Abstract: Methods and apparatuses are described for system for identifying and mitigating high-risk database queries through ranked variance analysis. A server identifies database queries executed against databases in a production computing environment within a predetermined time period, each database query associated with execution plans and each execution plan having corresponding plan data elements. For each database query: the server generates execution variance data for the execution plans for a database query based upon the corresponding plan data elements, comprising: determining an execution time variance between the execution plans; and determining a buffer gets variance between the execution plans. The server ranks the database queries according to (i) the execution time variance, and (ii) the buffer gets variance.

Abstract: Methods and systems are described for data lineage identification and change impact prediction. Servers capture metadata that defines data objects associated with data sources. The servers determine direct relationships between data sources based upon the captured metadata. The servers identify indirect relationships between the data sources. The servers generate a data lineage across the data sources for the data objects. The servers extract unstructured text from database incident tickets and match the unstructured text to the metadata. The servers generate a multidimensional vector for the data objects based upon the data lineage and the unstructured text. The servers train a classification model using the vectors to predict a change impact score for each data object. The servers receive a request to change a data object. The servers determine a change impact score for the data object. When the score is below a threshold, the servers execute the change.

Abstract: Methods and apparatuses are described for system for identifying and mitigating high-risk database queries through ranked variance analysis. A server identifies database queries executed against databases in a production computing environment within a predetermined time period, each database query associated with execution plans and each execution plan having corresponding plan data elements. For each database query: the server generates execution variance data for the execution plans for a database query based upon the corresponding plan data elements, comprising: determining an execution time variance between the execution plans; and determining a buffer gets variance between the execution plans. The server ranks the database queries according to (i) the execution time variance, and (ii) the buffer gets variance.