What Is The Difference Between Data Analysis And Data Visualization?

The two terms data analysisand data visualizationseem to have become synonymous in everyday language in the wider data community.

Numerous job adverts focus on data visualization skills while not necessarily specifying the importance of analytical skills. Job titles reflect this trend with the emergence of new roles such as ‘data artist’, ‘data visualization expert’ and ‘data storyteller’, but organizations are still looking for people who can extract value from their data, so these roles must include analytical skills.

Data analysis is an exploratory process that often starts with specific questions. It requires curiosity, the desire to find answers and a good level of tenacity, because those answers aren’t always easy to come by.

Data visualization involves the visual representation of data, ranging from single charts to comprehensive dashboards. Effective visualizations significantly reduce the amount of time it takes for your audience to process information and access valuable insights.

However, that’s not to say that the two never work in harmony – far from it. In working with data, analysis should come before the visual output, but visual analytics can be an excellent method for running more effective analyses.

Visual analytics involves the process of building different charts with your data to give you various perspectives. This helps you identify outliers, gaps, trends and interesting data points that warrant further investigation.

The process of analysis is similar to the design process depicted through ‘the design squiggle’ by Damian Newman.

On the left you have the process of analysis, research and visual exploration which turns into more clarity, an understanding of the data and the finding of insights as you move to the right. Only at the conclusion of the process comes the dashboard, the output that brings everything together in a neatly packaged output.

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In your job as a data analyst or visualization expert you will likely be creating dashboards for your stakeholders. What is the role of the dashboard in the entire analytical process, though?

Many people see it as the ultimate deliverable that will answer all their questions. I suggest, however, that the dashboard is just a starting point for further discussion and analysis.

A dashboard, infographic or data story can be an excellent and very effective method for communicating insights. It shouldn’t stop there, though. At the point when your stakeholders work with their interactive dashboard, printed PDF report or the screenshot they have received by email, that is when further discussions should come about. It shouldn’t be the end point.

Look at the below Sales & Profitability dashboard created by Ann Jackson. It is a visually compelling, cleanly designed summary of the data that shows the changes over time, the geographical differences, losses for certain product categories and summarizes key performance indicators as numbers.

Would Ann hand this dashboard over to her stakeholders and call it done? No, because now the real discussions start. Ann can sit with her audience and drill into further details to explore why certain results have come about and identify opportunities for improving business performance. Further investigation of the data, exploring it with your audience, that is the value you add as an analyst, beyond producing dashboards. They give you an excellent basis for these discussions but shouldn’t be the end point.

One piece of advice I have shared with many analysts in the wider community is to not simply visualize data, but to show insights and to demonstrate your analytical skills.

Many tools make it very easy to build visualizations quickly. Your role as an analyst is to ensure that the information they present is accessible, easy to understand and clear.