SAP Data Visualization

Data Visualization for SAP Users: An Overview and Key Considerations

What is Data Visualization?

Data visualization is the concept of using pictures to explain data. Pictorial or graphical representations of information and data can be created through visual elements such as charts, graphs, and maps. Data visualization tools can make data more accessible to decision makers by presenting trends, outliers, difficult concepts, and new patterns in a visually appealing way. Data visualization is often considered a blend between science and art.

Data Visualization Tools and Capabilities for SAP Customers

SAP provides data visualization and analytics software with SAP Lumira.

Strong data visualization capabilities can also be achieved by integrating SAP Analytics Cloud into your business intelligence landscape.

SAP HANA can enable real-time in-memory computing to third-party tools and to activities such as data visualization. In this article, Deloitte writes about how you can adopt SAP HANA as a backbone for visualization applications.

Vendors including Qlik, SimpleFi Solutions, TIBCO, and Pyramid Analytics provide data visualization capabilities in their products.

Key Data Visualization Considerations for SAPinsiders

Data Visualization for SAP Users: An Overview and Key Considerations

What is Data Visualization?

Data visualization is the concept of using pictures to explain data. Pictorial or graphical representations of information and data can be created through visual elements such as charts, graphs, and maps. Data visualization tools can make data more accessible to decision makers by presenting trends, outliers, difficult concepts, and new patterns in a visually appealing way. Data visualization is often considered a blend between science and art.

Data Visualization Tools and Capabilities for SAP Customers

SAP provides data visualization and analytics software with SAP Lumira.

Strong data visualization capabilities can also be achieved by integrating SAP Analytics Cloud into your business intelligence landscape.

SAP HANA can enable real-time in-memory computing to third-party tools and to activities such as data visualization. In this article, Deloitte writes about how you can adopt SAP HANA as a backbone for visualization applications.

Vendors including Qlik, SimpleFi Solutions, TIBCO, and Pyramid Analytics provide data visualization capabilities in their products.

Key Data Visualization Considerations for SAPinsiders

Appeal to the human mind and drive real user adoption. Mico Yuk, CEO of BI Brainz, has been in the data industry since before SAP was considered a leader in the BI market. She witnessed SAP’s acquisition of BusinessObjects and the Xcelsius visualization tool. In this Q&A article published in 2015, Yuk describes her initial passion for data visualization, the importance of being able to prove any number that you present, and the criticality of creating well-designed visualizations. “No matter how great the data, if the data visualization is poorly designed, no one will use it,” Yuk says.

Solve problems and provide elegant solutions. In an SAPinsider event presentation, SAP’s Ingo Hilgefort, Global Product Evangelist, SAP Analytics Cloud, describes best practices for data visualization. One rule of thumb: Good design means never having to say “click here.” And, be aware of the impact of title, color, and orientation. These components can set the intension of your visualization and, when altered, set a completely different impression.

Consider color and contrast. According to Hilgefort, humans can only effectively differentiate around seven color steps. Therefore, selecting the correct color scheme for your message is important to avoid simply adding qualitative colors that might confuse your audience. A sequential color scheme, says Hilgefort, can be used to order values from low to high. He recommends a divergent color scheme be used when the values are ordered and there is a critical mid-point (e.g., an average or zero). And a qualitative scheme, he says, can be used when data falls into distinct groups (e.g., products) and requires contract between adjacent colors.