Building Certified, Trusted Data Natively in Snowflake with Semarchy xDM

Introduction

Managing clean, consistent, and governed data at scale is every modern data team’s biggest Achilles heel. And as organizations move more workloads to cloud environments like Snowflake, many are finding that traditional master data management (MDM) tools weren’t designed to keep up with the flexibility, scale, and speed that today’s platforms demand.

That leaves data professionals grappling with familiar pain points: governing inconsistent records across systems, maintaining clean pipelines, and ensuring the right version of the truth flows into reporting, analytics, and AI models. Semarchy’s Snowflake Native App changes that. As the first fully integrated native MDM application for Snowflake, Semarchy xDM consolidates data, enforces quality controls, enriches records, and manages governance workflows directly within your Snowflake environment. No external movement. No added infrastructure.

What makes it especially relevant now? xDM also helps teams prepare trustworthy data for advanced analytics and machine learning use cases, where quality and consistency are non-negotiable.

In this post, we’ll walk through practical use cases, explain how the Semarchy app works under the hood, and demonstrate how to configure and deploy it within your Snowflake environment. We’ll also cover how to utilize its low-code tools, API-first design, and CDC features to manage governed, analytics-ready data at scale.

What is Semarchy’s Snowflake App?

Overview of Semarchy’s Native Snowflake App

Semarchy xDM is a Snowflake Native App purpose-built to deliver MDM directly within the Snowflake environment. Unlike traditional MDM solutions that operate outside your data warehouse, xDM runs natively, meaning all processing, workflows, and storage happen inside your Snowflake account. 

The app is deployed as two containers: an application server and a Snowflake-hosted database. It supports data ingestion via REST APIs or Snowflake SQL landing tables. Once data enters the system, Semarchy’s certification engine processes it through configurable matching, enrichment, validation, and approval workflows, creating golden records that are stored natively in Snowflake.

From there, these records are accessible for analytics, business intelligence (BI), operational dashboards, or machine learning pipelines, without requiring additional movement or duplication.

Core MDM functionality includes:

• Entity modeling (e.g., customers, products, vendors)
• Data consolidation and survivorship
• Built-in AI-enrichers and external AI-API integration, including compatibility with Snowflake’s Cortex AI functions 
• Validation rules and exception handling
• Workflow-based stewardship and approvals
• Role-based dashboards for visibility into data quality KPIs

By managing data governance logic and quality controls at the point of storage, xDM helps Snowflake users shift from passive data hygiene to active data trust.

Why It’s Relevant to Developers

Semarchy’s Snowflake app enables developers to build powerful, governed data workflows directly within the Snowflake environment, minimizing manual effort and hand-coded logic. But the real value? Developers can configure domain models, certification pipelines, and governance rules once, then hand off day-to-day stewardship and approvals to business users through role-based interfaces and guided workflows.

By separating the technical scaffolding from the operational upkeep, xDM reduces developer burden while improving enterprise-wide data quality. Here’s how developers benefit:

• Design once, reuse often: Define certification logic, enrichment rules, and validation workflows declaratively, allowing them to be reused across domains and scaled over time.
• Empower business users: Build user-friendly forms, dashboards, and workflows that allow non-technical stewards to validate, approve, or correct records without writing a single line of code.
• Avoid custom governance tooling: Replace brittle, bespoke data quality checks with robust, transparent logic that lives natively in Snowflake and can be version-controlled.
• Integrate flexibly: Use REST APIs or Snowflake SQL to integrate with upstream pipelines, downstream BI tools, or external enrichment sources.

Key Features and Benefits for Developers

1. Native Integration with Snowflake

Semarchy xDM runs entirely within your Snowflake account as a native application. There’s no need to provision external compute or move data out of your environment for processing. All actions (matching, validation, enrichment, and approvals) are executed using Snowflake’s compute and storage capabilities.

The application is composed of two containers: an application server (used for orchestration and metadata configuration) and a native Snowflake database schema that houses certified golden records and operational metadata. Ingest data into xDM via two primary methods:

• SQL Landing Tables: Load data into predefined staging tables using Snowflake pipelines or your preferred ETL tool.
• REST APIs: Push data into Semarchy’s certification engine via structured API calls, allowing integration with real-time or event-based sources.

Semarchy also integrates with Snowflake’s native features, including:

• Warehouses: Compute scaling for profiling, validation, and transformation jobs
• Role-based access control (RBAC): Aligns with Snowflake’s security model
• Secure Data Sharing & Cortex AI Integration: Use certified golden records across business units or partners via secure views or Snowflake data shares. Enrich data further by integrating with Cortex AI services to generate insights, perform document classification, or apply ML models directly on trusted data.

This tight integration means no back-and-forth data movement, fewer latency issues, and simpler governance and compliance.

