Assisted in the establishment of the Enterprise Data Governance Framework
CASE STUDY
Data Governance for an Oil & Gas Company
CLIENT:
Oil & Gas company
EMPLOYEES:
10,000+
INDUSTRIES:
Oil & Gas
SERVICES:
Data Governance Advisory
Data Governance Refinement
PLATFORMS:
Master Data Management
PowerBI
DATA DOMAINS:
Metadata
ABOUT:
This Oil and Gas company is one of the world’s largest publicly held international oil and gas companies. It carries out the refining of crude oil; produces, transports, trades and sells petroleum products; and manufactures lube base stocks and finished lubricants.
CHALLENGE:
The client, a prominent player in the Oil and Gas industry, faced significant challenges in managing their ever-growing data assets. These challenges included maintaining data accuracy, ensuring regulatory compliance, and enhancing operational efficiency. They recognized the need for a robust data governance strategy to address these issues and tasked us with the mission of transforming their data management practices.
The challenge was complex and exciting, as it required the team to create and articulate data policies, standards, and business rules while meticulously documenting them in a central repository. This included the establishment of an enterprise data governance framework to promote the strategic use of data across the entire enterprise. The primary aim was to establish and optimize the organization’s standard data governance practices, ultimately driving improved data-driven business performance and ensuring compliance.
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SOLUTION:
What we delivered:
D3Clarity’s data governance resources worked collaboratively alongside enterprise data governance leaders and data stewards to establish and execute an enterprise data governance framework.
In the pursuit of data governance excellence, several vital practices were implemented to address the challenges faced by organizations, particularly within the context of the oil and gas industry.
Firstly, identifying and defining of Critical Data Elements (CDEs) emerged as a crucial step. This process ensured that valuable resources were directed towards maintaining the accuracy and reliability of the most essential data elements. The precision achieved through CDE identification significantly enhanced data quality, ultimately supporting more informed and effective decision-making.
Secondly, adopting relevant industrial standards played a pivotal role in this journey. Embracing industry standards ensured compliance with regulations and demonstrated a steadfast commitment to best practices. This commitment fostered trust among customers, partners, and stakeholders while simultaneously mitigating compliance risks.
Thirdly, a vital aspect of enhancing data governance was the measurement of current data management maturity levels. Assessing data management maturity provided invaluable insights that empowered organizations to make informed decisions regarding resource allocation, infrastructure investments, and process improvements. Ultimately, this led to greater operational efficiency and cost savings.
Additionally, creating a data governance playbook played a central role in standardizing data management processes. By reducing errors and enhancing operational efficiency, the playbook ensured consistent practices across the organization, fostering a culture of data governance.
The creation and management of data domains also played a significant role in this journey. Data domains effectively categorized and governed data, improved data quality, compliance, and operational efficiency. The organized and cohesive management of data assets streamlined operations and decision-making.
Moreover, establishing a data catalog facilitated the discoverability and understanding of data assets. This reduced time spent searching for data accelerated decision-making and improved overall operational efficiency.
Forming dedicated data stewardship teams was essential for ensuring clear ownership and accountability for data quality, compliance, and issue resolution. These teams were critical in reducing data-related risks and maintaining data integrity.
Furthermore, the development of business data lineage diagrams empowered organizations to understand how changes in data impacted business processes. This, in turn, facilitated better decision-making, reduced risks, and optimized resource allocation.
The gathering of definitions for a business glossary provided a common language for employees, enhancing communication, fostering collaboration, and ensuring a shared understanding of key terms and concepts across departments.
Additionally, creating a data quality dashboard allowed organizations to monitor and address data quality issues proactively, reducing errors, operational disruptions, and ensuring data accuracy.
Lastly, defining and educating users on their roles and responsibilities within the data governance framework was crucial. This step enhanced security, compliance, and the overall data environment, promoting responsible data management and governance practices.
How we delivered:
Over the course of several months, D3Clarity assisted with the completion of numerous key deliverables, including:
- Identify and Define Critical Data Elements (CDE):
- The team conducted a comprehensive assessment of the client’s data landscape, identifying the most critical data elements pivotal to their operations. This involved close collaboration with subject matter experts and thorough data profiling.
- Identify and Adopt Relevant Industrial Standards:
- Through research, D3Clarity was able to recommend relevant industry standards tailored to the oil and gas sector, creating a custom catalog that outlined the details and benefits of each standard. These standards are currently being adopted into the client’s data governance framework.
- Define and Measure Current Data Management Maturity Level:
- A detailed assessment was performed on the client’s data management maturity using industry-standard maturity models. This evaluation provided a clear picture of their existing data practices, highlighting areas for improvement and investment.
- Creation of a Data Governance Playbook:
- Working closely with the client’s teams, a comprehensive data governance playbook was developed. This playbook outlined standardized processes, procedures, and best practices for data management and governance.
- Create and Manage Data Domains:
- The client and the D3Clarity team worked together to create and manage data domains, categorizing their data assets into logical groups, such as supply chain, operations, and business development. This allowed for clear data domain ownership to be established.
- Establishment of a Data Catalog:
- A robust data catalog solution was implemented utilizing the client’s Collibra tool, indexing and documenting all critical data assets. This catalog allowed users to easily discover and access data, significantly reducing the time spent searching for information.
- Form Data Stewardship Teams:
- Dedicated data stewardship teams were formed and assigned responsibility for data quality, compliance, and issue resolution within specific domains. These teams ensured clear accountability for data assets.
- Build Out Business Data Lineage:
- The D3Clarity team constructed detailed data lineage diagrams, illustrating how data flowed through the client’s various operations. This visual representation enabled the client to make informed decisions based on data impact analysis.
- Gather Definitions for a Business Glossary:
- All business units collaborated with D3Clarity to gather and document definitions for a comprehensive business glossary. This common language enhanced communication and alignment across departments.
- Creation of a Data Quality Dashboard:
- A real-time data quality dashboard was created, allowing the client to monitor and proactively address data quality issues. This dashboard became an integral tool for data quality management.
- Define and Educate Users on their Roles and Responsibilities:
- Clear roles and responsibilities were defined for data governance, security, and compliance. Customized training programs were designed and delivered to educate employees on their roles within the data governance framework.
RESULTS:
Deliverables:
- Organizational data lineage analysis
- Identify and document Critical Data Elements (CDE)
- Standardized existing data organization models, processes, and standards
- Define data governance roles and responsibilities
Business Value:
- Data lineage analysis is essential in tracking the flow and transformation of data across various systems, processes, and applications.
- Data quality improvement by ensuring critical data is accurate, complete, and reliable. Additionally, CDE's are the foundations for Informed decision-making enabling data-driven decisions that are more accurate and reliable.
- Consistent and standardized approach to data across the whole organization, improving efficiency and productivity through standardized data organization models and processes streamlined for data management tasks.
- Well-defined roles clarify who is responsible for various aspects of data management and governance, facilitating efficient and effective data governance practices.
In closing, the successful culmination of this data governance project represents a significant milestone in the organization’s journey toward effective data management and utilization. Over the course of this project, D3Clarity established a robust data governance process, defined clear roles and responsibilities, and enhanced the quality, security, and availability of the data assets. This remarkable milestone was achieved through diligent efforts and a clear strategic vision, demonstrating the profound impact of effective data governance.
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