What is Data Optimizer?

Data Optimizer is an asset data verification, creation, and cleansing solution designed to give asset-intensive companies the mobility, accuracy, and control they need to properly develop, analyze, and structure the critical information supporting their maintenance, reliability, and production strategies.

The sustainability of any system, process, or program depends on the integrity of the data supporting it. Data Optimizer provides the visibility and speed needed to quickly analyze taxonomy, nomenclature, conventions, hierarchies, systems, conditions, completeness, relationships, and other vital components of your asset performance management data.


  • Identify duplicates, incompletes, and target other gaps in data quality
  • Configurable governance and controls satisfy any enterprise compliance requirements
  • Identify and target critical data for improvement strategies (i.e. criticality analysis, pm optimization, reliability analysis, etc.)
  • Enables rapid data build on new, acquired, or design assets
  • Mobile functionality facilitates accurate collection, completeness, and revision
  • Instant updates and progress performance
  • Controlled revisions through EAM / CMMS connections
  • Historical records are stored and accessible for future reference
  • Provides data requirements to contractors and engineers in a EAM / CMMS ready interface

Key Features

Data Quality Design

Smart, self-learning logic provides assurance that naming and structures are developed according to predetermined criteria.

Data Build Control and Progress

Define every detail of a data review or build, including field requirements, priority, and approving authority. Track progress at a cumulative level, by individual user, or during approvals; ensuring projects are on the right trajectory.

Component Classes

A library of built-in class structures provides users with a quick start in industry standard alignment. Flexibility allows users to create robust component classes specifically for their industry or operating context.

Data Metrics

Organizations can assess their data against industry standards or define site standards to continuously measure, benchmark, and improve data completeness and quality.