Most organizations have far more data than they can trust. Customer records duplicated across CRM, ERP, and eCommerce. Product data that differs between the catalog and the warehouse system. Financial figures that don't reconcile between reports. When data is inconsistent, incomplete, or ungoverned, every downstream process that depends on it — analytics, forecasting, compliance, customer experience — is built on an unstable foundation. Full On Consulting's data management consulting practice addresses all four disciplines required for trustworthy enterprise data: data governance, master data management, data quality, and data architecture — because a gap in any one of them limits the value of the others, and limits the value of every analytics or AI investment built on top.
4
Enterprise source systems consolidated into a single governed data warehouse in one engagement
$40M+
In documented client savings enabled by trusted data and disciplined technology strategy
20+
Years of enterprise data management and IT leadership experience per senior consultant
100%
Senior consultants — no junior staff on your data management engagement
Our Data Management Services
From Data Governance to a Governed, Trusted Data Foundation
Data Governance
Design and implement a data governance framework — ownership structures, policies, business glossary, data definitions, and data stewardship roles that ensure data is consistently defined, maintained, and trusted across the organization — and that business stakeholders own rather than delegate entirely to IT.
Master Data Management
MDM consulting and master data management program design — establishing a single authoritative source for customers, products, suppliers, and financial hierarchies. We implement the architecture, integration patterns, and golden record processes that eliminate the duplication and conflict that undermines reporting and operations.
Data Quality Services
Data profiling, cleansing, standardization, validation, and ongoing monitoring — building the processes and tooling that maintain data quality over time, not just at the point of a one-time cleanup before a major implementation. Quality maintained is more valuable than quality achieved once.
Data Architecture
Data architecture consulting covering data warehouse design, data lake architecture, lakehouse patterns, and metadata management frameworks — designing the structural foundation that your analytics, reporting, and AI initiatives depend on to be reliable, scalable, and governable at enterprise scale.
Data Strategy
Data strategy consulting that defines how your organization will manage, govern, and capitalize on its data as a strategic asset — delivering the investment roadmap that sequences governance, MDM, quality, and architecture initiatives against business priorities and available resources.
Data Migration & Integration
Secure, validated data migration and integration services — profiling source data before migration begins, remediating quality gaps, and executing migration with validation controls that ensure data integrity throughout. We do not move dirty data into new systems and call it done.
What Makes Us Different
Why Our Data Programs Produce Data You Can Actually Trust
Governance Before Architecture, Architecture Before Analytics
Data programs that build analytics infrastructure before governance is established consistently produce ungoverned data estates that are expensive to maintain and impossible to trust. We sequence engagements correctly — governance and quality first, then architecture, then analytics.
MDM as a Core Deliverable, Not a Future Phase
Master data management is consistently the most deferred element of data programs — complex, disruptive, and resisted by teams who have built workarounds. We scope MDM as a core deliverable from engagement initiation, not as phase three that never arrives.
Data Quality Profiled Before Remediated
The majority of data migration and analytics failures trace back to skipping the profiling and assessment phase. We profile all relevant data sources before making any remediation or architecture recommendations — so the solution is designed around the actual data, not assumptions about it.
Stewardship Roles That Persist After We Leave
Governance programs that depend on consultant involvement to function are not governance programs — they are consulting engagements with a sunset date. We design stewardship programs with clear business ownership and sustainable processes that operate independently after the engagement ends.
Featured Case Study
Data Warehouse: Establishing a Single Source of Truth Across Four Enterprise Systems
A distribution company had customer, order, product, and financial data fragmented across SAP, Salesforce, Magento, and a warehouse management system — with no consistent definitions and no authoritative source for any of them. Full On Consulting assessed, profiled, cleansed, and integrated all four systems into a governed data warehouse, creating the single source of truth the business had never had. The result was real-time reporting at the executive level for the first time, built on data the business could actually trust.
A broader IT transformation engagement demonstrated the same data discipline at enterprise scale — delivering $40M in documented savings while managing the data architecture, governance, and quality required to support a complex, multi-year technology program across 90+ global facilities.
Read the Full Case Study →4
Enterprise systems unified into a single governed data warehouse with real-time reporting
$40M+
In total documented savings enabled by trusted data and disciplined technology transformation
20+
Years of enterprise data management and IT leadership experience per senior consultant
Before You Engage
What to Ask a Data Management Consulting Firm
Do they profile data quality before designing the solution?
The majority of data migration and analytics failures trace back to skipping data profiling and quality assessment. Organizations that move directly from requirements to architecture or implementation routinely discover quality problems during execution — when they are most disruptive and most expensive to address. Ask whether the firm conducts a structured data profiling exercise before any architecture recommendations are made, and what happens when they discover quality gaps that were not anticipated in scope.
How do they address master data without deferring it to a later phase?
Master data management is the most commonly deferred element of enterprise data programs — complex, disruptive, and consistently deprioritized in favor of more visible deliverables. It is also the single change most likely to have the largest impact on data quality and analytics reliability. Ask how the firm approaches MDM scoping, whether it is included in the core engagement from initiation, and what methodology they use to establish golden records and de-duplicate across source systems without disrupting business operations.
How do they design governance that business stakeholders actually own?
IT can build the systems, but data governance is a business discipline. When business stakeholders don't participate in defining data standards, ownership structures, and stewardship roles, the resulting framework is either ignored by the business or unoperational in practice. Ask how the firm engages business stakeholders in governance design, how stewardship roles are established with real accountability, and what the governance operating model looks like once the consulting engagement ends.
How do they ensure data quality is maintained over time, not just at implementation?
A one-time data cleansing effort without ongoing quality processes degrades back to its original state within months — because the business processes and integrations that created the problems in the first place continue to operate. Ask what ongoing data quality monitoring, validation rules, and exception management processes are built as part of the engagement, and how data quality metrics are made visible to the stewardship teams who own the relevant data domains.
Make Your Data Trustworthy
Build the Data Foundation That Makes Analytics, Compliance, and AI Actually Work
Our senior data management consultants will assess your current data landscape, establish governance and MDM programs that business stakeholders own, and build the architecture and quality controls that make enterprise data genuinely reliable — so every analytics and AI investment built on top of it delivers real value.
Schedule a Free Data Management Consultation →WHY FULL ON CONSULTING
Senior Consultants Only
Every engagement is led and delivered by senior consultants — former CIOs, CTOs, and enterprise IT executives. You get the people you were sold, not a bait-and-switch to junior staff after the contract is signed.
$40M+ in Documented Savings
Our track record includes $40M+ in verified client savings, a $130M M&A integration across 90+ global facilities, and an end-user computing transformation for 18,000 employees. We deliver measurable outcomes — not just recommendations.
20+ Years of Enterprise Experience
Our consultants average 20+ years of enterprise IT experience across Fortune 500 and mid-market companies. We have run the same programs we are being asked to lead — across SAP, Oracle, Salesforce, ServiceNow, and large-scale transformations.
Strategy Through Execution
We do not hand you a strategy deck and walk away. Our teams stay engaged from initial assessment through go-live — accountable for outcomes, not just deliverables. If we recommend it, we are prepared to execute it.
Boutique Agility
As a boutique firm, we move faster, adapt to your priorities, and work with your team rather than around it. No bureaucracy, no layers of overhead — just focused, senior-led execution from day one.
A Partner, Not a Vendor
We build long-term relationships grounded in trust and integrity. Many of our clients have engaged us across multiple initiatives and refer us to peers — because we do what we say we will do, every time.