As the COVID-19 pandemic began to threaten lives around the world, SAP NS2 realized something needed to be done. So we followed a logical approach, focusing on our expertise, to help.
Our focus was to collect and leverage data to better understand, track, plan for, and help others identify ways to contain the virus. Because we realized the importance of data insights early on in the pandemic, we were able to find analytic solution sets that could be quickly and effectively deployed to keep pace with the growing data landscape.
And it was all done by using SAP Analytics Cloud.
Why SAP Analytics Cloud?
We chose SAP Analytics Cloud (SAC) for its codeless, drag-and-drop UX simplicity, as well as its multi-functional capabilities. This would prove to make the process of developing a comprehensive and visually appealing overview possible in a short amount of time.
The software combines predictive and forecasting capabilities, such as triple exponential smoothing or linear regression, with customizable canvases for building analytic dashboards. The end result is a set of data visualizations that turn complex information into situational awareness.
Built from the SAP Cloud Platform as an entirely web-based SaaS solution, SAC takes full advantage of the most fundamental cloud capabilities: scalability, agility, and on-demand deployment.
It also has full integration with SAP, third-party, and open-source databases, apps, and services. This connection provides live insights into multiple data sets without the need to load it directly into the system.
End users can then see the latest updates without having to initiate any formal extract, transform, load (ETL) process.
This flexible integration goes one step further with automatic access and connection to an R server and an Esri server. What this means is that it is possible to instantly take advantage of the geospatial capabilities of SAC while visualizing those geo-objects on Esri maps and to write custom R scripts to use bleeding-edge machine learning algorithms on your data.
From Data to Dashboard
Data for the SAP NS2 analytic sessions came from two sources: A Johns Hopkins GitHub repository that had aggregated official confirmed cases, total deaths, and total recoveries counts from health organizations all around the world and the official IHME forecasts from their site dedicated to the COVID-19.
After uploading into the system, the individual columns of data were immediately categorized as numeric, categorical, a date, or a timestamp. From there, we were able to build out relationships and hierarchies between data columns, both logically and geospatially.
There are many different template design options, including blank canvases, all of which can serve to give important insights into the design of dashboards with maps, graphics, KPI trackers, and reactive filters. Even though charts in the dashboard must call out to an R server, the load times for these complex graphics takes only seconds.
COVID-19 and Beyond
SAC was designed to incorporate ease of use with powerful analytics and visualization tools. The democratization of data analytics opens the door to users of all skill levels to build compelling stories, predictive tools, and complex maps.
This also gives business analysts, statisticians, and data scientists avenues for low-level operations with more advanced features such as R integration.
Moving forward, SAC has proven to be a fundamental tool for office processes such as supply chain and accounting. It can also be applied to mission-focused requirements such as tracking of a global pandemic.
Agencies can now access invaluable data insights quickly and without a lot of expensive overhead or highly trained personnel.
You can find out more about SAP Analytics Cloud here.
