Trillium Discovery

Investigating data quality is like looking for a bunch of needles in a haystack. On top of that you need to involve people that can recognise and signify the needle.

For that you need a solution that is designed to help business users perform data quality assessments on large data volumes and that enables them to easily monitor data quality on a constant basis.

Automated out of the box data profiling capability.

  • Discover data structure; generate data statistics.

  • Analyse data content; identify personal data and data relationships.

  • Identify data dependencies, keys and joins.

Create and validate business rules.

  • Quantify and prioritise data quality issues.

  • Report on data quality metrics for accuracy, consistency and completeness.

  • Monitor quality thresholds and trends over time.

Key capabilities

  • Advanced profiling

    • Profiling of a wealth of basic statistics.

    • Plus advanced profiling options such as pattern analysis, soundex routines, meta-phones, natural key analysis.

    • Join analysis & dependency analysis.

    • Comparisons against defined data standards, and regulations with business rules.

  • Monitoring

    • Monitor data sources for specific events and errors.

    • Notify users when data values do not meet requirements, like unacceptable data values or incomplete fields.

    • Gives users the environment necessary to understand the true nature of their current data landscape and how data relates across systems.

  • Model control functions

    • Data architects and data modellers can rely on results from key integrity, natural key, join, and dependency analysis.

    • Physical data models can be produced through the effects of reverse engineering the data, to validate models and identify problem areas.

    • Venn diagrams can be used to identify outlier records and orphans.

 

Business UX/UI

The user interface is designed specifically for a business user. It is intuitive, easy to use, and allows for immediate drill down for further analysis, without hitting production systems.

Collaborative environment

Team members can log into a common repository, view the same data, and contribute to prioritising and determining appropriate actions to take for addressing anomalies, improvements, integration rules, and monitoring thresholds.

  • Comprehensive repository

    • The repository stores metadata created by reverse-engineering the data.

    • This metadata can be summarised, synthesised, drilled down into, and used to recreate original source record replicas.

    • Business rules and data standards can be developed within the repository to run systematically against production systems, complete with alert notifications.

  • Trillium Quality

    • Data can be cleansed and standardised directly using Trillium Quality.

    • Name and address cleansing, address validation, and recoding processes can be run using Trillium Quality.

    • Cleansed data is placed into new fields, never overwriting source data.

    • The cleansed files can be used immediately in other systems and business processes.

  • Integrates with Data360 Govern

    • Publish business rule metrics, quality dimensions, profile statistics, data lineage automatically to Data360 Govern.

    • Ensure that rules defined in your governance solution are delivered to Trillium Discovery for evaluation.

    • And that the resulting data quality metrics are made available to the governance tool to view quality results.