Qlik Technologies. has been granted a patent for a method that involves partitioning data tables into blocks, generating bidirectional indexlets for efficient data retrieval, and creating a global attribute list to optimize query processing based on user interface selections. GlobalData’s report on Qlik Technologies gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Qlik Technologies, was a key innovation area identified from patents. Qlik Technologies's grant share as of July 2024 was 48%. Grant share is based on the ratio of number of grants to total number of patents.
Data model partitioning and indexlet generation method
The patent US12050645B2 outlines a method and apparatus for efficiently processing queries associated with a data model that includes at least one table. The method begins with receiving a query based on user interface selections linked to specific attributes within the table. It involves partitioning the table into blocks of rows and generating indexlets for these blocks, which serve as references for the data. A global attribute list is created, linking each attribute to its corresponding indexlet, indicating whether specific values are stored in the rows. This structured approach allows for the targeted loading of relevant portions of the data model into the memory of a computing device, even when the data model exceeds the device's memory capacity.
Additionally, the claims detail various enhancements to the method, such as the ability to process queries, generate an attribute-to-attribute index, and facilitate parallelized operations on the data model. The apparatus described includes processors and memory that execute instructions to perform these tasks. The method also allows for sequential loading of the data model and includes provisions for partitioning additional tables and generating corresponding indexlets. Overall, the patent presents a comprehensive framework aimed at optimizing data retrieval and processing in complex data models.
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