The Data Management Challenge: Closing the Gaps

Organizations today typically manage data across multiple siloed systems — ERPs, CRMs, and legacy applications — each developed with different governance standards and use cases. This often leads to inconsistent and incomplete records, making it difficult to generate reliable business insights or apply advanced AI algorithms.

A 2024 study by the Harvard Business Review (HBR), sponsored by Profisee and Microsoft, revealed significant gaps in organizations’ readiness for AI and analytics. While 96% of respondents acknowledged the importance of high-quality data, only 58% felt their data was ready for AI-driven initiatives. Similarly, there were considerable gaps in data governance and platform readiness.

Key Data Management Gaps:

• MDM Gap: Organizations lack a unified approach to mastering critical data across systems.
• Governance Gap: Companies struggle to define and enforce data standards across their data estate.
• Analytics Platform Gap: Existing platforms aren’t fully integrated, hindering analytics and AI-readiness.

To close these gaps, businesses must prioritize building a solid data foundation through governance and MDM. This will ensure that data is not just available but also accurate, consistent and ready to use across all analytics and AI initiatives.

Why MDM Before Analytics: The Foundation for AI-Readiness

Before an organization can truly harness AI, it needs to ensure its data is consumable — clean, consistent and complete. Profisee MDM plays a crucial role in this process by consolidating and governing data across disparate systems to create a unified source of truth. With Profisee, organizations can match, merge and validate their data, ensuring it meets governance standards set by tools like Microsoft Purview.

How MDM Fills the Data Management Gaps:

• Match and Merge: Profisee MDM consolidates data from different sources, resolving inconsistencies and eliminating duplicates.
• Data Standardization: The platform ensures that data adheres to defined governance standards.
• Validation and Remediation: Data is validated against data quality metrics, and issues are corrected before feeding it into analytics and AI systems.

By creating this solid data foundation, businesses can confidently drive digital transformation, reduce operational inefficiencies and unlock new opportunities through AI.

The Power of Partnership: Microsoft Azure & Profisee MDM

Profisee is uniquely positioned to support AI and analytics initiatives in Azure. Recognized as a top-tier partner for Microsoft’s Data and AI programs, Profisee offers deep integration across Microsoft’s tech stack, making Azure ‘sticky’ for enterprises. In fact, Profisee was the first MDM solution to ship native connectors with Microsoft Fabric, Azure Data Factory and Power BI.

Key Integrations:

• Microsoft Purview: The governance platform that defines data standards, which Profisee MDM enforces.
• Azure Data Factory (ADF): Profisee MDM features pre-built pipeline templates with ADF, making it easier to integrate data from disparate systems.
• Microsoft Fabric: As the only MDM integrated with Microsoft Fabric from Day 1, Profisee allows seamless access to mastered data for analytics and AI consumption.
• Power BI: Profisee MDM provides a native connector for Power BI, making it easy to visualize data directly from the MDM hub.

These integrations not only simplify data management but also accelerate AI-enablement, allowing organizations to become AI-ready much faster.

Real-World Examples: Profisee in Action

1. Domino’s Pizza

Domino’s faced challenges in consolidating customer data across its multiple ordering systems — web, app, phone, CRM and point-of-sale. With Profisee MDM, the company created a central data hub, generating a single, trusted customer view that improved sales and marketing efforts. By automating data validation and deduplication, Domino’s was able to optimize campaigns, driving millions to the bottom line.

2. Mass General Brigham

As a leading healthcare system, Mass General Brigham needed a reliable way to manage their provider data across 12 health systems. By integrating Profisee MDM, they consolidated provider data from disparate sources, ensuring patients could easily search for providers. The result was improved patient experiences and more efficient data management.

3. Lexmark

Lexmark leveraged Profisee MDM to enhance its demand forecasting for print supplies. By breaking down data silos and cleansing customer location data, the company significantly reduced manual data prep for AI, saving 30% of workload and boosting combined revenue and savings by $2 million.

The Future: Consumable Data for AI

With Profisee MDM, businesses can transform raw data into consumable data products that are trusted, consolidated and ready for use in AI and analytics. This includes eliminating inconsistencies, automating data quality processes, and preparing data for use across advanced analytics tools like Azure Synapse, Azure Databricks and Power BI within Microsoft Fabric.

With the rapid advancements in AI, the ability to trust and govern data is becoming increasingly critical. By using Profisee MDM alongside Microsoft Azure, organizations can ensure their data is not only ready for analysis but can also power sophisticated AI applications like Azure OpenAI Copilot, driving new business insights and operational efficiencies.

Interested in seeing how Profisee can drive AI readiness at scale in your organization? Request a custom demo to see the power of consumable data for your business firsthand.