Implementation and data
Data models, taxonomy, quality, governance, migration and integration architecture.
A PIM implementation roadmap: phases, timelines and team
A PIM implementation roadmap with five phases, typical durations by company size, the core project team and the risks that most often delay go-live.
Implementation and dataProduct data modelling: families, attributes and variants
How to model product data in a PIM: families, attribute types, variant levels and axes, with worked examples and design rules for scalable catalogues.
Implementation and dataDesigning a product taxonomy and classification scheme
How to design a product taxonomy in a PIM: master classification, navigation trees and mappings to GS1 GPC, ETIM, ECLASS and Google product categories.
Implementation and dataProduct data quality: metrics, completeness and scoring
How to measure product data quality in a PIM: six dimensions, metric formulas for completeness, validity and timeliness, and a weighted scoring model.
Implementation and dataProduct data governance: roles, workflows and ownership
How to set up product data governance: owner, steward and custodian roles, a RACI matrix for product attributes, approval workflows and policy controls.
Implementation and dataMigrating product data into a new PIM
A step-by-step guide to PIM data migration: source inventory, profiling, mapping, cleansing, test loads, cut-over and validation, with typical durations.
Implementation and dataPIM integration architecture: ERP, commerce, DAM and APIs
How to design PIM integration architecture: system-of-record rules for ERP, DAM and commerce, and when to use batch, API, event-driven or MACH patterns.