Description

A focused course, tailored for you

The Data Steward's Course on Consolidating Master Data When Legacy Systems Clash

Turn fragmented data silos into a single source of truth without endless spreadsheet wars and missed deadlines.

Stop rebuilding the same master data spreadsheet every Monday while leadership demands a single source of truth that never arrives.

$199 one-time

Tailored to your situation. Access within 24 hours. 30-day money-back.

Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.

Why this course

You spend every week juggling CSV exports, manual mappings, and ad-hoc queries because the core systems never speak the same language. The current process forces you to chase owners, reconcile mismatched identifiers, and re-run cleanses whenever a new report is requested, draining bandwidth and eroding confidence in the data.

Meanwhile, senior leadership asks for a unified customer view for the upcoming product launch, but the evidence you can produce lives in scattered SharePoint folders, outdated Excel workbooks, and undocumented scripts. If the data quality gaps surface during the launch review, the project stalls, budgets inflate, and your credibility takes a hit.

The audit team is already flagging inconsistent master data definitions, and the next compliance checkpoint will require a documented governance framework, approved change procedures, and a live data quality dashboard. Without a repeatable method, you risk repeated fire-drills and a costly remediation sprint.

What you walk away with

Create a living master data governance charter that gains executive sign-off.
Design and deploy a unified data model that integrates all critical source systems.
Automate daily data quality checks and surface alerts in a central dashboard.
Produce a complete evidence pack for the next compliance review in under a day.
Establish a repeatable onboarding workflow that reduces new data source integration time by 50%.

The 12 modules

Module 1. Assessing Current Master Data Landscape

Map all source systems, data owners, and existing governance artifacts.

Module 2. Defining a Unified Data Model

Create a single logical schema that resolves overlapping attributes.

Module 3. Establishing Governance Roles and RACI

Assign clear responsibilities for data creation, stewardship, and approval.

Module 4. Building the Data Quality Framework

Set rules, thresholds, and remediation workflows for key entities.

Module 5. Automating Data Ingestion Pipelines

Configure repeatable ETL jobs that enforce the unified model.

Module 6. Creating a Centralized Data Catalog

Publish metadata, lineage, and definitions in an accessible portal.

Module 7. Designing the Live Quality Dashboard

Visualize completeness, accuracy, and timeliness metrics for stakeholders.

Module 8. Documenting Change Management Procedures

Standardize request intake, impact analysis, and approval steps.

Module 9. Generating Audit-Ready Evidence Packs

Assemble required artifacts and reports for compliance checkpoints.

Module 10. Running a Pilot Integration Project

Apply the new method to a high-impact data source and measure results.

Module 11. Scaling Governance Across the Enterprise

Roll out the framework to additional domains with a rollout plan.

Module 12. Sustaining Continuous Improvement

Embed feedback loops and periodic reviews to keep data quality high.

How this addresses your situation

Specific modules that map to what you said you are dealing with.

Module 1 covers Assessing Current Master Data Landscape , exactly the inventory pain you face when trying to locate all source system definitions for the upcoming product launch.

Module 5 covers Automating Data Ingestion Pipelines , exactly the manual mapping nightmare you encounter each time a new CRM feed is added.

Module 9 covers Generating Audit-Ready Evidence Packs , exactly the last-minute scramble you endure when the compliance review deadline is announced.

What you get with this course

A master data governance charter template.
A unified data model worksheet with pre-filled example entities.
A RACI matrix for data stewardship roles.
A data quality rule catalog and scoring guide.
An ETL mapping checklist for source system integration.
A searchable data catalog metadata sheet.
A live data quality dashboard prototype.
A change request intake form with approval flow diagram.
An audit evidence pack checklist.
A pilot project plan workbook.
A rollout schedule template for enterprise scaling.
A continuous improvement scorecard.

What you will have in hand by Day 1, Week 1, Month 1

Day 1: tailored playbook in hand, governance charter template pre-populated for your environment, intake form ready for the next request.

Week 1: first version of the unified data model worksheet live and shared with the data architecture lead.

Month 1: live data quality dashboard running, audit evidence pack ready, and governance process embedded in weekly operations.

Before and after

Before

You maintain dozens of Excel files, scattered SharePoint folders, and handwritten notes to track master data definitions. Evidence lives in isolated spreadsheets, making audit requests a scramble and causing frequent rework whenever a new system is added. The team loses hours each week reconciling mismatches and manually updating dashboards.

After

All master data definitions reside in a single catalog, with an automated quality dashboard refreshed daily. A governance charter, RACI matrix, and change request process are documented and approved, and you can produce a complete audit evidence pack with one click. Leadership now sees a reliable, unified view of customers and can plan initiatives confidently.

What happens if you do not address this

If you ignore this, the next quarterly audit will flag incomplete master data evidence, forcing a costly remediation sprint. The product launch will be delayed as senior leaders lose confidence in the data foundation. Your performance review may reflect repeated data quality failures.

Who it is for

A data steward who spends most of the day aligning source system extracts, maintaining data dictionaries, and fielding urgent requests from business analysts. They operate in a matrixed environment, balancing technical constraints with business priorities, and need a practical, step-by-step method to institutionalize master data processes.

Who this is NOT for. This is not for someone who needs a basic introduction to what master data is.

How it arrives

Within 24 hours of purchase your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it. The playbook is hand-built around your specific situation, not LLM-generated boilerplate.

Time investment. 6 hours of focused work spread over a week and the course saves an estimated 40-60 hours of manual data reconciliation.

Why $199 is the right number

Compared with hiring a half-day consultant for $3,000, buying a generic compliance course for $1,200, or spending 60+ hours building a method from scratch, this $199 course gives you a ready-to-use framework and artefacts that deliver ROI within weeks.

FAQ

Do I need prior experience with data modeling tools?

No, the course walks you through building the model using familiar spreadsheet techniques before introducing automation.

Will the templates work with our existing ERP and CRM systems?

Yes, the artefacts are technology-agnostic and include mapping guides for common enterprise platforms.

How much time will I need each week to complete the course?

Allocate about 3 hours per week and you’ll finish the 12 modules within a month.

Is there any support if I get stuck on a specific integration step?

A private discussion board is available for peer feedback and instructor clarification throughout the program.

30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.