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What You'll Learn
Businesses that develop their own systems for Master Data Management (MDM) often come to a turning point where the costs to maintain, scale, and integrate outweigh the benefits. With cloud-native SaaS MDM platforms like Informatica Customer 360, Supplier 360 growing in popularity, enterprises are able to modernize their master data capabilities as well as their data governance processes; they also help to provide new insights with advanced AI/ML-driven capabilities. This guide will walk you through best steps to migrate from custom MDM to Informatica SaaS MDM.
Why Migrate to Informatica SaaS MDM
While custom-built MDM solutions may address short-term needs, your data environment needs will create long-term challenges such as brittle integrations, excessive manual process monitoring, lack of scalability, and an inability to maintain a mature level of compliance and security. Informatica MDM SaaS is built on a cloud-native and microservices-based architecture that offers pre-built domain model applications like Customer 360, Supplier 360, Product 360, and Reference 360. Informatica provides standardized ingestion with connectors, assimilates data quality and governance, upgrades automatically, and provides security at a high level. If you are seeking modernization at the data platform level, Informatica SaaS MDM becomes the natural extension of what your organization has deployed.
You must consider cloud SaaS MDM platforms like Informatica to:
- Achieve elastic scalability with decreased infrastructure overhead.
- Utilize integrated capabilities in AI-driven data quality, and data matching.
- Utilize pre-built domain models (Customer 360 SaaS, Product 360 SaaS, Supplier 360 SaaS).
Core Challenges in Migrating Custom MDM Systems
Moving from a highly customized or legacy on-prem MDM system presents several challenges such as:
- Complex, customized data models and workflows that must be accurately mapped to the SaaS schema.
- Migration of master keys and unique identifiers with referential integrity.
- Rebuilding or refactoring rules for data quality, matching, and survivorship using the tools available in Informatica.
- Achieving zero or near-zero downtime so as not to impact operations.
- Migrating metadata such as user roles, security, audit logs and so forth.
A well-organized data migration plan reduces these risks in stepwise phases. Lumendata has expertise in delivering the same.
Key Considerations Before Migration
1. Alignment with Business Strategy
You should migrate in the context of your business strategies, for example to upgrade customer experience, faster onboarding or meeting regulatory requirements by moving to the cloud. Engage with business stakeholders early to understand their governance rules, workflows, and downstream reporting implications in the new environment.
2. Data Scope and Complexity
Articulate the scope of work carefully: is the migration limited to one domain (e.g., Customer 360), or multiple domains (Customer, Product, Supplier)? Migration becomes increasingly complex with each domain, and every integration.
3. Migration Approach
Industry’s best practices suggest:
- Migrate in phases either domain by domain or in geography.
- Run both systems for a parallel time frame for validation.
- Stage for cloud storage if scaling is an issue with large data sets. Staging can support performance and rollback.
4. Compliance and Security
MDM in cloud introduces possibilities around data residency, encryption, and role-based access control. You need to validate compliance with Informatica security compliance framework and internal audit needs.
Seven-Step Migration List for Moving from Custom MDM to Informatica SaaS MDM
- Know your business scope. Know your success metrics
Migration starts by deciding what data domains need to be migrated, which downstream systems depend on these data domains, and which business use cases need to be supported at go-live. Success metrics should be quantified, i.e., deduplication rates, improved data quality, or reconciliation rates with downstream applications. Executive sponsorship is also needed along with cross-functional agreement among IT, data governance, business owners, and architecture teams.
- Do data discovery and inventory
With a discovery sprint, there is a lower risk of missing anything essential. Record every system that currently feeds the custom MDM system and make note of formats, frequency of updates, and integration approach. Document any and all existing business rules and survivorship logic, as well as deduplication assignments. Profile the data and identify potential quality issues—like duplicates, incomplete fields, and inconsistent formats. It’s also important to document any scripts or manual workarounds because these often hide business logic that will need to be replicated or improved upon as part of the migration.
- Design the target model and mapping
Align the existing data model to Informatica’s domain templates. Now is the time to rationalize attributes, eliminate deprecated fields, and use industry standards. Define survivorship and deduplication strategies, identify required enrichment and standardized fields, and establish how historical data will be archived or transformed. Document mappings for attributes as needed and agree to a target schema with business and technical stakeholders.
