Salesforce, inc. (20240378220). Query Semantics for Multi-Fact Data Model Analysis Using Shared Dimensions simplified abstract

Query Semantics for Multi-Fact Data Model Analysis Using Shared Dimensions

Organization Name

salesforce, inc.

Inventor(s)

Thomas Nhan of Seattle WA (US)

Tyler Martin of Seattle WA (US)

Franz Gustave Amador of Seattle WA (US)

Marian Simo Boitel of Seattle WA (US)

Jeffrey Mark Booth, Jr. of Seattle WA (US)

Russell Steven Paul-jones of Duvall WA (US)

Jinbo Feng of Medford MA (US)

Query Semantics for Multi-Fact Data Model Analysis Using Shared Dimensions - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240378220 titled 'Query Semantics for Multi-Fact Data Model Analysis Using Shared Dimensions

The abstract of the patent application describes a computing device that receives user input specifying two data fields, constructs dimension and measure subqueries, retrieves tuples, and generates data visualizations based on the extended tuples.

• The computing device constructs dimension subqueries based on characteristics of the data fields and objects to which they belong.
• Join types are determined for combining data rows with values from the specified data fields.
• Measure subqueries are constructed and executed to retrieve additional tuples.
• Extended tuples are formed by combining data from the dimension and measure subqueries.
• Data visualizations are generated and displayed based on the extended tuples.

Potential Applications: - Data analysis and visualization tools - Business intelligence software - Data mining applications

Problems Solved: - Efficient retrieval and visualization of complex data sets - Streamlining the process of combining data from different sources

Benefits: - Improved data analysis capabilities - Enhanced decision-making based on visualized data - Increased efficiency in handling large datasets

Commercial Applications: Title: Advanced Data Visualization Software for Business Intelligence This technology can be used in industries such as finance, marketing, healthcare, and e-commerce for analyzing and visualizing large datasets to make informed business decisions.

Prior Art: Further research can be conducted in the field of data visualization, database management, and query optimization to explore existing technologies related to this innovation.

Frequently Updated Research: Stay updated on advancements in data visualization techniques, database management systems, and query optimization algorithms to enhance the capabilities of this technology.

Questions about the Technology: 1. How does this technology improve data analysis processes? 2. What are the key factors to consider when constructing dimension and measure subqueries for data visualization?

Original Abstract Submitted

a computing device receives user input specifying a first dimension data field and a second dimension data field. the device constructs a dimension subquery according to characteristics of the first dimension data field, the second dimension data field, a first object to which the first dimension data field belongs, and/or a second object to which the second dimension data field belongs, including determining a join type for combining (i) first data rows that include data values of the first dimension data field and (ii) second data rows that include data values of the second dimension data field. the device constructs the dimension subquery according to the determined join type, and executes the dimension subquery to retrieve first tuples. the device constructs measure subqueries and executes the measure subqueries to retrieve second tuples. the device forms extended tuples, and generates and displays the data visualization according to the extended tuples.