Best Master Data Management Cloud for Businesses

Best Master Data Management Cloud Options for Businesses

MDM Cloud for Businesses Selecting the right master data management (MDM) cloud solution is crucial for businesses looking to improve data quality and governance. The right MDM system can help break down data silos, eliminate duplicate records, and provide a single source of truth for critical business data. In this comprehensive guide, we'll explore the top MDM cloud platforms and key factors to evaluate when choosing an MDM cloud provider.

Overview of Master Data Management in the Cloud

Master data management in the cloud refers to MDM software delivered as a cloud-based service or software-as-a-service (SaaS) model. Some key benefits of cloud-based MDM include:

• Lower upfront costs: MDM cloud eliminates large upfront investments in software and hardware. Businesses pay a monthly or annual subscription fee.
• Faster deployment: MDM cloud solutions can be up and running in weeks or months versus on-premises systems which can take 6 months or more.
• Scalability: Cloud MDM allows you to easily scale capacity and users up or down as needs change.
• Regular updates: Cloud MDM vendors manage updates and maintenance without additional IT overhead.
• Accessibility: Users can access cloud MDM from anywhere with an internet connection. Useful for global and mobile teams.
• Security: Reputable cloud MDM vendors employ robust security like encryption, access controls, and high availability.

While on-premises MDM still works for some large enterprises, cloud MDM offers faster time to value and lower TCO for most organizations.

Top Cloud MDM Solutions for Businesses

Some leading cloud MDM platforms to consider include:

Informatica CLAIRE

Informatica CLAIRE is a leading cloud MDM platform built on AWS. Key features include:

• Metadata-driven architecture for flexibility
• AI/ML for data quality and matching
• Pre-built connectors and data model templates
• Role-based self-service for business users
• Integrations with Salesforce, Workday, and other apps

Ideal for midsize to large enterprises in any industry seeking robust MDM capabilities.

IBM InfoSphere Master Data Management

IBM offers a robust cloud-based MDM platform leveraging AI and self-service features. Highlights:

• Business user self-service portal -prebuilt industry data models
• Automatch machine learning for matching
• Integrates with Watson Knowledge Catalog
• Data virtualization and data quality capabilities

Well-suited for regulated industries like banking, insurance, and healthcare.

Oracle Cloud MDM

Oracle Cloud MDM provides a flexible cloud platform for PaaS MDM across channels, suppliers, products, locations, and more. Key features:

• Prebuilt customer and product data models
• Embedded data quality and matching
• REST APIs for integration
• Role-based self-service and stewardship
• Transaction logging for auditability

Ideal for existing Oracle customers seeking a cloud-based MDM system.

SAP Master Data Governance

SAP offers a cloud MDM solution tightly integrated across SAP's product portfolio. Key highlights:

• Tight integration with S/4HANA, C/4HANA, and Ariba
• Business user self-service features
• Hierarchy and relationship management
• Integrated data quality, validation, and matching
• Monitoring apps and preconfigured dashboards

A logical choice for SAP-centric organizations seeking enterprise-grade cloud MDM.

Stibo Systems STEP

STEP offers full MDM capabilities for both cloud and on-premises. Key features:

• Graph-based master data modeling
• Business-friendly web interface
• Automated data quality and entity resolution
• REST APIs for integration
• Role-based self-service management

Flexible for organizations with complex MDM needs across cloud and on-premises.

Key Evaluation Criteria for Selecting a Cloud MDM Platform

Factors to consider when evaluating cloud MDM platforms:

Integrations

• What out-of-the-box connectors does it have?
• What APIs are available for custom integrations?
• How easy is it connect to requisite source systems and applications?

Data Modeling Capabilities

• Does it have pre-built data models for customer, product, suppliers etc?
• Does it allow hierarchical, graph-based, and relationship modeling?
• How flexible is the data modeling for custom entities?

Data Quality

• Does it provide built-in data quality features like validation, standardization, deduplication etc?
• Are there automation and machine learning capabilities?
• Can it integrate with external data quality tools?

Self-Service & Stewardship

• Does it allow business users to update, enrich, find, and report on master data?
• Are there built-in workflows for stewardship and governance?

Security

• Does the vendor provide robust access controls, encryption, and security certifications?
• How is data access restricted and user activity logged?

