Massachusetts Mutual Life Insurance has been granted a patent for systems and methods that allow for scaling up data processes while remaining compliant with ACID principles. The technology enables sourcing, cleansing, and fusion of data from various sources, generating reports. The patent also covers the ability to modify data files and update the fused dataset and report in real-time based on the modifications. GlobalData’s report on Massachusetts Mutual Life Insurance gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Massachusetts Mutual Life Insurance, predictive modeling techniques was a key innovation area identified from patents. Massachusetts Mutual Life Insurance's grant share as of June 2023 was 1%. Grant share is based on the ratio of number of grants to total number of patents.

The patent is granted for a method of data cleansing, fusion, and real-time report generation

Source: United States Patent and Trademark Office (USPTO). Credit: Massachusetts Mutual Life Insurance Company

A recently granted patent (Publication Number: US11669538B1) describes a method and system for data cleansing, fusion, and reporting within an Extract, Transform, and Load (ETL) application. The method involves performing a data cleanse on multiple datasets sourced from different databases, generating a cleansed dataset within the ETL application. A data fusion process is then performed on the cleansed dataset, integrating the multiple datasets and generating a fused dataset.

Based on the fused dataset, a report is generated by the processor. After the report is generated, the method allows for modifying a cell value in the original set of data files without modifying the original datasets. The fused dataset is then updated based on the modified cell value, and the report is updated in real-time based on the updated fused dataset.

The method also includes populating a column-oriented database with the fused dataset sourced from the ETL application. This allows for generating the report based on the fused dataset sourced from the column-oriented database.

The data cleanse process involves modifying or removing inaccurate data from the datasets. Additionally, the data fusion process resolves semantic conflicts within the cleansed dataset.

The patent also describes the use of a multidimensional dataset from a massively parallel processing (MPP) database of a cloud computing platform. The MPP database stores records from external data sources, and the multidimensional dataset is generated within the cloud computing platform.

The system described in the patent includes a processor configured to perform the data cleanse, data fusion, and reporting processes. It also includes the capability to update the fused dataset and the report in real-time based on modifications made to the original data files.

Overall, this patent presents a method and system for efficient data cleansing, fusion, and reporting within an ETL application, allowing for real-time updates and integration of datasets from different databases. The use of a column-oriented database and a multidimensional dataset enhances the performance and scalability of the system.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.