Sat. Nov 20th, 2021

What is Visual Analytics?

Visual analytics is the use of sophisticated tools and processes to analyze datasets using visual representations of the data. Visualizing the data in graphs, charts, and maps helps users identify patterns and thereby develop actionable insights. These insights help organizations make better, data-driven decisions.

Sometimes confused with data visualization, visual analytics isn’t simply a matter of representing data graphically. Rather, modern, interactive visual analytics makes it easy to combine data from multiple sources and deeply analyze the data directly within the visualization itself. Further, AI and machine learning algorithms can offer recommendations to help guide the user’s exploration.

Visual Analytics Benefits

The overall benefit of visual analytics is that it helps turn massive data sets into business insights which can have a major positive impact on your organization.
  1. Share findings and track progress: Interactive reports and dashboards help users track, organize and share key performance indicators across an organization.
  2. Make faster decisions: Users can understand data insights much more quickly by seeing and working with data sets when they are in a visual format.
  3. Explore data more easily: Self-service analytics tools which allow users to interact with data in a visual context allows them to discover hidden relationships and patterns in the data without relying on help from IT.
  4. Promote data literacy: Making data easier to work with and understand democratizes data analytics, getting more people across and organization involved.

 

Visual Analytics Examples

Explore these examples based on KPIs relevant to specific roles.

1. Marketing

In this example, visual analytics helps a marketer boost ROI by letting them see and understand each phase of the customer life cycle. This is made possible by connecting data from the CRM, advertising tools, and web analytics platform.

2. Supply Chain

Big data visual analytics can help supply chain managers immediately find connections between complex, disparate data sources by surfacing KPIs and allowing interactive exploration.

3. Sales

Sales managers benefit from the clean, organized presentation of sales data to increase revenue, improve forecasting, and identify key trends.

4. Human Resources

Visualizations can provide HR executives the ability to review and analyze KPIs in a single dashboard. This example shows data on employees by role and by location, plus key data such as gender ratio and training progress.

5. Finance

In this example, a loan manager at a consumer bank can explore how different regions, product and loan officers perform over time and drive the biggest impact on revenue and margins.

6. IT Visual Analytics

IT managers can leverage data analytics and visualization to better anticipate upcoming technology needs and identify underused systems and applications.

Visual Analytics Best Practices

To help you be successful with visual analytics, we’ve compiled the following key best practices to be aware of.

Define goalsBefore you begin, be sure to define specific goals for your visual data analysis work. What specific questions are you trying to answer?

Integrate and manage the dataYour source data needs to be transformed into clean, business-ready information. You’ll need to combine and replicate data from a variety of sources and then bring it into standardized formats stored in a repository such as a data lake or data warehouse.

Simplify visualizationsChoose the right visual technique to present your story in the simplest way possible. Learn more about visualizing data.

Get InspiredSee the ten most compelling and interesting data visualization examples from recent years.

Read more.

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