Modernization advisory for inherited data estates. The estate is larger than the roadmap assumes.
Reports, pipelines, jobs, models, SQL logic, notebooks, and manual workarounds have accumulated for years.
Data modernization advisory
Modernize inherited data estates without pretending they started clean.
I help data and technology leaders assess messy estates, design practical target architecture, provide fractional data/platform leadership, and guide modernization work across legacy BI, cloud platforms, Databricks, semantic layers, and AI-ready analytics foundations.
The starting point
Modernization rarely starts from a clean slate.
Most teams inherit platforms, reports, pipelines, ownership gaps, and business logic that evolved over years. Before choosing a target architecture, leaders need a clearer view of what exists, what still matters, what depends on what, and where risk is hiding.
Dependencies are partly known and partly folklore.
Teams know the critical outputs, but not always the upstream packages, stored procedures, jobs, semantic models, or ownership gaps behind them.
Platform decisions get made with weak evidence.
Without a clearer current-state view, modernization becomes a debate about whether to migrate, rebuild, retire, consolidate, or leave things alone.
AI-ready architecture depends on old reality.
Databricks, Fabric, Power BI, Snowflake, dbt, and AI initiatives all run into the same inherited complexity if the foundations stay unclear.
What leaders need to know
The work is useful when it changes what leaders can decide.
- What exists, and what still matters?
- What is still used, owned, trusted, or business-critical?
- What depends on what?
- What is risky, duplicated, stale, or poorly understood?
- What should be retired, migrated, rebuilt, consolidated, or left alone?
- What platform direction makes sense, and what should be funded first?
Where I fit
Senior architecture help before the delivery machine starts making the choices.
I work at the intersection of data platform architecture, BI modernization, analytics governance, semantic layers, executive decision support, and delivery leadership.
The work often starts with assessment. From there, it can move into roadmap, business case, target architecture, fractional leadership, partner oversight, or hands-on architecture support.
From assessment to architecture
Understanding the estate is only useful if it changes the modernization path.
Modernization does not start with choosing a platform. It starts with understanding what exists, what still matters, what depends on what, where business logic is hiding, and which parts of the estate should be retired, rebuilt, governed, or modernized.
I help turn that current-state complexity into a practical modernization path, then stay close enough to help architecture, governance, semantic foundations, partner scope, and delivery decisions hold together.
AI-ready foundations
AI exposes whether the data estate is ready.
- Governed metrics and trusted semantic layers
- Clearer ownership, source contracts, and data quality expectations
- Modernized BI, reporting, and platform architecture
- Known dependencies, confidence gaps, and legacy business logic
- Operating practices that make delivery, incidents, and change less improvised
Current state
Assessment
Roadmap
Business case
Execution support
What we do
Assessment, architecture, and leadership for modernization work.
Some clients need a focused assessment. Others need a fractional data leader, a Databricks or cloud architecture partner, delivery oversight, or hands-on help turning a roadmap into work that can actually ship.
Estate Review
Clarify what exists, what still matters, where risk is concentrated, and which assumptions need testing.
Inventory shape, dependency concerns, usage signals, ownership gaps, confidence limits, and modernization complexity.
Platform Architecture
Shape practical target-state architecture for BI, cloud data platforms, semantic layers, Databricks, governance, and AI-ready foundations.
Architecture options, integration patterns, semantic-layer direction, governance boundaries, and target-state tradeoffs.
Modernization Roadmap
Connect architecture direction to sequencing, funding, delivery capacity, partner scope, and executive decisions.
Retire, migrate, rebuild, consolidate, retain, or investigate paths translated into an executable modernization sequence.
Fractional Leadership
Provide fractional data and platform leadership, hands-on architecture support, partner oversight, and delivery discipline.
Executive advisory, delivery alignment, architecture review, partner/vendor coordination, backlog shaping, and operating-model support.
TangleMap
TangleMap is one accelerator inside the assessment process.
TangleMap supports Microsoft BI modernization assessments for legacy SQL Server, SSRS, SSIS, SSAS, SQL Agent, and related Power BI/Fabric paths. It helps produce inventory, dependency evidence, complexity signals, warnings, and confidence gaps.
It is strongest when the first problem is not migration execution, but getting enough evidence to make modernization planning less speculative.
Good at
- Inventory across legacy Microsoft BI assets
- Dependency evidence with confidence gaps
- Complexity signals for modernization planning
- Coverage warnings where access or metadata is incomplete
- Roadmap inputs for retire, migrate, rebuild, or investigate decisions
Useful when
- The Microsoft BI estate is too large for interviews and spreadsheets.
- Reports, jobs, packages, models, and SQL logic need a shared evidence base.
- Leaders need a practical read on migration complexity before committing budget.
- A partner team needs stronger discovery inputs before roadmap or delivery planning.
Engagements
Scope the help to the decision, not the other way around.
Work can be scoped tightly around a decision, structured as a project, or extended as fractional leadership when the organization needs senior continuity through delivery.
Assessment Sprint
A focused current-state review and modernization findings package for a specific estate, platform, or decision.
Defined-Scope Advisory
Roadmap, business case, architecture review, platform modernization, semantic-layer, or governance support with clear boundaries.
Fractional Data / Platform Lead
Ongoing senior advisory and hands-on architecture support for teams that need judgment, direction, partner oversight, and delivery discipline.
Partner Support
Subcontracted or co-sold assessment and architecture support for consulting firms with modernization opportunities.
Representative experience
Practical experience across strategy, architecture, and delivery.
This work is grounded in 18+ years across data strategy, enterprise architecture, BI modernization, Azure, Databricks, BigQuery, governed analytics, semantic layers, delivery leadership, and executive advisory.
- Modernization roadmaps and platform simplification
- Governed metrics, semantic foundations, and trusted reporting
- Compliance-sensitive analytics and data quality improvement
- Delivery leadership, consulting practice growth, and operating model design
- Legacy Microsoft BI discovery and modernization assessment IP through TangleMap
Telecom and media modernization
Led analytics modernization across a multi-brand telecom/media environment with roughly 800 analytics and reporting users and data related to millions of customers, including shared KPI definitions, reporting continuity, release process, and platform cost reduction work.
Compliance-sensitive reporting
Worked through trusted reporting and data quality improvement in an environment using data from a large partner ecosystem, where governance, ownership, and confidence mattered as much as the technical platform.
Reusable platform delivery
Designed reusable data platform, governance, and delivery accelerators across client environments, combining architecture standards, implementation patterns, and practical handoff models.
Point of view
Modern platforms fail when inherited complexity is treated as background noise.
A modern data platform is not just a new stack. It is a set of decisions about ownership, trust, semantics, governance, dependencies, delivery patterns, and years of accumulated reporting and pipeline logic. The first step is understanding the estate well enough to make those decisions deliberately.
Start here
Start with the decision or delivery gap that needs senior help.
A short conversation can usually tell whether the useful next step is an assessment, architecture review, fractional leadership role, or focused delivery support.