18060500. SYSTEM AND METHOD FOR FAST CONSTRAINT DISCOVERY ON RELATIONAL DATA simplified abstract (Microsoft Technology Licensing, LLC)

SYSTEM AND METHOD FOR FAST CONSTRAINT DISCOVERY ON RELATIONAL DATA

Organization Name

Microsoft Technology Licensing, LLC

Inventor(s)

Shaleen Deep of Madison WI (US)

Zifan Liu of Redmond WA (US)

Ashish Tiwari of Sammamish WA (US)

Anna Fariha of Redmond WA (US)

Avrilia Floratou of Sunnyvale CA (US)

Fotios Pasallidas of New York NY (US)

SYSTEM AND METHOD FOR FAST CONSTRAINT DISCOVERY ON RELATIONAL DATA - A simplified explanation of the abstract

This abstract first appeared for US patent application 18060500 titled 'SYSTEM AND METHOD FOR FAST CONSTRAINT DISCOVERY ON RELATIONAL DATA

Simplified Explanation

The patent application abstract describes techniques for improved constraint discovery on relational data, including constructing a lattice, performing a tree-based verification process, presenting DC information via a GUI, and generating candidate DCs for evaluation.

• Constructing a first layer of a lattice using a plurality of candidate denial constraints (DC) with a number of predicates.
• Performing a tree-based verification process on the first layer of the lattice to determine verified DCs and unverified DCs.
• Presenting DC information based on verified DCs via a graphical user interface.
• Generating a second layer of the lattice by combining unverified DCs for evaluation.

Potential Applications

The technology described in the patent application could be applied in database management systems, data analysis tools, and data quality assurance software.

Problems Solved

This technology helps in efficiently identifying and verifying denial constraints in relational data, improving data integrity and accuracy in databases.

Benefits

The benefits of this technology include enhanced data quality, improved constraint discovery processes, and streamlined data management operations.

Potential Commercial Applications

Potential commercial applications of this technology include database software development, data analytics platforms, and data governance solutions.

Possible Prior Art

One possible prior art for this technology could be existing constraint discovery algorithms in database management systems.

Unanswered Questions

How does this technology compare to existing constraint discovery methods in terms of efficiency and accuracy?

The article does not provide a direct comparison with existing methods, leaving the reader to wonder about the relative performance of this technology.

Are there any limitations or constraints in the implementation of this technology in real-world database systems?

The article does not address any potential limitations or challenges that may arise when implementing this technology in practical database environments.

Original Abstract Submitted

Example aspects include techniques for improved constraint discovery on relational data. These techniques may include constructing a first layer of a lattice using a first plurality of candidate denial constraints (DC) each having a first number of predicates. In addition, the techniques may include performing a tree-based verification process on the first layer of the lattice to determine one or more verified DCs confirmed to be DCs and a plurality of unverified DCs that are not confirmed to be DCs. Further, the techniques may include presenting, via a graphical user interface (GUI), DC information based on the one or more verified DC, and generating, for construction of a second layer of the lattice to be evaluated via the tree-based verification process, a second plurality of candidate DCs by combining the plurality of unverified DCs.