Eight evidence-backed assessment modules spanning trusted data foundations, AI controls, cost optimization, and modernization. Run each independently or combine them into one coordinated customer program.
The platform helps leadership understand current state, future state, remediation priorities, expected outcomes, assumptions, timeline, and investment considerations. Each module translates approved metadata, governance evidence, and business context into an executive-ready view of what to fix first and why it matters.
Evaluates governance, security, metadata, quality, lineage, architecture, and business readiness before the organization scales AI use cases.
Core question: Is the data estate ready to support trusted enterprise AI, copilots, and agentic workflows?
Evaluates the maturity and effectiveness of the organization's data governance operating model. The assessment examines ownership, metadata, data classification, access governance, lineage, data quality, trusted consumption, and governance processes to identify practical remediation priorities and improvement opportunities.
Core question: Are critical data assets owned, classified, controlled, traceable, and governed for trusted use?
Identifies workload, storage, BI, pipeline, cloud, tagging, ownership, and review-cadence opportunities to reduce waste and improve financial discipline.
Core question: Where is spend concentrated, what is driving it, and which actions can reduce cost without compromising outcomes?
Reviews AI systems, agents, approvals, scoped access, sensitive-data controls, lifecycle risk, monitoring, and operating accountability.
Core question: Are AI systems properly inventoried, approved, restricted, monitored, and governed throughout their lifecycle?
Establishes a validated current-state architecture baseline, evaluates target-state options, defines a conceptual Business Information Model, and produces a modernization roadmap and investment assumptions.
Core question: What current-state constraints matter, and what target architecture and roadmap should leadership approve?
Evaluates critical-data quality controls, data contracts, freshness, completeness, incidents, pipeline monitoring, SLA/SLO coverage, and root-cause capabilities.
Core question: Are critical data products fit for use, and can failures be detected and resolved before business impact?
Classifies source assets and workloads, analyzes dependencies and complexity, and defines target foundations, effort, waves, coexistence, cutover, validation, and decommissioning.
Core question: What should move, how difficult will it be, and how should migration, cutover, and decommissioning be sequenced?
Rationalizes Qlik applications and reporting assets, evaluates compatibility and dependencies, sizes delivery effort, and defines the Power BI target blueprint and migration waves.
Core question: Which Qlik assets should be retired, consolidated, migrated, or rebuilt, and in what sequence?
When the customer objective spans multiple domains, select two or more modules and compose a coordinated program. Completed assessments contribute evidence-backed findings; modules not yet assessed remain clearly labeled as planned sequencing guidance.
Align the assessment mix to the customer objective, scope, and business decisions.
Identify prerequisites, handoffs, decision gates, and downstream effects across modules.
Organize foundation, control, optimization, and modernization work into an integrated roadmap.
Produce a combined customer web report, PDF, editable PowerPoint, priorities, and roadmap.
The assessment starts with a metadata export ZIP and becomes stronger when customers add business context, policy evidence, operating model details, and domain priorities. Customers do not need to provide raw production data, secrets, credentials, or direct system access.
| Input | Status | How it improves the output |
|---|---|---|
| Platform metadata export ZIP | Required | Supports validation, scorecards, evidence-backed findings, and normalized metadata review. |
| Industry selection | Required | Adjusts weighting, critical-data priorities, policy expectations, and report language. |
| Business priorities and key initiatives | Recommended | Connects findings to business outcomes, urgency, and implementation sequencing. |
| Remediation effort and ownership context | Recommended | Improves priority sorting from low-effort, high-impact quick wins through high-effort, high-impact strategic work. |
| Governance policies, standards, and process documents | Recommended | Clarifies expected controls, decision rights, stewardship, approval paths, and operating cadence. |
| Critical data domains and data product inventory | Recommended | Improves materiality scoring and keeps recommendations focused on the most important data assets. |
| Access review, lineage, quality, and reporting certification evidence | Recommended when available | Improves confidence in governance maturity, trusted consumption paths, and control-gap prioritization. |
Executive summary, score, headline risks, customer context, and the business reason to act.
Assessment scope, evidence used, methodology, scoring lens, and interpretation guidance.
Scorecards, maturity heatmaps, gaps, risk register, evidence-backed observations, and control themes.
Target operating model, expected control improvements, governance behaviors, and trusted consumption outcomes.
30/90/180-day roadmap organized around sequencing, dependencies, owners, and delivery confidence.
Expected benefits, implementation assumptions, investment considerations, and what must be true to realize value.
| Priority band | What it means | Typical action |
|---|---|---|
| Low effort, high impact | Quick wins that reduce risk, improve evidence quality, or unlock better governance with limited coordination. | Start immediately. |
| Moderate effort, high impact | Important improvements that need planning, ownership, and cross-functional coordination. | Schedule in the first 90 days. |
| High effort, high impact | Strategic work tied to operating model, tooling, architecture, accountability, or process transformation. | Fund and manage as a program. |
Understand the business risk, expected outcomes, and investment priorities without needing technical translation.
Align on ownership, metadata, quality, lineage, trusted reporting, and operating model improvements.
See where sensitive data, access governance, approvals, and monitoring controls need remediation.
Connect usage patterns, waste reduction, accountability, and modernization investments to measurable value.