International Business Machines Corporation

Dmitri Lerko

Clea Anne Zolotow

John Valentine Delaney

Francesco Mariani

David O'Grady

Maeve M O'Reilly

Teodora Sandra Buda

A mechanism is provided for determining a predicted performance of a database com. A first model for a database is determined using machine learning and training data based on monitoring the database operating in a production environment. A second model for the database is determined by combining the first model and a knee of curve formula for the database. The second model is stored for use in determining the predicted performance of the database in response to a database query.

Predicting performance of database queries

Computing systems, methods and collaboration tracking tools for predicting, tracking, and reporting the occurrence of unscheduled collaborations between two or more contributors to a project using computer systems equipped capabilities to transmit and/or receive location information of each individual contributor. An analytics module receiving the location information may use the location data to identify when two or more contributors to a project are in the same location together, and further predict whether the proximity of location and timing of the contributors crossing paths will predictably lead to an undocumented project-related collaboration determined as a function of location information, historical data and input collected. The collaboration tracking tools predict, report and/or record collaborations of project-related topics. Collaboration tracking tools confirm discussion of project-related topics, report to project managers for the purpose of updating the project managers and provide the project team with a copy of the recorded collaboration.

Collaboration tracking system

Growing community of inventors

Balbriggan, Ireland

Dmitri Lerko