Cloud Deployment & Scalability

• How flexible are the cloud deployment options (public cloud, private cloud etc)?
• How easy is it to scale users and capacity up and down?

Total Cost of Ownership

• What is the pricing model (per user, per record, etc)?
• What level of support, maintenance, and training options are included?
• How do costs compare to on-premises or alternative models?

Selecting a solution that aligns with your use cases, integrations, deployment preferences, and budget will be critical for MDM success.

Steps for Implementing Cloud MDM

Deploying cloud MDM involves careful planning and execution across these key phases:

Plan

• Document MDM business requirements, KPIs, and success metrics
• Perform due diligence on solutions
• Select MDM platform partner
• Build project team across IT, business analysts, and key stakeholders

Design Data Model

• Map key master data domains like customer, product, chart of accounts etc.
• Define attributes, relationships, metadata model
• Validate designs with stakeholders

Configure Software

• Provision cloud environment
• Install connectors for integration
• Customize workflows, forms, and interfaces

Integrate

• Connect MDM with source systems via APIs and connectors
• Develop ETL jobs to load data into MDM repository

Test

• Perform integration testing, QA, and user acceptance testing
• Refine workflows, business rules, and processes iteratively

Deploy

• Activate in production environment
• Roll out self-service portal, training for administrators and business users

Optimize

• Expand scope of entities and attributes over time
• Monitor adoption, data quality KPIs, user feedback
• Communicate wins and continue enhancing value

A phased rollout focusing on quick wins can help demonstrate MDM value. Appointing data stewards and gradually expanding self-service access enables sustainable adoption.

Pros and Cons of Cloud MDM

Pros

• Faster time to implement - weeks vs. months
• Pay-as-you-go subscription model
• Easy to scale capacity and users
• Automatic updates and maintenance
• Anywhere accessibility over internet
• Tight integration between modules

Cons

• Potential lock-in to software vendor
• Reliance on internet connectivity
• Perceived reduced customization flexibility
• Potential data security concerns
• Lack of existing integration with some legacy systems

Alternatives to Cloud MDM

Organizations should evaluate if an alternative solution like PIM, CRM, or data lake may fulfill their needs:

• Product Information Management (PIM) - Manages product data but lacks capabilities for customers, suppliers, finance etc.
• CRM - Manages customer 360 data but not broader domains. Should integrate with full MDM.
• Data Lake - Provides raw data consolidation but lacks governance, stewardship, and data quality of MDM.
• Hybrid On-Prem MDM - Allows on-prem system with cloud data integration. Adds complexity for full benefits.

For most robust master data capabilities needed to drive digital transformation, a dedicated cloud MDM platform is ideal for all but the very largest enterprises.

Conclusion and Recommendations

Selecting a purpose-built cloud MDM solution enables organizations to effectively consolidate, govern, manage, and consume master data across the enterprise. Leading solutions allow IT to control infrastructure and integration while empowering business teams via self-service access.

Key recommendations:

• Focus evaluation on cloud MDM alignment with use cases, integration needs, and budget
• Prioritize data quality, flexible modeling, stewardship, and ease of use
• Start with a phased pilot focused on 1-2 domains before expanding
• Complement with data governance program for sustainable success
• Measure data quality KPIs and metrics rigorously

With the right cloud MDM platform, businesses can achieve a single version of truth to maximize operational efficiency and provide trusted data to drive strategic decisions.

FAQs About Cloud MDM

Q: Is cloud MDM secure?

Cloud MDM offered by leading providers employ robust security protections including encryption, access controls, activity logging, and high availability. However, organizations should still perform due diligence on their cloud vendor.

Q: How long does cloud MDM implementation take?

Typical implementation spans 3-6 months. Starting with a focused pilot system can enable value realization within weeks before expanding broader capabilities.

Q: Can cloud MDM integrate with on-premises systems?

Yes, most cloud MDM solutions provide APIs, connectors, and integration technologies to integrate with on-premises sources like ERPs. Hybrid deployment is also an option.

Q: Does cloud MDM require master data consolidation?

For maximum value, businesses should seek to consolidate master data within their cloud MDM repository. Virtual or federated approaches can work but limit capabilities for stewardship, governance, and quality.

Q: What are examples of master data domains?

Common master data domains managed by MDM include customers, products, suppliers, locations, assets, accounts, materials, employees, and more.