SAC Data Management Jobs Statistics and Analysis
NEW Statistics and Analysis Capabilities for Data Management Jobs
Q2.2022 QRC and wave 2022.07 bring brand new information to your tenants.
The Story can be accessed from the same place (Files > System > Common > SAC Content) as the other performance content that has been shipped to your tenants like the SAP Analytics Cloud Performance Statistics and Analysis and has the same look and feel.
But now we offer you the possibility to get an overview of jobs that have been scheduled in your tenant, with frequency, expiry date etc. to, for example, identify housekeeping potential, as well as the possibility to identify long runners and erroneous instances.
The Story contains two pages, Overview and Statistics. Both offer page filter for date, model ID, model name, creator, frequency and status of the job.
The starting page should give an overview of important KPIs like users that have scheduled jobs, the amount of schedules, the amount of instances as well as the amount of models that are used.
Below the KPIs we show the top 5 jobs or models by different runtime criteria to help you to identify problematic candidates.
The statistics page shows averages, maxima, median and error percentage of all schedules.
The following time series with jobs and their maximum duration shows the historic trend of jobs and their maximum duration, but can also be used to check whether a specific job or model was long running already all the time, or whether we face a specific pattern over time.
This is followed by a table that shows all job instances descending by job duration. It provides information of job log start time, the corresponding model, message type, frequency, result, creator and instance ID.
Last you can get details on the job instance from the table above in the following table by selecting one entry and filtering down. You will get the full information on creation date, expiry date, model ID, update method, etc.. This should help you to answer all questions be it for reasons of housekeeping or performance analysis.
We hope that this new feature is helpful for you. Stay tuned for news, there is a lot more to come!