Decision making, across industries, have grown to rely heavily on data. However, the volume of data that a business needs to take proactive and preventive decisions are often too much for a non-number manager to understand. This is where data visualization in business comes into the picture.
Through visualization, managers are better able to understand and explain the direction in which their domains are moving. However, it is one thing to make infographics and explain a campaign performance and it is a completely other thing to convert Boeing’s takeoff and landing data into a visual format.
For managers, this means that they will have to keep a better set of data visualization practices in place to be able to convert the millions of data into an image-based type. A manager who wishes to get great at data visualization process often begins by learning the rules. When should I use a line graph? What is too many when it comes to colors? How can I make the data readable? Do I have to start my x-axis at zero or hundred? While we cannot give an answer to all these questions, we can get you acquainted with the best data visualization practices.
Something that would help you in converting all these massive amounts of data sets into digestible format.
What is data visualization in business?
Data visualization is the representation of information and data in graphs, maps, charts, or other visual format. The process makes it easy for the stakeholders to look at the trends, identify correlations, and identify the outliers in their data and overall business performance.
Considering the ever growing rise in big data, effective data visualization is a crucial step in converting massive data points into a compelling story and actionable insight. All in all, the data visualization process plays a massive role in increasing the revenue, efficiency, and the profitability level.
What are the benefits of data visualization principles and practice?
Data visualization goes beyond the transformation of data in visual formats. It is a key business intelligence capability which is used to highlight the key aspects of a data while highlighting business impacting insights. Insights that help managers make smarter decisions.
Here are some of the benefits of data visualization.
Expedited decision-making: By viewing data sets in a visual format, managers are able to understand the business movement at a quick glance. It leads to saving the time that goes in studying a pile of numbers and sheets.
Greater data exploration: Data visualization tools enable the users to interact with data to discover patterns, see the data relations, and unravel the actionable insights – all without the need of involving a data engineer.
Track business initiatives: The data visualization dashboards help managers track the performance of their initiatives by looking at how the business operations affect the key performance indicators (KPIs).
Increases the ROI on analytics: Since visuals make it easy to understand data, it becomes easier for managers to improve company’s growth by taking decisions on-time.
What is the right type of data visualization for a business?
Gone are those days when data was presented in bullet formats or in bar graphs. Today, as the variety and volume of data has increased, so has the types of data visualization. Let us look at the different types of data visualization a manager can choose from depending on what their requirement is.
Change over time
The purpose of these charts is to show the data has been changing over a period of time. It could be data around the product sale over 5 years or simply the user demand over time.
Chart types:
- Area Timeline
- Circles Timeline
- Calendar Heatmap
- Column-Line Timeline
- Column Timeline
- Gantt Chart
- Fan Timeline
- Scatterplot-Line Timeline
- Line Chart
- Slope Chart
- Seismogram, etc.
Distribution
The purpose of this data visualization type is to show how the data has been spread across a certain group. This helps managers with spotting the commonalities and outliers. An example of this could be public officials wanting to see the income characteristics of a population.
Chart types
- Boxplot
- Barcode
- Dot plot
- Cumulative curve
- Histogram
- Violin, etc.
Part-to-whole
