International Business Machines Corporation

Holger Kache

Alan P Plante

Mary Ann Roth

Vijayshankar Raman

Charles Daniel Wolfson

Volker Gerhard Markl

Jacques Labrie

Michael John Morton

Veera Maddipati

Stephan Eberhard Ewen

Paulo R R Pereira

Rajiv S Kadayam

Robert Clarence Webber, Iii

Yannick Saillet

Guy Maring Lohman

Eser Kandogan

Tessa Ann Lau

Peter Martin Schwarz

Anshu Narendra Jain

Guenter Anton Sauter

Joshua W Hui

Torsten Bittner

Benjamin Honzal

Shivashankar Halan

Provided are a method, system, and article of manufacture for discovering transformations applied to a source table to generate a target table. Selection is made of a source table comprising a plurality of rows and a target table resulting from a transformation applied to the rows of the source table. A first pre-processing method is applied with respect to columns in the source and target tables to produce first category pre-processing output. The first category pre-processing output is used to determine first category transformation rules with respect to at least one source table column and at least one target table column. For each unpredicted target column in the target table not predicted by the determined first category transformation rules, a second pre-processing method is applied to columns in the source table and unpredicted target columns to produce second category pre-processing output. The second category pre-processing output is used to determine second category transformation rules with respect to at least one source table column and at least one target table column.

Discovering transformations applied to a source table to generate a target table

The mapping system and method comprises receiving a query identifying a source entity, the source entity being of a first entity-type; generating a plurality of candidate entities from an analysis of an entity-relationship graph in response to the query based on the source entity; and computing feature values for each candidate entity of the plurality of candidate entities by passing the source entity and the plurality of candidate entities to a type-specific entity recommender particular to the first entity-type.

Providing a visual and conversational experience in support of recommendations

Provided are a method, computer program product, and system for processing a data management request. User intent that defines properties of target data is determined. Policies and constraints for the data management request are determined. An abstract data management request that identifies source data, the target data, and the polices and constraints is created. A technology to use to process the data management request based on the user intent, policies, and constraints is determined.

Intent based automation of data management operations by a data management engine

According to one embodiment of the present invention, a computer system monitors information assets providing data for constructing a logical entity. The information assets are dependent upon each other for data and form a topology. The computer system receives an event message associated with an information asset. The event message includes information relating to one or more conditions of that information asset. The computer system processes the received event message to determine the presence of a change within the associated information asset that affects the topology. The change is determined based on the information relating to the one or more conditions within the received event message. The computer system further transmits a notification of the change to one or more entities in response to determining the presence of the change. Embodiments of the present invention further include a method and computer program product for monitoring information assets.

Monitoring information assets and information asset topologies

Methods, systems, and articles of manufacture for constructing and populating data marts with dimensional data models from a set of data repositories that contain factual and association information about a set of related assets are disclosed. An intermediate data warehouse is generated to process the facts and associations for each asset. Using the intermediate warehouse, one or more data marts are generated with fact tables, dimensions, and hierarchies to fully model the information available for each asset.

Dynamically building and populating data marts with data stored in repositories

A way for progressively refining a query execution plan during query execution in a federated data system is provided. Re-optimization constraints are placed in the query execution plan during query compilation. When a re-optimization constraint is violated during query execution, a model of the query execution plan is refined using a partially executed query to form a new query execution plan. The new query execution plan is compiled. The compiled new query execution plan is executed.

Progressive refinement of a federated query plan during query execution

A method for predictable query execution through early materialization is provided. The method deals with the problem of cardinality misestimation in query execution plans, by pre-executing sub-plans on a query execution plan that have questionable estimates and collecting statistics on the output of these sub-plans. If needed, the overall query execution plan is changed in light of these statistics, before optimizing and executing the remainder of the query.

Predictable query execution through early materialization

Growing community of inventors

San Jose, CA, United States of America

Holger Kache