Introduction to Data Analytics in Oil & Gas

• Importance of data-driven decision-making

• Overview of analytics applications across upstream, midstream, and downstream

• Role of analytics in safety, operations, and business efficiency

Types of Data in the Oil & Gas Industry

• Operational, geological, production, and financial data

• Structured vs. unstructured data sources

• Data lifecycle: collection, storage, and utilization

Fundamentals of Data Management

• Data integrity, quality, and governance

• Common challenges in industrial data systems

• Data cleaning and preparation basics

Exploratory Data Analysis (EDA)

• Understanding patterns and trends in datasets

• Using statistical summaries and data profiling

• Detecting outliers and anomalies

Introduction to Analytical Tools & Platforms

• Overview of Excel, Power BI, Tableau, and Python for analytics

• Selecting the right tool for your objectives

• Integration of data from multiple sources

Visualization Principles and Best Practices

• Importance of visual storytelling

• Choosing the right chart type for each dataset

• Avoiding clutter and misrepresentation in visuals

Power BI for Oil & Gas Applications

• Creating interactive dashboards

• Real-time data visualization for operations and KPIs

• Sharing insights across teams and management

Tableau for Advanced Visualization

• Building effective dashboards and reports

• Using filters, parameters, and calculated fields

• Case study: production and performance visualization

Predictive Analytics and Forecasting

• Basic concepts of machine learning in O&G

• Production forecasting, failure prediction, and optimization

• Data-driven maintenance planning

Data-Driven Decision-Making in Operations

Communicating Insights to Non-Technical Stakeholders

Future of Analytics in Oil & Gas