- Build migration architecture and automation
Determine which data ingestion and data transformation methods will be used to get data into Informatica MDM SaaS as Informatica supports a wide range of ingestion options, from batch pipelines to APIs to set the ingestion method of choice. For example, to ingest a large volume of data, often the best approach is to stage the data in the cloud storage and then ingest it in parallel. Additionally, automate all quality checks, reporting, and reconciliations to manage, track, and reduce the amount of manual work. Create a phased ingestion strategy by ingesting small samples of data first and then scaling over time.
- Execute data cleansing and trial loads
Conduct focused cleaning and matching cycles on sampled datasets to correct improper identifiers, standardize addresses, deduplicate data, or normalize product or supplier codes. Engage business users in the validation of matching rules to ensure matching results meet required operational needs. Iterative trial ingests can be useful in refining performance and uncovering hidden issues prior to a full-scale migration.
- Perform full migration and data validation
Conduct a complete migration rehearsal. Validate the number of records, calculate checksums, reconcile downstream queries, and compare the golden record. Rehearsals should replicate the production cutover, from the freeze windows to rollback procedures and downstream system updates. Have some sort of automated validation scripts to verify critical measures such as record counts, data quality scores, and downstream KPIs. Run legacy and SaaS MDM in parallel, if possible, for x weeks or months to compare parallel outputs to help mitigate risk.
- Execute Cutover and Manage Hypercare
Utilize a defined runbook for the cutover. If needed, halt updates to the legacy system, run final delta loads, and point downstream systems to the Informatica endpoints. Ensure hypercare support is in place – stewards and technical support team members are available to resolve issues quickly. SLAs, performance of data flows, and reported user issues should be monitored in real-time fashion. After stabilization, hold a lesson learned workshop and build a roadmap for future enhancements – like adding the next domain or enabling AI matching.
Migration Checklist
Pre-Migration
- Alignment of executive sponsor and stakeholders
- Source systems and data feeds documented
- Data profiling completed
- Target schema and survivorship rules approved
Migration
- Automated ingestion pipelines built and tested
- Validation scripts in place
- Trial ingests completed and tuned
- Prepared for parallel run
Post-Migration
- Trained team on Informatica interfaces
- Launched monitoring dashboardsLaunched monitoring dashboards
- Archived legacy data in an accessible manner
- Documented continuous improvement roadmap
Lumendata's Unique Migration Capabilities
At LumenData, we focus on data strategy, MDM implementations, and AI-driven analytics. As an Informatica Platinum Partner, we provide:
- QuickStart Programs which accelerate SaaS MDM deployments.
- Accelerators that speed up time-to-value.
- Advisory and implementation expertise.
- End-to-end capabilities: strategy, integration, governance, training, and managed services.
Whether you are coming from a custom-built system or modernizing from legacy on-prem MDM, LumenData will ensure a smooth, low-risk migration. LumenData worked with a global cruise-line who was struggling with fragmented guest data that resided in booking, loyalty, and on-board systems. By implementing Informatica Customer 360, the client was able to do the following:
- Consolidate millions of guest records into a single source of truth.
- Improve guest experience with more personalized offers.
- Decrease the time it took to onboard new customer data into marketing and CRM platforms.
Conclusion
The transition from a custom or on-premises MDM environment to Informatica SaaS MDM is challenging but achievable with a well-conceived plan, the appropriate tools, and the right expert partner. Enterprises that follow the thorough, phased approach detailed above will limit the risks while benefiting from scalable, AI-driven Master Data Management capabilities. Lumendata’s proprietary accelerators, significant Informatica experience, and practical methodologies streamline migration to put organizations in the best position to benefit from modern MDM—their MDM migrations will be quick, smooth, and preserve data fidelity and business continuity throughout the process. If modernizing your MDM platform is a priority, partnering with Lumendata will result in a customized, best-in-class migration experience tailored for your specific business/technical needs.
About LumenData
LumenData is a leading provider of Enterprise Data Management, Cloud and Analytics solutions and helps businesses handle data silos, discover their potential, and prepare for end-to-end digital transformation. Founded in 2008, the company is headquartered in Santa Clara, California, with locations in India.
With 150+ Technical and Functional Consultants, LumenData forms strong client partnerships to drive high-quality outcomes. Their work across multiple industries and with prestigious clients like Versant Health, Boston Consulting Group, FDA, Department of Labor, Kroger, Nissan, Autodesk, Bayer, Bausch & Lomb, Citibank, Credit Suisse, Cummins, Gilead, HP, Nintendo, PC Connection, Starbucks, University of Colorado, Weight Watchers, KAO, HealthEdge, Amylyx, Brinks, Clara Analytics, and Royal Caribbean Group, speaks to their capabilities.
For media inquiries, please contact: marketing@lumendata.com.
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