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Company: BHP
Role: Business Analyst and Project Manager
Duration: January 2016 - December 2016
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BHP is a leading global resources company that extracts and processes minerals, oil, and gas, with a commitment to environmental sustainability.

As Master Data Manager at BHP's Maintenance Center of Excellence, I oversaw data integrity and quality, which are crucial for optimizing maintenance strategies and operations.

Responsibilities

  • Developed and implemented data management policies and procedures to ensure accuracy and accessibility.

  • Collaborated with IT and maintenance teams to align data governance with organizational goals.

  • Enhanced decision-making and maintenance practices, leading to significant cost reductions.

  • Led the data cleansing and enrichment efforts, ensuring high data quality and consistency across BHP's global maintenance operations.

  • Designed and implemented master data governance frameworks, improving data traceability, compliance, and alignment with business objectives.

  • Collaborated with cross-functional teams to integrate master data into predictive maintenance programs, enhancing equipment reliability and performance.

  • Managed vital stakeholder relationships across various departments, ensuring data initiatives were aligned with operational needs and strategic goals.

  • Provided training and guidance to teams, enhancing their understanding of data management best practices and fostering a data-driven culture within the organization.

  • Automated data validation processes, reducing manual intervention and increasing efficiency in data management tasks.

  • Developed key performance indicators (KPIs) and dashboards, enabling real-time data quality monitoring and impacting maintenance outcomes.

Technologies Utilized

  • SAP MDG (Master Data Governance): Managed and governed master data to ensure accuracy and consistency.

  • Oracle E-Business Suite: Used for enterprise resource planning (ERP) to streamline business processes.

  • SQL and PL/SQL: For querying databases and managing data.

  • Informatica: Employed for data integration and ETL (Extract, Transform, Load) processes.

  • IBM InfoSphere: For data governance and quality management.

  • Python: Used for automating data cleansing and validation tasks.

  • Microsoft Excel (Advanced): For data analysis and reporting.

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