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Context & Quality

Through our consulting process and implementation of data genealogy change detection and integrated master data management, we help our clients secure actionable information they can trust and fast!

When integrity, confidence and context data is high it is exponentially more valuable. The physical word and business environments change constantly and those changes need to reflect in the digital representation in a consistent manner to provide reliable, accurate and trustworthy information.

Optimate’s experience with large and smaller scale Plan Information Management Systems implementations, helps our customers to maintain their multiple stakeholder focussed view(s) of their data. Any change in sources in the physical world or in the master data references initiates a validation and update process providing accurate, in context and up to date information.

Practice Lead for Context & Quality

Tony Watkins

Tony’s professional experience was founded in the mining industry on project work where he spent more than 17 years working for many large Australian and global mining companies. During that time Tony gained experience that fostered the creation of an engineering consulting business providing a range of services; mainly in the area of Industrial Automation and Operations Data Systems. Over the last 10 years, Tony has implemented Operational Data Platforms in large scale systems, including BHP, Alinta Energy and Chevron’s Wheatstone, Gorgon and Tengiz operations. As Practice Lead at Optimate, he focusses on the most challenging aspect of any data foundation: data of adequate quality in an understandable context. His ability to address these issues in manageable parts with pragmatic and durable solutions is recognized throughout the industry.

The Context and Quality practice addresses the primary issues to make data usable – available and useful: users need to find it – so it needs to be in the Context(s) of all the consumers – and the health of the data needs to be managed to meets reporting and analysis requirements. In that capacity, the Context and Quality practice bridges the gap between the technology and the user community and makes data recognisable and understandable. This is essential to the lowering of the threshold to use operational data by a widening user base in decision support and decision automation, and ultimately accelerate and increase benefits realisation.

Areas of focus for the Context and Quality practice include:

  Developing the Organisational Capabilities to build and sustain OT data usage structures and frameworks in brownfield situations
   focused on incremental delivery and short timeframe wins.

  Definition and implementation of OT data hierarchies aligned to classic system data structures like asset hierarchies, chart of accounts,
   geographical locations etc or the more tailored solutions every business has. 

  Embedding of data and rules-driven automation – using tools and established practices – into the building and changes management to
   sustainably keep the OT data linked with the reference systems.

  Data quality and health management, including quality definition, fault detection and data quality management dashboards.