Write back to PI from the Integrator for Machine Learning. Currently we are writing back to Excel from Azure Machine Learning Service but would like to do this with less integrations.

As an Integrator user, I do not want to overwhelm the PI Data Archive when the Integrator reads data, either for an initial view backfilling operation or when I have multiple views running in real-time. I would like the Integrator to throttle Data Archive reads so as to not overwhelm the Data Archive or give me insight when I am making an expensive Data Archive call with the Integrator.

As an integrator for Business Analytics user I would like to be able to choose which directory in Azure data lake my view is published to so that is is easier to manage and analyse data once it is there.

Currently this is only possible through setting up additional targets, which is cumbersome.

Implement Testing methodology for Microsoft Patches
PI System owners need to ensure that their deployed systems both meet internal IT policies regarding recommended OS and other component recommended and critical patches, and that their PI applications are not adversely affected by these patches.

Consider a testing methodology similar to what PI AF employs which is currently to automatically monthly test all critical and recommended patches against the currently released application version.

Error message logs sometimes are not detailed enough to properly troubleshoot. The customer would like to increase logging available in order to get more insight as to what is going on.

One example - the PI Integrator for BA does not publish any message when there is a permissions/access issue to output data to a Kafka Topic.

As an Integrator user with multiple AF servers and databases organizing my data, I would like the ability to use a shape from a view pointed towards AF Server 1 to populate a new view for assets on AF Server 2 that match the shape. Currently, when I try the "Use a shape from a different view" option in the Integrator Designer, the asset shape clears as soon as I select a different server.

Support integration to non-Esri GIS systems such as GE Smallworld

When PI outputs multiple TAGS data to the SQL database, the output table needs only three fields (TAGS, time, value).

We have a large team that builds and manages our PI system. I need a way to tell users an asset is used by PI Integrator for publishing data so they know not to delete or edit that asset. For our PI Server, we use custom PI Point attributes to track what systems use a given PI tag. It would be nice if we could do the same with AF properties to track which AF elements are used by PI Integrator.

When you add a new attribute to a view, that column is placed at the end of the table. The column should be added in the correct placement like it would be if that attribute was added when the view was first created.

I am using PI Integrator to write data to file and then importing the file into a system PI Integrator does not natively support. Since I have to copy files over the network to get them to my other system, it would be nice if PI Integrator compressed the files once publishing is complete.

My users want to see the PI Point names in their views and not just the attribute name. I would like to be able to add the attribute configuration string as a column in my view.

Currently, it is not possible to set the file extension that is published to Azure Data Lake Store by the PI Integrator for Microsoft Azure. It is currently hardcoded to .txt format.

The end user should have the option to choose which file format (txt /csv/etc) that is to be eventually published to ADLS.

As a PI admin using the integrator with event frames for reporting, I would like the integrator to calculate summaries across event frames. For example, I'm interested in the average value of an attribute from the beginning of one phase to the end of the operation, where the phase and operation events are generated by a batch interface.

As a PI admin working with the integrator, I would like to be able to limit the amount of data returned for new elements added to existing views. This avoids the situation where a long-running view is unintentionally slowed when the integrator backfills data for the new element over the whole history of the view.

Add an Amazon Redshift publication target. In talking with some customers, some have decided to go with this data warehouse service. Right now some are trying to use the flat file target as an intermediate before feeding it to Amazon Redshift.

Provide a mechanism to filter out attributes that are not wanted on the PI Coresight ad-hoc trend. Customer Issue: All of the layer's fields (attributes) are included on the ad-hoc trend by default. This makes for a crowded trend that often includes unnecessary attribute data.Ê