Target Brands, Inc.

Deepa Sarasamma

Payal Verma

Karthik Gorti

Saravanan Kandasamy

Prajakta Deshpande

Sudha Adarsh

The present disclosure relates generally to scoring queries based on accesses to databases. The scoring of a query can include generating a sub-score for each of one or more query metrics and generating an overall score for the query using at least some or all of the sub-scores. Additional information that is associated with the query may also be determined. User inputs can be received to modify the scoring of the queries, to modify the information presented in a user interface, and/or to modify the determination of some or all of the additional information.

Methods and systems for providing query metrics

The present application describes a database performance and usage footprint monitoring and analysis platform and related user application, which may provide insights across the whole of an enterprise's database inventory to increase visibility, accountability, and efficiency. The platform and related application may provide insight into enterprise database footprint and utilization, including displaying the data and associated metrics and analysis in a customizable interface. The platform may ingest and capture performance data and events to provide resource properties and cost analyses across enterprise groups. Future performance may be predicted by the platform, future data trends identified, and platform may provide usage prediction, perform root cause analysis to recommend action items, and provide alerts, among other functions. These improvements may reduce operational downtime, reactive events and efforts, and information gaps; enable informed business decisions; and make more efficient use of database resources.

Database usage footprint monitoring platform

Methods and systems for managing synchronization among databases are described. One method includes establishing a trigger within a transactional database storing a plurality of transaction records, the trigger having a trigger condition associated with storing a new transaction record in the transactional database. The method includes, in response to each occurrence of the trigger condition, storing a primary key of the new transaction record into a primary key table. The method also includes aggregating transaction record information into a transaction dataset, the transaction record information being from each of a plurality of transaction records that are associated with primary keys stored in the primary key table during a predetermined time period; and transmitting the transaction dataset to a remote analysis database as streaming data.

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Minneapolis, MN, United States of America

Deepa Sarasamma