- Present their stories
- Network with peers and partners
- Hear about industry trends
- See the latest from OSIsoft
This year our regional seminars focus on industrial analytics. Analytics is promising to deliver new efficiencies within critical operations. Join us to gain insights into:
- The role of IoT, Edge, Cloud and Data Lakes within Industrial Analytics
- Different analytics approaches for critical operations
- Capabilities of the PI System to support your analytics
- Best practices for industrial analytics
- Analytics case studies
Analytics with the PI System
|Wednesday, April 24, 2019|
|8:00 AM - 9:00 AM|
|9:00 AM - 9:10 AM|
Welcome & Introduction
|9:10 AM - 9:40 AM|
Keynote: The PI System: Empowering People to do Successful Analytics (by RSM)
Today, analytics is promising to deliver new efficiencies within industrial operations. To maximize the value of industrial analytics, you need a strategic approach that addresses edge, enterprise and cloud tools for operations data while minimizing delays and failures from data inaccessibility, intensive data processing, and poor data quality. A successful industrial analytics strategy requires a data infrastructure approach that fosters trust and is optimized for enterprise-wide operational analytics.
This overview session introduces the latest trends within industrial analytics, highlights best practices for success, and shows how the OSIsoft PI System, edge, and cloud technology support different types of analytics for varying audiences – from engineers and managers to data scientists within IT and OT groups.
|9:40 AM - 10:10 AM|
|10:10 AM - 10:40 AM|
Your People Are the Key to Successful Analytics
To take advantage of operational data across the enterprise, you need to enable more people to consume the data: maintenance engineers, general managers, data scientists, and executives. From real-time access and exploration to operational reporting and analytics, users have different data, technology, and application needs. Managers need to know if targets are being achieved. Analysts need operational data integrated with business data. Data scientists need a cleaned operational data set to train machine learning algorithms for predictive capabilities. But raw operational data can be hard to understand, difficult to access in real time, and hard to consume without extensive processing, which leads to trust and quality issues. In this session, we’ll demonstrate how the capabilities of the PI System can be used to gather, structure, process and deliver the analytics needs of different audiences throughout the enterprise, ensuring that any person can access, understand, and trust the data.
|10:40 AM - 11:00 AM|
|11:00 AM - 11:30 AM|
Visual Data Analytics for Industrial Operations: Finding the best BI and PI System tools
Many of today’s visual analytics tools have been created for business and financial applications and users. Operations managers and engineers need analytics tools specifically designed for industrial operations, which can deliver real-time insights into process and equipment performance. In this session, we'll explore visualization approaches and discover the options best suited for your operations and business needs. We’ll demonstrate how industrial engineers can easily build operational views with PI Vision, use tools like PI DataLink for ad hoc data exploration in Excel, and leverage Power BI from Microsoft for reporting business and operations data together – all with minimal technical skills.
|11:30 AM - 12:00 PM|
Best Practices for Supporting Enterprise Analytics with IT Groups
Enterprise analytics involves data from a complex environment of systems, devices, networks, and departments that span operation technology (OT) and business IT groups. IT groups are rapidly investing in new edge, cloud and analytics technologies: new sensors, edge devices, Microsoft, AWS, and SAP analytics tools, and open source data lakes in the cloud. The result is an even more complex ecosystem of existing and new sources of data and technology that spans IT and OT, all while requiring utmost security.
This session focuses on the best practices for leveraging existing and new sources of data from both OT and IT investments. Learn how a data infrastructure approach can securely enable OT and IT to share and deliver analytics-ready data for both operational analytics and enterprise analytics. We’ll demonstrate how the PI System can enable enterprise agility to adopt new technologies and analytics methods that leverage edge, cloud, machine learning and artificial intelligence.
|12:00 PM - 12:30 PM|
Delivering high quality operational data for Advanced Analytics
Advanced analytics tools and platforms allow businesses to ask more from their operational data and obtain new insights. Yet 60% of Big Data projects fail. Simply ingesting raw operational data into your favorite business intelligence tool or data lake creates significant challenges and barriers to success. Problems with data access, data quality, data structure, and outputs from “black boxes” typically lead to unreliable conclusions or predictive algorithms that are never adopted.
In this session, we’ll cover the challenges of using new analytics tools with operational data; share how the PI System and the PI Integrators deliver analytics-ready data; show how subject matter experts in operations can easily curate data that can be understood by business and IT operations; and demonstrate how the 3rd party advanced analytics tools from Amazon, SAP, and Microsoft, can consume the data for trusted and quality analytics.
|12:30 PM - 1:30 PM|
Lunch & Networking
|1:30 PM - 2:15 PM|
Enabling Enterprise Analytics for IT Groups Needing Operations Data
Optimizing the value of your critical operations data means going beyond your operations teams. Sharing the operations data with your IT team enables business data to be combined with operations data for added insights, and advanced analytics projects to deliver insights not possible before. To gain value from these enterprise analytics projects it’s imperative these insights are transferred back into the operations environment and the tools used every data by operators and process engineers.
In this session we explore key challenges for supporting IT with advanced analytics projects and how the PI System is best utilized to streamline IT enterprise analytics projects, and importantly transfer insights back into operations to drive efficiencies.
|2:15 PM - 3:15 PM|
Using PI System and Data Science to Optimize Energy At OSIsoft HQ (Advanced Users)
Key to successful analytics projects is carry out essential pre-cursor steps prior to analytics. Identifying the business need, the data required and preparing the data prior to modeling. Having modelled the business problem iteratively learning from insights to implement and re-analyze the model to drive further optimization.
In this session we will show how OSIsoft has used its own PI System and analytics tools together to improve energy utilization in its Head Quarters. The audience will learn how OSIsoft data scientists formed and tackled a real world problem. The session will discuss the PI System in connection with open source technologies such as R and Python that can be used to extend the role of the PI System within Industrial operations. Expert knowledge of data science or the PI System is not required.
|3:15 PM - 4:00 PM|