Abstract: A system may port a data model into a strict schema system, translate the data model into a transformation rule definition, fit the transformation rule definition to a transform action, receive strict schema data, perform the transform action on the strict schema data based on the transformation rule definition to form rough data, and execute filtering and enriching operations on the rough data to form loose schema data.

Abstract: A computer-implemented method includes analyzing, by a processing unit, a relational database to discover a plurality of static relationships between a plurality of data fields captured in two or more tables. The processing unit can discover a plurality of entity relationships based on observing application-generated queries and results of accessing the relational database in response to one or more test triggers. The processing unit can build one or more relation graphs based on the static relationships and the entity relationships to link a plurality of nodes with one or more edges that define at least one relationship between the nodes. One or more class graphs are formed having a reduced number of edges than the one or more relation graphs. The processing unit can generate one or more result data graphs using the one or more class graphs as a graph database model of the relational database.

Abstract: A computer-implemented method includes analyzing, by a processing unit, a relational database to discover a plurality of static relationships between a plurality of data fields captured in two or more tables. The processing unit can discover a plurality of entity relationships based on observing application-generated queries and results of accessing the relational database in response to one or more test triggers. The processing unit can build one or more relation graphs based on the static relationships and the entity relationships to link a plurality of nodes with one or more edges that define at least one relationship between the nodes. One or more class graphs are formed having a reduced number of edges than the one or more relation graphs. The processing unit can generate one or more result data graphs using the one or more class graphs as a graph database model of the relational database.

Abstract: Embodiments include cognitive control of runtime resource monitoring scope. Aspects include obtaining historical data for each of a plurality of metrics for a computer system and calculating, based on the historical data, an anomaly relationship score for each of the plurality of metrics. Aspects also include calculating, based on the historical data, a sensitivity score for each of the plurality of metrics and determining a priority score for each of the plurality of metrics based upon a weighted combination of the anomaly relationship score and the priority score. Aspects further include receiving real-time data for each of the plurality of metrics and presenting a subset of the real-time data to a user, the subset created by selecting one or more of the plurality of metrics based on the priority score of each of the plurality of metrics.

Abstract: Embodiments include cognitive control of runtime resource monitoring scope. Aspects include obtaining historical data for each of a plurality of metrics for a computer system and calculating, based on the historical data, an anomaly relationship score for each of the plurality of metrics. Aspects also include calculating, based on the historical data, a sensitivity score for each of the plurality of metrics and determining a priority score for each of the plurality of metrics based upon a weighted combination of the anomaly relationship score and the priority score. Aspects further include receiving real-time data for each of the plurality of metrics and presenting a subset of the real-time data to a user, the subset created by selecting one or more of the plurality of metrics based on the priority score of each of the plurality of metrics.

Abstract: A computer-implanted method for creating a filtered digital entry includes generating, via a processor implementing a trace generation engine, a trace indicative of successful transactions and erroneous transactions. The processor instantiates a plurality of buffers in a buffer pool each configured to record a trace function boundary. The processor then analyzes each buffer in the buffer pool based on the trace function boundary to evaluate whether each function entry in the trace contains an erroneous transaction. If the processor determines that a function entry contains an erroneous transaction, the processor sets an output flag in a call stack map associated with that function. The processor then generates a filtered digital entry based on the call stack map. The filtered digital entry includes only erroneous transaction data from the trace.

Abstract: A computer-implanted method for creating a filtered digital entry includes generating, via a processor implementing a trace generation engine, a trace indicative of successful transactions and erroneous transactions. The processor instantiates a plurality of buffers in a buffer pool each configured to record a trace function boundary. The processor then analyzes each buffer in the buffer pool based on the trace function boundary to evaluate whether each function entry in the trace contains an erroneous transaction. If the processor determines that a function entry contains an erroneous transaction, the processor sets an output flag in a call stack map associated with that function. The processor then generates a filtered digital entry based on the call stack map. The filtered digital entry includes only erroneous transaction data from the trace.