| Code | Date | Time | Duration | Location | Currency | Team of 10 Per Person | Team of 7 Per Person | Early Bird Fee Per Person | Normal Fee Per Person |
|---|---|---|---|---|---|---|---|---|---|
| DBMS26 | 09 May - 14 Jun 2026 | 9 PM Indian Time |
2 Hours Per Day
|
Zoom Online
|
USD
|
1150
|
1250
|
1500
|
2000
|
The Classes Will be Only On Saturday & Sunday Via Zoom Online for 6 Weeks.
Boost your team's skills and your budget! Enjoy group discounts for collaborative learning. Send an inquiry to info@peassociations.com.
Oil and Gas Data Management and Dashboarding Through SQL, NoSQL and Python
This course provides oil and gas professionals with essential knowledge and skills to manage data efficiently using SQL, NoSQL, and Python. It focuses on data integration, storage, and dashboarding to help drive informed decisions in real-time. Participants will learn how to handle structured and unstructured data, create interactive dashboards, and improve data-driven operations.
Description
The oil and gas industry generates a vast amount of data across various domains, from exploration to production. Effective management of this data is key to optimizing performance and making informed business decisions. This course is designed to teach participants the fundamentals of data management using SQL for structured data, NoSQL for unstructured data, and Python for data manipulation and visualization. By the end of the course, participants will be able to manage large datasets, develop dynamic dashboards, and extract actionable insights using powerful tools and techniques.
Demo Class
The increasing complexity of oil and gas operations demands efficient data management and real-time dashboarding solutions. This course introduces professionals to the use of SQL, NoSQL, and Python—industry-standard tools for handling, processing, and visualizing data. Participants will gain hands-on experience with real-world datasets, learning to implement best practices in data integration, storage, and dashboard development.
Understand the fundamentals of data management in the oil and gas sector.
Learn SQL and NoSQL for handling structured and unstructured data.
Master Python for data manipulation and dashboard creation.
Design and build dynamic dashboards for real-time decision-making.
Develop skills to streamline data workflows and improve operational efficiency.
This course employs a blend of theory, practical exercises, and case studies. Participants will engage in hands-on activities using actual oil and gas datasets to apply SQL, NoSQL, and Python tools in real-world scenarios. Interactive sessions and discussions will foster a deep understanding of the subject, while practical assignments will allow participants to immediately apply their knowledge.
Improved data handling capabilities for more effective decision-making.
Enhanced ability to manage large datasets across different stages of oil and gas operations.
Better operational efficiency through real-time dashboarding and data visualization.
Reduced risk and operational downtime through informed, data-driven decisions.
Develop critical data management and visualization skills.
Gain proficiency in SQL, NoSQL, and Python for oil and gas data applications.
Ability to manage and analyze both structured and unstructured data.
Build expertise in designing custom dashboards to support real-time business intelligence.
Enhance career prospects in the data-driven oil and gas industry.
Data analysts, engineers, and managers in the oil and gas industry.
Petroleum engineers and geoscientists looking to enhance their data management skills.
IT professionals involved in data storage, management, and integration for oil and gas.
Anyone seeking to improve their understanding of data management and dashboarding using SQL, NoSQL, and Python.
MODULE 1:
- Introduction Anaconda Python Package
- Introduction to Database and RDMS
- Introduction to Ms-SQL server environment
- Life cycle of oil and gas data.
- Recap of Python Programming Language
- Data Containers recap
- Pandas Recap
MODULE 2:
- Introduction to pyodbc connector
- Introduction to elements of database design
- Decision-making and code flow control
- Functions and Classes.
- Introduction to drivers and SQL connectivity.
- Reading data from SQL databases.
- SQL Data types.
- Design validation and null value handling.
MODULE 3 :
- Conditions in SQL queries
- Python data filtering vs. SQL data filtering
- Introduction to base map creation for oil fields using Python and SQL
- Introduction to SQL operators and other conditioning statements
- Adding data into SQL databases.
- Single data row insertion.
- Multiple data row insertion
- Excel-Python-SQL integration for bulk data loading.
- Introduction to elements of Database design.
- Displaying data in interactive dashboards
MODULE 4:
- Deleting and updating records in SQL databases.
- Export data from SQL to various data types.
- Database dashboarding.
- Creating a data monitoring solution for oil and gas production using SQL and Python
- Introduction to data views (table views)
- Backing up data from SQL tables.
- Basic Housekeeping in ms-sql server.
MODULE 5:
- Basic SQL report generation
- Creating a Database from Scratch
- Create multisource data application in Python.
- Create a Basic Production/Injection Event Recording System in SQL and Python
- Reservoir Management application using SQL and Python.
- Converting Operational data from SQL to Production Engineering and Monitoring Solutions.
MODULE 6:
- Introduction to object-relational databases.
- Introduction to PostgreSQL.
- Basic Operations and Custom datatypes in PostgreSQL
- Introduction to Document Databases.
- Introduction to MongoDB and NoSQL technology.
- Introduction to JSON and BSON files and Structures.
On successful completion of this training course, PEA Certificate will be awarded to the delegates
Mr. Nashat J. Omar With over 11 years of specialized experience in petroleum engineering, focus on production and flow assurance brings valuable expertise to the energy sector.
He possess a strong command of Python and C#, which empowers him to create efficient data management solutions and streamline workflows.
His collaborative nature and adaptability enable him to thrive in multidisciplinary settings, where he consistently contributes to success through innovative problem-solving.
He is dedicated to continuous learning and staying ahead of industry advancements, ensuring that he can enhance operational efficiency and guarantee robust flow assurance.
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