Master Data Management implementation

Master Data Management (MDM) implementation is a system and a process for managing master data: the reference data used across all of the company’s systems — clients, counterparties, products, materials, departments, accounts. In a large company the same data lives in the CRM, ERP, billing and the warehouse, and everywhere differently: a client is duplicated, a product has three codes, a supplier has different details. MDM consolidates them into a single authoritative golden record, removes duplicates, sets quality rules and data owners and distributes the standard back to the systems. We set up the master-data model, matching and deduplication rules, change-approval processes (data governance), integration with your systems and quality control. Unlike PIM (see the “PIM implementation” service), which is responsible for product data, and DAM (see the “DAM implementation” service) — for media, MDM is broader: it is about all the key references at once, and PIM is essentially a special case of MDM for products. And it is not a data warehouse (DWH) or BI: a warehouse and BI collect data to compute reports from it, while MDM produces the standard itself — the trusted record those systems rely on; MDM does not replace them, it feeds them clean data. Importantly and honestly: MDM is a heavy and expensive project, and it is rarely justified unless your data is genuinely fragmented across systems. If you have one or two systems and the data is not duplicated — MDM is not needed, it is using a sledgehammer to crack a nut: it is cheaper to put order in the system itself, and we will say so directly. MDM is justified when there are many systems, the same entities are duplicated and diverge, and because of this errors happen in reports, deliveries and invoices. Also honestly: MDM is not just software — it is also governance and cross-team coordination. Half of the success is agreeing who in the company owns each reference and by what rules changes are made; no system will decide for you who is right in a dispute between departments — but MDM formalizes that agreement, automates approval through a workflow and greatly eases coordination; the final word stays with your teams. And about merging duplicates without illusions: identifying duplicates relies on probabilistic matching — we set up rules and thresholds, clear matches are merged automatically, ambiguous ones go to manual validation; there is no 100% automation here. Picture this: you create a client once — and they are the same in the CRM, billing and analytics, with no duplicates or discrepancies. The base price starts from 250,000 ₽; this is the floor for a project with one or two references. For large banking and retail rollouts with many systems and deep governance the budget is noticeably higher and estimated individually — it depends on the number of references, source systems and the depth of governance.

• The same data (clients, products) is duplicated and diverges between the CRM, ERP and warehouse.
• Reports do not add up — different systems show different figures for the same thing.
• It is unclear who is responsible for a reference and which record is the correct one.
• Data errors turn into failed deliveries, wrong invoices and losses.

• A master-data model: which references, attributes, the golden record
• Matching and deduplication rules (matching, merging duplicates)
• Data governance: data owners, rules and change approval
• Integration with source systems (CRM, ERP, billing, warehouse)
• Quality control: completeness checks, validation, monitoring
• Distribution of the standard data back to the systems (synchronization)
• A change log and record history (audit)
• Team training and procedures for maintaining the references

• One verified reference — a standard instead of out-of-sync copies
• Reports add up — all systems look at the same data
• Owners and rules are clear — order in changes
• Fewer errors in deliveries, invoices and analytics caused by bad data

• An audit of your data, systems and duplicates, and we design the model and governance
• We set up matching, quality rules, integration and synchronization
• We implement it, train the data owners, launch and support the start

• How is MDM different from PIM?

  PIM (see the “PIM implementation” service) is the management of product data: attributes, descriptions, for the catalog and sales channels. MDM is broader: it is about all the company’s key references at once — clients, suppliers, products, materials — and about consistency across all systems. PIM is essentially a special case of MDM for products. A small business more often starts with PIM; MDM is for large ones with many references and systems.

• Do we definitely need MDM?

  Probably not, if you have one or two systems and the data is not duplicated — then MDM is excessive, it is cheaper to put order in the system itself, and we will honestly talk you out of it. MDM is justified when there are many systems (CRM, ERP, billing, warehouse), the same clients and products are duplicated and diverge, and this causes real losses in reports and operations.

• Will MDM merge all duplicates by itself without errors?

  Fully automatically and without errors — no. Matching records (whether it is one client or two different ones) is often probabilistic: we set up rules and thresholds, clear matches are merged automatically, and doubtful ones go to manual review. For example, “John Smith” in two systems — one person or two different ones: if the tax ID or phone matches, we merge automatically; if only the name matches, we send it to manual review. And one more thing: MDM will not decide for you who in the company owns the data and by what rules it changes — that is an organizational agreement that the system formalizes and maintains but does not invent.