Case Studies - Data Compression

Client: ESRI

Client Business Need: ESRI had a need to solve spatial data delivery problem as well as reduce data storage requirements for its products. Since huge volumes of spatial data were being processed by various kinds of GIS applications, it required an efficient way to compress, transmit, store and access spatial and attribute information. For example, a complete streets network data (30+ million streets) for continental U.S. takes as much as 20 GB if stored uncompressed, requiring 30-40 CDs of data to be shipped along with the application itself.

Technical Response: Invented data compression technology incorporating a number of sophisticated methods of statistical data analysis, complex compression algorithms and efficient code written in pure C++, achieving compression ratios of up to 1:50.

The technology allows compressing both spatial and attribute information, so that dBase and ESRI Shape Files could be compressed to maintain spatial database entity.

The decompression module provides a generic C++ API, which allowed it to be easily incorporated into multiple GIS applications.

Client Result: The usage of the data compression technology reduced the number of CDs required to deliver spatial data from 40 to 1, which provided significant savings, as well as simplified software installation and reduced storage requirements for the software user.

It also significantly reduced bandwidth requirement for data delivery via broadband and wireless networks. Most importantly, it allows working with large amounts of data on mobile devices with smaller storage.