Predictive Data Analytics in Oil & Gas
September 14th - Hilton Americas

About the Training Course

The Predictive Data Analytics in Oil & Gas is a 6-hour live and practical training delivered by Dr. Prashanth H Southekal (profile below), Managing Principal of DBP-Institute and Adjunct Professor of Data and Analytics at IE Business School (Spain). This training will equip participants with key Predictive Data Analytics concepts and skills.

Predictive Data Analytics is the use of business knowledge/hypothesis, data, and statistical models to identify the likelihood of future outcomes. The goal of Predictive data analytics is to go beyond knowing what has happened to provide the best assessment of what will happen in the future so as to better prepare and respond to future events.
 

Learning Objectives

In today's volatile, uncertain, complex, and ambiguous (VUCA) global market, Data and Analytics offer unlimited possibilities for enterprises to create a sustainable competitive advantage. Today Data and Analytics today are considered the next frontier for innovation and productivity in business. A Mckinsey report says data-driven organizations are 19 times more profitable with EBITDA increases between 15% to 25% than peers. According to Boston Consulting Group (BCG), the first 9 of the top 50 Innovative companies in the World are data firms.

In this backdrop, this training Predictive Data Analytics in Oil & Gas is designed for experienced professionals and builds on one’s technical and leadership competencies. This training has a strong focus on the application of data and insights for improved business performance. 

This training has 3 key learning objectives:

1. Understanding Predictive data analytics (including ML) and its key characteristics
2. Formulating Predictive data analytics models
3. Applying Predictive data analytics techniques, deriving insights, and communicating the insights derived to the business stakeholders.

Upon completion of the course, candidates will be positioned on the following core competencies:

1. Spot business opportunities and use-cases for predictive data analytics
2. Identifying capabilities and risks for implementing predictive data and analytics solutions
3. Improve the adoption of predictive data and analytics solutions in the organization

Course Contents

Session 1: Introduction to Data and Analytics (1 hour)

  • Introduction to Data and Analytics
  • 3 Types of Analytics + 2 types of Insights + MAD Framework
  • Data Science Techniques Taxonomy
  • Data Analytics Lifecycle
  • Business Data, Characteristics, and Types
  • 3 types of IT Systems
  • Data Lifecycle and Data Quality

Session 2: Predictive Data Analytics – Part 1 (2 hours)

  • Fundamentals of Predictive Data Analytics
  • Data Preparation for Predictive Data Analytics
  • Data Profiling for Predictive Data Analytics
  • Hypothesis Testing and P-value

Session 3: Formulating Predictive Data Analytics Models Session 3: Predictive Data Analytics – Part 2 (2 hours)

  • 4 Key Predictive Data Analytics Techniques
  • Hands-on exercise on Multiple Linear Regression (MLR)
  • Fundamentals of Machine Learning (ML)
  • 4 key characteristics of ML Models

Session 4: Ensemble ML Model + Supervised & Unsupervised ML Algorithms Session 4: Summary & Wrap-up (1 hour)

  • Remediating Bad Analytics
  • Data Visualization and Data Storytelling
  • Summary and Wrap-up
  • Predictive Data Analytics Case Studies – Oil/Gas, Mining, and Retail/CPG

Course Instructor 

Dr. Prashanth H Southekal
Dr. Prashanth H Southekal
DBP-Institute
Managing Principal
Dr. Prashanth H Southekal is the Managing Principal of DBP-Institute, a Data Analytics Consulting and Education company. He is also an Adjunct Professor of Data and Analytics at IE Business School (Spain). He brings over 25 years of Information Management experience from over 75 companies such as SAP, Shell, Apple, P&G, SAS, and GE. In addition, he has trained over 3,000 professionals the world over in Analytics, Data Products, and Enterprise Performance Management (EPM). He sits on the Advisory board of Evalueserve (Switzerland) and Grihasoft (India). Dr. Southekal is the author of 2 books - Data for Business Performance and Analytics Best Practices and writes regularly on Forbes.com. He is an Adjunct Professor of Data Analytics at IE Business School (Spain) where he received the teaching excellence award for the 2020-2021 academic year. CDO Magazine has included Dr. Southekal in the 2022 LIST OF LEADING ACADEMIC DATA LEADERS. Dr. Southekal holds a Ph.D. from ESC Lille (FR) and an MBA from Kellogg School of Management (US).