DM360 is the Agilus data management platform. It does two jobs: it assesses your data management maturity and AI readiness across seven pillars, aligned to the DAMA-DMBOK2 and DCAM international standards — and it delivers automated data quality: profiling, cleansing, matching, deduplication and ruleless anomaly detection. It is the instrument behind every Agilus consulting baseline, and its 21-question AI Readiness Scorecard is free.
Because DM360 scores against DAMA-DMBOK2 and DCAM rather than a private methodology, your board can verify the yardstick — and your progress is a number, not an assurance.
21 questions, about six minutes, an indicative maturity score with immediate feedback.
49 questions across all seven pillars, producing a detailed report (~30 pages): pillar scores, gap analysis and a sequenced improvement roadmap.
The assessment tells you where quality is the gap; DM360’s quality engine closes it:
Connects to your sources and quantifies the state of the data — completeness, duplicates, format violations, referential breaks — ranked by business impact against the six DAMA quality dimensions.
Names, addresses, identifiers and reference data corrected and standardised against defined rules, with every change logged and auditable.
Deterministic and machine-learning matching that finds the duplicates exact logic misses, with survivorship rules that assemble the golden record.
DM360’s ruleless data quality uses machine learning to learn what normal looks like in your data and automatically flag what deviates — no analyst-written validation rules required. Rule-based checking catches the errors you anticipated; ruleless catches the ones you didn’t.
Dashboards, thresholds and alerts that make quality an operational metric — watched weekly, trended monthly, escalated when it slips.
DM360 is the data management platform built by Agilus. It assesses data management maturity and AI readiness across seven pillars aligned to the DAMA-DMBOK2 and DCAM international standards, and automates data quality — profiling, cleansing, standardisation, matching, deduplication, ruleless anomaly detection and continuous monitoring. Its 21-question AI Readiness Scorecard is free.
A data maturity assessment measures how well an organisation manages its data as an asset — governance, quality, architecture, master data, metadata and more — against a defined maturity scale. Anchoring the assessment to recognised standards such as DAMA-DMBOK2 and DCAM makes the result objective and comparable over time.
Ruleless data quality is an approach, pioneered in Agilus’s DM360 platform, where machine learning learns the normal patterns in a data set and flags anomalies automatically — without analysts writing validation rules in advance. It complements rule-based validation by catching unanticipated errors.
Yes — 21 questions, about six minutes, no payment and no obligation. You receive an indicative maturity score and immediate feedback.