Data Analysis with a Spatial Dimension
This post is part of Transformational Tuesdays: A Series on SAP HANA Business Value from the SAP HANA Solution Management team celebrating 10 years of SAP HANA in 2020.
The analysis of data is at the core of nearly every decision a company can make. Data analysis is simply a process of obtaining raw data and converting it into useful information, or insights, so that businesses can operate with high levels of efficiency. Once you identify the data needed to operate, you can start to collect, process, clean and then ultimately visualize the data.
So how do businesses determine what data to collect? Start with the end in mind. Some questions often considered might be:
- What am I selling?
- Who are my customers?
- Why do they need this good or service?
- When will they need it?
- How will I go-to-market?
One of the most fundamental and often overlooked questions though is “where?”
The question of “where” is becoming increasingly critical to our business outcomes. This means we must investigate spatial relationships, processes and patterns to better understand the locations where business activities occur.
Consider some of the questions we might ask about our business activity as it relates to location in order to generate new and valuable insights:
- Where are our customers?
- Where do my products sell best?
- Where are my business assets (equipment)?
- Where should I locate my distribution network for optimal customer service (logistics)?
- Where are my goods coming from (traceability)?
- Where are the weaknesses in my supply chain?
- Where are my urgent needs (especially in the world of COVID-19)?
SAP makes it easy to store and process spatial data. In SAP HANA, business data is easily augmented with spatial aspects and SAP Analytics Cloud (SAC) can subsequently be used to visualize this data. This capability allows users to decrease the time to action as well as the effort necessary to process.
Some key resources for getting started with spatial processing in SAP HANA can be found here:
In addition to the above technical references, the following are some examples of spatial processing in action to give you some ideas for how it may apply in your domain:
- Good Things Come Together: DBeaver, SAP HANA Spatial & Beer
- Predicting Taxi Destinations with SAP HANA
- The Impact of Geospatial Features on Machine Learning
In addition to our own tools at SAP, we also participate in the broader ecosystem of spatial offerings. SAP HANA was the first in-memory database and the first DBaaS to be certified as an Esri geodatabase. This allows for advanced use cases and speeds up the processing underneath Esri while also reducing or eliminating the ETL between business and GIS systems as I mentioned in a previous blog post. SAP HANA also supports open source tools like QGIS.
In the world of COVID-19, analyzing data has never been more important. With SAP HANA, however, businesses now have a common database for both their business and spatial data to help deliver the critical answer to “Where?”.