Increasing Metric Trust for Myriad360
Myriad360 is a trusted global systems integrator that partners with leading brands to deliver agile, innovative, and future-ready technology solutions. Through meticulous planning, resource optimization, and a dedicated, high-touch team, Myriad360 helps businesses strengthen their technology operations across cybersecurity, modern infrastructure and networking, cloud, and artificial intelligence. Their global expertise and consulting capabilities give clients strategic IT accelerators that support growth, resilience, and long-term performance.
Myriad360 manages a series of internal dashboards that centralize metrics for business operations across multiple departments and data sources. As the scale of their operations and data infrastructure grew, additions and changes to their metrics made it increasingly difficult to maintain an accurate, reliable view of their data. After conducting a data maturity assessment with Velir, Myriad360 set out to improve metric trust and make smarter, more effective data-driven decisions. Velir helped them build a roadmap and a dictionary of metrics to execute their vision and strengthen their data operations.
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Challenge
One of the most critical parts of data maturity is documentation. Businesses with mature data operations can effectively catalog and track their metrics to their sources, improving data reliability and veracity.
In Myriad360’s case, data reliability had become a bottleneck. With multiple data sources feeding different dashboards, and different dashboards being fed by multiple tables, the complexity of their operation and the pace of their growth made it difficult to accurately track and trust their most valuable metrics.
The client’s challenges included:
- Disparate Data Sources: Multiple sources feeding metrics with different definitions and measurements created confusion in Myriad360’s data operations.
- Lack of Technical Alignment: While Myriad360’s data lived in a central data warehouse, they needed better alignment across the technical formulas powering their dashboards.
- Queries lived in PowerBI: Velir discovered that transformation logic lived in Power BI instead of the transformation layer, requiring a lightweight refactoring of their queries.
- Falling Trust: Growth in data sources, inconsistencies in formulas, and missing definitions made it harder for Myriad360 teams to confidently use their data over time.
Approach
Our work to strengthen metric trust for Myriad360 grew out of a data maturity assessment designed to evaluate their data strategies, infrastructure, and capabilities. This audit, paired with further analysis of Myriad360’s dashboards, revealed the need to streamline reporting, define and align metrics, and catalog the lineage of available data.
We developed a plan to create a custom solution that combined metadata artifacts with exposure properties to maintain a continuously updated dictionary of metrics. The plan focused on materializing more granular data and automatically documenting every metric that powered Myriad360’s dashboards.
Our approach included:
- Enrich Myriad360’s transformation-layer metadata.
- Iterate through data columns to extract more granular information from column names and descriptions.
- Link data columns to their downstream dashboard and reporting dependencies.
- Produce a table that automatically tracks fields and downstream reports.
Solution
Our solution addressed a critical gap in the native documentation capabilities of Myriad360’s transformation layer: automated materialization of column-level lineage and metadata. We extended the metadata artifacts package to provide a queryable, granular view of individual columns, including their definitions, sources, and downstream dependencies in BI dashboards.
This created a living record of the metrics and definitions feeding Myriad360’s newly revamped dashboards. The solution also included a lightweight migration and refactoring effort to rebuild complex queries in the transformation layer instead of Power BI, ensuring the data needed to build metric trust was available in a consistent, governed location.
Results:
- Automated Column-Level Catalog: Created a queryable table that automatically documents column names, descriptions, and source models, eliminating the need for manual data dictionaries.
- Integrated Downstream Lineage: Enriched the catalog by identifying which BI dashboards and reports depend on each column.
- Added Operational Metadata: Incorporated a last_updated timestamp from model run data, giving teams immediate visibility into the freshness of the underlying data for each metric.
- Enabled Proactive Governance: Created a foundation for instant impact analysis before changing a column and future automated alerts on metric freshness.