Portable Database Image
This article may have been previously nominated for deletion: Wikipedia:Articles for deletion/Portable Database Image exists. It is proposed that this article be deleted because of the following concern:
If you can address this concern by improving, copyediting, sourcing, renaming, or merging the page, please edit this page and do so. You may remove this message if you improve the article or otherwise object to deletion for any reason. Although not required, you are encouraged to explain why you object to the deletion, either in your edit summary or on the talk page. If this template is removed, do not replace it. This message has remained in place for seven days, so the article may be deleted without further notice. Find sources: "Portable Database Image" – news · newspapers · books · scholar · JSTOR Nominator: Please consider notifying the author/project: {{subst:proposed deletion notify|Portable Database Image|concern=No assertion as to why this file format is notable}} ~~~~Timestamp: 20061021082225 08:22, 21 October 2006 (UTC) Administrators: delete |
Portable Database Image (.pdi) is a loss-less format designed for analytics, publishing and syndication of complex data. The .pdi footprint is typically 100 to 1000 times smaller than the footprint normally found in structured data files or database systems, and is rendered without any loss of detail. A .pdi runs in the main memory of a users’ computer without disk or network IO.
The .pdi is a digitally rights protected, encrypted data source that can be accessed by any ODBO compliant OLAP tool, Microsoft Excel and the Panoratio Explorer GUI.
The .pdi presents detailed discrete or binned data without pre-calculation or cardinality reduction. It allows for real-time correlation and relationship exploration of unrestricted bounds — throughout all dimensions. They (.pdi’s) have been tested in excess of 5,000 dimensions and 500 million rows of information, with query response times in the .1 to 8 second range.
Additionally, because of patented techniques used in .pdi generation, patterns found in the data are summarily exposed, allowing for instant predictive and descriptive data mining. Yield optimizations, segmentation, outcome optimizations and simulations are all dynamically supported by the .pdi format. Users are constantly presented with the most changed and most highly correlated dimensions affected in every query as discovered in the patterns of the historical data.
The .pdi format, generation process, and GUI, were invented by Dr. Reimar Hoffman and Dr. Michael Haft from Siemens AG Artificial Intelligence/Machine Learning .