|Presenter slides now available!||Presentations|
Date: October 2, 2014 from 8:30am to 1:30 p.m. CST
Location: Houston, TX - CityCentre Three, Suite 200 (Texas A&M University-Mays Business School facility)
Cost: There is no cost to attend this event.
SAS Day at Texas A&M
An event hosted by the Department of Statistics at Texas A&M University and led by Dr. Simon Sheather, Professor and Academic Director MS(Analytics) & MS(Statistics) online at Texas A&M University’s Department of Statistics.This event will highlight speakers from the SAS Institute, Inc. and industry experts that will discuss topics including analytics and data mining to make better business decisions. A panel of experts from a variety of industries will discuss how their companies are using big data and analytics, and how they are fostering a fact-based decision making culture in their companies. The number of participants is limited.
Participants will hear how big data and analytics are being used in companies in:
- Energy supply and distribution
- The benefits from using big data and analytics in your business
- Common obstacles to big data and analytics
- How companies build a culture of using big data for better decision making
- The types of data, software and statistical methods used in analytical decision making
Reserve your seat any time before October 2nd. Dress is business casual. Continental breakfast and light lunch will be available free of charge.
|Plenary Session - Armistead Sapp, SVP R&D: How the internet of things intersects with advance analytics and big data how that will change everything...||9:10am|
|Breakout Session I||10:00am|
|Breakout Session II||11:05am|
|Lunch with Keynote Speaker - Keith Holdaway||12:15pm|
Principal Solutions Architecht
SAS Global Oil & Gas Business Unit
Oil companies are being forced to explore in geologically complex and remote areas to exploit more unconventional hydrocarbon deposits. In areas with intrinsically poor data quality, problems are convoluted, and the cost associated with poor predictions (dry holes) rises. To counter these issues in E&P, companies need to integrate analytical methodologies that exploit the power of data-driven models and data mining techniques.
SAS and Osisoft will co-present Working with Saudi Aramco’s downstream operation data based on Osisoft’s flagship Pi System, learn how predictive analysis and asset surveillance modeling was used to proactively predict the collapse of an amine processing contactor and monitor production levels of their amine gas treating process contactor and down-comer.
Armistead W. Sapp
Executive Vice President and Chief Technology Officer
Armistead Sapp leads the software research and development divisions and the P-20 division at SAS Institute’s world headquarters in Cary, NC. He also leads the R&D division at SAS, charged with bringing the talents of SAS employees around the world together to produce the highest quality software for business intelligence, advanced analytics, customer intelligence, industry solutions, mobile applications and more.
Former Director of Innovation
Learn from a real world innovator who will provide insight into how a vision to improve the business, can be transformed into viable analytical solution that considers People, Process and Technology.
Senior Systems Engineer
SAS US Energy Division
Process manufacturing provides many challenges in managing performance, efficiency and safety. Examining critical assets of various configurations over a 14 to 18 months. SAS provided the ability to not only identify equipment with challenges but examine the detail operations of equipment and measure performance over time. This solution provides manufacturers with advanced analytics and more descriptive visuals to promote the health and safety of the asset, the process, and those individuals who are part of the community that our assets reside in.
The SAS Solution provides:
- Root Cause Analysis
- Performance Measures
- Historical Reference
Head of Organizational Transformation Services
SAS Global Business Consulting
As the value of business analytics is becoming a cornerstone of successful business strategies, organizations are striving to transform their environments to use analytics effectively across the enterprise. Producing business value from the investment in analytics requires more than just technology. Internal business and organizational change, guided by strategy, is needed to ensure adoption of analytics by business users. Enterprise Business Analytics centers of excellence can lead and guide the required changes. This presentation will analyze the technical and organizational challenges companies must address. It will also explore the different types of Business Analytics Centers of Excellence, and provide the SAS approach to establishing and evolving centers of excellence. The presentation will conclude with a review of a case study.
Predictive Analytics Lead
A panel discussion focusing on applied analytics in the oil and gas industry and moderated by Charlie Sanchez, Executive Lead-Energy Risk at SAS.