PI Integrator and Cortana Intelligence for Facilities

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OperationalizeModelPrepare

Predictions as Future Data (to PI 2015)

Azure SQL Data Warehouse

INGESTPREPAREDATA SOURCES

On Premise

Energy Forecast for Production Facilities and Smart Buildings

Machine Learning

Power BI

ANALYZE PUBLISH CONSUME

Cortana

Web/LOB Dashboards

Azure SQL Data Warehouse

Data Scientist

Interact directly with data

Built-in to SQL Server

Data Developer/DBAManage data and

analytics together

Relational Data

Analytic Library

T-SQL Interface

Extensibility

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R Integration

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Microsoft Azure

Machine Learning Marketplace

New R scripts

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Intelligent analytics across realmsEmbed R, Python or Azure ML on-premises or cloud

Advanced Analytics & Power BI with PI System data | events and context

Architecture Notes

Scenario The OSIsoft office building in San

Leandro has hundreds of sensors

monitoring energy consumption. Our

goal is to find patterns of energy

usage and determine areas for

optimization.

Azure Cortana Intelligence Suite

Action

People

Automated Systems

Apps

Web

Mobile

Bots

Intelligence

Dashboards &

Visualizations

Cortana

Bot

Framework

Cognitive

Services

Power BI

Information

Management

Event Hubs

Data Catalog

Data Factory

Machine Learning

and Analytics

HDInsight

(Hadoop and

Spark)

Stream Analytics

Intelligence

Data Lake

Analytics

Machine

Learning

Big Data Stores

SQL Data

Warehouse

Data Lake Store

Data Sources

Apps

Sensors and devices

Data

Predictions as Future Data (to PI 2015)

Azure SQL Data Warehouse

INGESTPREPAREDATA SOURCES

On Premise

Energy Forecast for Smart Buildings

Machine Learning

Power BI

ANALYZE PUBLISH CONSUME

Cortana

Web/LOB Dashboards

Azure SQL Data Warehouse

Asset Framework (AF) data from PI System

12

Engine 1 Engine 100

PI Integrator for Cortana Intelligence

Publish PI AF data to Cortana Intelligence Stores

PI Integrator allows you to push “Analytics Ready” data directly to Cortana Intelligence

Azure Machine Learning Model

Understanding our Data

Weekly Average Energy Consumption shows Anomaly on Saturday. Further investigation reveals one of the HVAC scheduler was not set properly.

Understanding our Data

Weekly Average Energy Consumption shows we have are high use during morning 7 AM

Scoring the Predictive Model

Based on historical data, predictions of future energy use was pretty close to actual usage.