Come to this workshop and learn how to get more insight and knowledge from the familiar datasets in your PI System. As a PI System professional you have worked with the PI System and know how it works. Use the concepts in this workshop to extract more value and become the super star who creates knowledge from data through good visualization and analytics. Understanding of the basics of PI System tools is a prerequisite for this workshop. No prior knowledge of data science concepts are required.

Who should attend? Data Scientist and Beginner

This session explores the partnership between Esri’s powerful ArcGIS mapping application and real-time infrastructure offered by the PI System. Discover how easy it is to connect your PI System with your Esri ArcGIS platform to provide critical metrics and spatial awareness to your enterprise. Take advantage of newly features release to perform both real-time GIS analysis and time-enabled feature layers to see perform a historical playback of event interactions.

This workshop will introduce you to leveraging two enterprise systems - OSIsoft PI System (time) and Esri ArcGIS (space) - with product level integration with a few clicks. We will use the Oil & Gas industry as an example and will demonstrate as how easy it is to bring GIS maps to life by streaming operational data (SCADA, Metering etc) from assets, pipeline segments, and mobile assets and also perform historical playback of important events for situational awareness and emergency response analysis. Lastly, we will create an interactive online version of Esri’s Operations Dashboard and dashboard using WebApp Builder.

This workshop is intended for PI users desiring to learn a new tool for agile, ad hoc, process data analysis. We will be using Microsoft Power BI to analyze PI Views published by the PI Integrator for Business Analytics. The hands-on examples help students appreciate of how multidimensional data analysis can help gain command of large datasets through filtering and grouping of process measurements. Theworkshop will cover other relevant features like how to expand the scope of your analysis by including data from other sources, applying statistical evaluations of your data and by defining measures for benchmarking and advanced analysis. Visualizations include a brief overview of R and Python possibilities. If you’ve become frustrated trying to manage today’s mega-spreadsheet, this workshop might have the answer for you.

Are you new to the PI System and find yourself in an administrator role? Are you interested in beefing up your troubleshooting skills and learning some tips for administering the PI System? This workshop will walk you through troubleshooting some common misconfigurations based on the real-world experiences of OSIsoft Product Support Engineers. You'll also learn time saving tips and other ways to make your life as a PI System Administrator easier. This workshop is meant for new administrators, but could provide a valuable refresher for seasoned administrators.

Have you already heard about the power of Asset Framework (AF), and are eager to implement or expand an existing AF structure in your organization, but… not sure where to start from? Are you wondering if there are any timesaving tips for deploying scalable and consistent AF structures? In this session, you will build a simple, yet scalable, AF structure from the ground-up using proven recommendations and guidelines. Specifically, you’ll see how to build templates that leverage your current tag naming conventions (or lack thereof) to achieve standardization across sites. Through planning out your AF hierarchy, and following best practices such as using Template Inheritance, setting Units of Measurement explicitly, and utilizing Categories, you will be able to quickly create a consistent and repeatable AF model to help your users build meaningful displays and reports with ease.

AF Analytics offers distinctive advantages when preparing time-series data for advanced analytics. It can play and essential role in testing, evaluating and operationalizing developed models. In addition, the openness of the PI System supports several different data access methods, meeting the needs of any data engineer or scientist.

This course will explore several examples demonstrating how AF Analytics can serve as an advanced analytics workbench. For comparison, examples will employ different data access methods, PI Integrator for Business Analytics, PI SQL Client and the PI Web API. Predictive models using PI Data will be developed in Python, a readily available open source application that is widely used for advanced analytics.

This will not be a developer's class, but rather a workshop for those wanting to gain an improved understanding of how to make statistically derive models relevant to Operations. No prior knowledge of Python is required but a basic understanding of PI AF is helpful.