Certified Profisee Consultants

Looking for experienced Profisee consultants? We help organizations implement, optimize and scale Profisee MDM solutions.

Why choose Ammizing for Profisee Consulting services?

  • We have several years of experience implementing Profisee in different global companies
  • We consider the end-to-end data flow, not just Profisee
  • We are known to deliver high quality value in a fast pace to our customers
  • We have several consultants with Profisee Academy certification
  • We have competence from strategy to implementation level
  • We are used to work in multinational teams
  • We are a cross functional team with broad experience, not just in Master data management, but also in system architecture, enterprise architecture, project management and user experience design.

Are you planning to migrate from MDS to Profisee?

We offer experienced consultants who help companies successfully migrate from Microsoft Master Data Services (MDS) to Profisee. As MDS reaches end of life and lacks modern capabilities, migrating is essential to ensure scalability, data governance, and long-term support. Profisee provides a future-proof, flexible platform that strengthens data quality and enables digital transformation. Our experts guide you through a smooth, secure transition—minimizing risk while maximizing business value.

Profisee implementation guide

Implementing Profisee successfully is less about installing software and more about aligning data strategy, governance, and business ownership. After leading several Profisee implementations, we know that success depends on disciplined architecture, clear accountability and good cooperation between all involved teams.

Start with business outcomes

Before touching the platform, define:

  • What business problem are we solving?

  • Which domains (Customer, Product, Vendor, etc.) are in scope?

  • What KPIs will measure success?

Avoid the “platform-first” mistake. Profisee is powerful, but without defined outcomes, it becomes a data repository instead of a Master Data Management (MDM) solution

Establish Governance early

Implement governance processes before onboarding large data volumes. Technology enables governance — it does not replace it

Design the data model carefully

The data model is the foundation, ensure a solid multi-domain foundation supporting all business process aspects from start to avoid lock-in or remodelling later. Make sure to also consider integrations in and out of Profisee when defining the model. A poorly designed datamodel can cause a lot of problems if integration is not considered in the modeling phase.

Start integration work early

Do not wait with integration work to the end of the project. That imposes high risk of late delivery due to unexpected problems revealed during defining integration details. Decide which integration patterns to use, how data shall be mapped (on a detailed level attribute by attribute) and make sure to keep good working spirit between alll involved teams, no blame games! And remember, the sooner Profisee starts communicating with other systems, the sooner the business will see value of this investment.

Implement data quality iteratively

Do not attempt to fix all data issues on day one. Use Profiee’s match and merge capabilities pragmatically. Overly aggressive match rules can destroy trust in the system.

User adoption is critical

Especially if you are going for Centralized implementation style. Users will have to change their way of working, and not always to the better (in their opinion). Good master data benefits all users in the organisation, but it is the data stewards that have to do the heavy lifting when it comes to improving master data quality. They need to fully understand why they need to change their old way of working and see the bigger picture of data quality.

Depolyment and scaling

Do not deploy several models at once, start with a consolidating model and let the data stewards get used to work with the data in Profisee. When the data quality is high enough, connect outbound integrations one domain at the time. 

And, as a final advise, let the MDM tool be an MDM tool. It is possible to tailor Profisee to do a lot of things, especially connected to Azure functionapp, try to focus on MDM and move tool support for other business process to other systems.


At Ammizing we also have several years of experience with implementing Stibos system STEP and some experience with Riversand. Comparing these platforms is a good example to showcase why it is important to include experienced MDM consultants already in your MDM RFP process. Although all platforms will answer to your RFP request, you will get very different capabilities out from different tools. They will all support your business in a good way, but depending on your organisations needs, you may buy the wrong tool for solving your specific problems. 

Please contact us for an in depth analysis, but as a rule of thumb, if you are looking for true MDM capabilities and want a cost effective solution that is up an running quite fast, choose Profisee. If your requirements are more towards PIM and you need different taxonomies to be connected to your product domain, look more deeply into Stibo or possible Riversand.

Each platform has its pros and cons. The pros for Profisee is, according to us, the ease of implementation and true multidomain design, it is the ”data-workinghorse” in the background, while Stibo is stronger if you are looking for a PIM system for your retail channels.

Profisee vs other platforms

Profisee Data Governance & MDM Strategy

Master Data Management is not a tooling initiative — it is a business control mechanism. Profisee enables organizations to establish a trusted, governed foundation for critical data domains such as Customer, Product, Vendor, and Location. The strategy must align technology, governance, and operating model.

A Profisee-driven governance model establishes:

  • Clear data ownership at the business level

  • Defined stewardship responsibilities

  • Approval workflows for critical changes

  • Policy enforcement through validation and business rules

The objective is to shift from reactive data correction to proactive data control.

FAQ

We are happy to be consulted in any MDM matter, below are some common questions and answers:

What does a Profisee Consultant do?

A Profisee consultant designs, implements, and optimizes Master Data Management (MDM) solutions using the Profisee platform. This includes data modeling, governance design, match and merge configuration, integration architecture, workflow setup, and stewardship enablement.

You should hire a Profisee consultant when:

  • You are implementing Profisee for the first time

  • Your MDM program lacks adoption or governance

  • Data quality issues are affecting reporting or operations

  • You are expanding into new domains (Customer, Product, Vendor)

 

Experienced consultants reduce implementation risk and accelerate time-to-value.

This depends on scope, complexity of the domain, number of source systems and team set up. Our team is focused and well coordinated, so for us, a single-domain implementation of moderate complexity (e.g. supplier with a defined process) typically takes 4–6 months. A largly depending factor is organisation readyness and integration complexity ( number of integrations to depending systems). Multi-domain enterprise programs may run in phases over 6–18 months

Common challenges include:

  • Unclear data ownership

  • Overly complex data models

  • Weak match and survivorship rules

  • Poor integration design

  • Lack of executive sponsorship

 

An experienced Profisee architect mitigates these risks early.

Profisee enables role-based access and stewardship so you can decide exactly who has access to what information. Data quality is secured by approval flows where two (or more) pair of eyes can be set to check every create and update event. It also comes with a powerful capability for defining data quality and validation rules. The matching engine makes it possible to set threasholds for when records shall be considered duplicates and which data that shall be survived to a golden record. All changes, made by human or system, can be traced supportin compliance, regulatory requirements and internal accountability.

However, it can not be stressed enough, governance must be designed as an operating model — not just configured in the tool.