making roles that rely on successfully using data visualization in both oral and written reports, this degree program can support your ambitions.
Learn more about Carleton University’s online MBA concentration in Business Analytics program.