In an exceedingly data driven industry such as Exploration & Production (E&P), incomplete, inconsistent or invalid data could have serious business implications. For example, the key business decisions, such as whether to drill now or wait till next formation, whether to participate in a bid etc. are based on geological and geophysical data.
Accurate, consistent and complete data is a crucial component of E&P organizations’ operational efficiency. This data goes through several manipulations and processing before it could be analyzed by domain experts. Maintaining data quality at each stage of the process requires a systematic approach to data quality.
We have extensive experience in E&P organizations data quality management. We have in-house Center of Excellence (CoE) for Data Quality Management (DQM) capability and foster Research and Development (R&D) initiatives to provide industry best solutions for E&P organizations’ data quality problems.
Through the years of DQM practice, we have developed delivery accelerators – DQM reusable components such as templates, tools, catalogues etc. that help us provide quick turnaround to E&P organizations’ data quality needs.
Our service offerings span across following areas:
- Data Quality Consulting Services
- Data Quality Assessment Services
- Data Quality Improvement Services
- Additional Support Services include:
- Interfaces, Adapters and Plug-ins
- Enterprise Reporting Tool Integration
- Change Management
Key Business Benefits
- Data analysis time reduction from hours to minutes and reduced time required to back track the issues by 90 percent
- 60 percent reduction in time for Geological and Geophysical (G&G) data cleansing, thereby improving data quality
- Automation of the data quality maintenance processes to ensure the data quality requirements are met with minimal supervision. The automation tools reduce data load time by 40 percent.
- Robust generic framework to implement the data quality management solution in multiple countries with very minimal customization
- Improve the quality and integrity of Enterprise Resource Planning (ERP) master data using a combination of preventative and detective controls
- Availability of unstructured data, such as digitized, indexed are made available to business along with structured data
- Data viewers to automate reporting and loading missing data