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PI System Data integration with Azure Machine Learning Studio without intermediate database

Question asked by AibekNur on Dec 10, 2018
Latest reply on Dec 11, 2018 by Eugene Lee

Hello All,

We have the task to use PI system data as inputs for a machine learning studio.

One of the conditions of the project is not to use the intermediate database in any form. As a start point we consider to use PI Integrator for Business Analytics, Advanced edition.

The input module of machine learning studio supports this type of sources:


Web URL via HTTP

Get data that is hosted on a web URL that uses HTTP and that has been provided in the CSV, TSV, ARFF, or SvmLight formats

Hive Query

Get data from distributed storage in Hadoop. You specify the data you want by using the HiveQL language

Azure SQL Database

Get data from Azure SQL Database or from Azure SQL Data Warehouse

Azure Table

Get data that is stored in the Azure table service

Import from Azure Blob Storage

Get data that is stored in the Azure blob service

Data Feed Providers

Get data exposed as a feed in OData format

Import from On-Premises SQL Server Database

Get data from an on-premises SQL Server database using the Microsoft Data Management Gateway

Azure Cosmos DB

Get data stored in JSON format in Azure Cosmos DB.

On the other hand, PI Integrator for BA supports these types of target:

PI View

Text File

Microsoft SQL Server

Oracle Database

Apache Hive

Hadoop HDFS

Azure SQL Server

Azure SQL Data Warehouse

Azure Data Lake Store

Apache Kafka

Azure Event Hubs

Azure IoT Hub


As I see input source types of Azure Machine Learning Studio do not match with output target types of PI Integrator for BA.


Can you advise any approaches to achieve our goal with these constrain?


Thank you,