Master Pimcore PIM/MDM Training, a practical and comprehensive course designed for developers, data managers, eCommerce professionals, product information specialists, IT professionals, and business teams who want to effectively manage product information and enterprise data using Pimcore.
Duration 3 days – 21 hrs.
Overview
The Pimcore PIM/MDM Training course provides participants with a practical understanding of how Pimcore can centralize, organize, enrich, and manage product information and master data across an organization. Participants will explore how a unified data platform can improve data consistency, governance, accessibility, and collaboration across business and digital channels.
Through practical exercises and real-world scenarios, learners will develop an understanding of Product Information Management (PIM) and Master Data Management (MDM) concepts and how they can be implemented using Pimcore. The course covers the principles needed to structure product and master data effectively while supporting organizations that manage large and complex datasets.
Participants will also gain insight into managing product-related information, digital assets, classifications, relationships, and data workflows. They will learn how properly structured and governed data can support eCommerce, digital commerce, product catalogs, websites, marketplaces, and other customer-facing channels.
A key focus of the training is developing a reliable approach to data quality and centralized information management. Participants will explore techniques for maintaining consistent product information, reducing duplicate or incomplete data, and establishing processes that improve the reliability of information throughout its lifecycle.
The course also introduces the role of Pimcore in integrating product and master data with other enterprise applications and digital systems. Participants will gain a broader understanding of how centralized data can support efficient business processes and provide a consistent source of information across multiple platforms.
By the end of the Pimcore PIM/MDM Training, participants will have a practical understanding of how to use Pimcore concepts and capabilities to organize product information, manage master data, improve data quality, support digital commerce, and establish a centralized approach to enterprise information management.
Learning Objectives
- Understand the fundamentals of Product Information Management (PIM) and Master Data Management (MDM).
- Gain proficiency in navigating the Pimcore platform and its core functionalities.
- Learn how to centralize and manage product data efficiently within Pimcore.
- Explore advanced features for data modeling, classification, and enrichment.
- Master the process of data import/export and synchronization with external systems.
- Discover best practices for data quality management and governance.
- Learn to create compelling product experiences across multiple channels.
- Understand the role of Pimcore in digital asset management and media enrichment.
Audience
- Business professionals involved in product management, marketing, and e-commerce
- IT professionals responsible for data management and system integration
- Developers interested in learning Pimcore for custom solutions
- Data Engineers
Pre- requisites
- Basic understanding of product management and data management concepts
- Familiarity with web technologies and databases is advantageous but not mandatory
- A general understanding of databases, data modeling, CMS, and eCommerce sites
Course Content
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Introduction
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Overview of Pimcore Features and Architecture
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Understanding Data Modeling under Pimcore
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Navigating the User Interface
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Customizing Attributes, Relationships, and Processes
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Integrating Data with Company Website
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Integrating Data with Marketing Materials
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Integrating Data with eCommerce Platform
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Creating Dynamic Templates
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Streamlining the Consumer Experience
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Exporting Data
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Improving Internal Workflows
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Collaborating with Marketing, Product Management Engineering and Business Analysts
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Troubleshooting
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Summary and Conclusion