2. Real-Time Data Streaming and Change Data Capture (CDC)

Semarchy supports real-time data streaming by working in tandem with Snowflake-compatible Change Data Capture (CDC) pipelines. These pipelines detect changes in source systems (like inserts, updates, or deletes) and push only the incremental changes into Snowflake, reducing data movement and processing overhead.

Here’s how it works:

1. CDC captures incremental changes from operational systems and sends them to Snowflake via your preferred pipeline.
2. Changes land in Snowflake staging tables, where they’re made available to Semarchy xDM for processing.
3. Semarchy’s certification engine automatically runs:
   • Match rules (e.g., fuzzy or phonetic matching)
   • Survivorship logic (field-level merge preferences)
   • Enrichment (via APIs or built-in rules, or Snowflake Cortex AI services)
4. Workflow logic is triggered if approvals or exceptions are required.
5. Validated records are written to certified tables in Snowflake.

3. No-Code, API-First Data Management

xDM gives developers a visual interface to build MDM logic fast, without losing control. The Application Builder provides drag-and-drop modeling for:

• Defining entities and attributes
• Creating relationships between domains (e.g., Customer → Address)
• Assigning validation logic and business rules
• Designing user forms and data exploration views

But the real strength lies in its extensibility:

• All functionality is exposed via REST APIs for ingestion, approval, status checks, and export.
• Versioned metadata allows you to treat data models and workflows as assets that can be published, iterated, and deployed using CI/CD-like flows.
• Compatible with Snowpark and SQL-based orchestration for seamless integration into modern data stacks.

4. Data Governance and Quality

Semarchy treats data governance as a configuration-first exercise. Developers can define validation and quality rules declaratively within the UI or via API, including:

• Field-level validation (e.g., required fields, regex checks)
• Conditional logic (e.g., enforce naming conventions by region)
• Match thresholds and survivorship policies
• Approval steps with assigned users or groups

Example: A rule to flag missing company names unless the record originates from India or Vietnam might look like this:

{

  “rule”: “MISSING_COMPANY_NAME”,

  “logic”: “IS_NULL(companyName) AND country NOT IN (‘IN’, ‘VN’)”,

  “severity”: “high”,

  “action”: “flag”

}

These rules can trigger workflows, be surfaced in dashboards, or route records to stewards for correction. Dashboards are built using the integrated Dashboard Builder, which supports:

• Quality KPIs
• Violation trend tracking
• Approval cycle metrics
• Domain-specific summaries (e.g., supplier completeness, product hierarchy health)

The result is not just visibility, but the ability to enforce and continuously improve governance policy without custom code.

Step-by-Step Guide: Setting Up Semarchy xDM in Snowflake

Getting started with Semarchy xDM as a Snowflake Native App is straightforward. If you’ve deployed other marketplace apps in Snowflake, this process will feel familiar. Here’s a high-level walkthrough of what the process looks like:

1. Install xDM from the Snowflake Marketplace

Find Semarchy xDM in the Snowflake Marketplace and click “Get” to deploy the app directly into your account.

2. Set Up Application Containers and Roles

Semarchy uses two Snowflake containers:

• A frontend application container for the UI and workflows
• A backend database container for storing metadata and golden records
  • Assign roles, warehouses, and object privileges as needed (Semarchy provides starter SQL scripts).

3. Configure Your First Domain and Data Model

Using the App Builder:

• Define entities and attributes (e.g., name, address, ID)
• Create relationships and set validation rules
• Publish to auto-generate screens and workflows

4. Ingest Source Data

Use:

• Snowflake landing tables
• REST APIs for external ingestion
  • Load data from CRMs, ERPs, flat files, or pipelines, then profile and prep for matching.

5. Define Matching, Enrichment, and Approval Logic

Within the App Builder:

• Set up match rules (exact, fuzzy, phonetic)
• Configure enrichment via APIs or built-in functions
• Build multi-stage approval workflows for exceptions

6. Publish and Monitor

Deploy your application and use Semarchy’s dashboards to:

• Monitor profiling results and workflow activity
• Track data quality trends and rule violations
• Visualize Golden Record lineage and performance

For more detailed setup steps, refer to the full deployment documentation.

Best Practices for Using Semarchy xDM with Snowflake

Semarchy xDM is built to run natively in Snowflake, leveraging its security, compute, and integration capabilities. To maximize the benefits of your implementation, consider the following best practices for configuration.

Performance Optimization

• Right-size Snowflake warehouses: Use Snowflake’s flexible compute model to assign appropriate warehouse sizes to your profiling, validation, and certification jobs based on workload.
• Use built-in delta processing: xDM supports processing only changed records when possible, reducing overhead and improving job efficiency.

Security and Governance Configuration

• Align with Snowflake’s RBAC model: Semarchy supports role-based permissions that match Snowflake’s access control structure, ensuring secure data domain access and stewardship workflows.
• Enable audit logs: Track changes, approvals, and stewardship activity through xDM’s built-in auditing features and Snowflake account usage logs.

Scalability with Large Data Volumes

• Model cleanly from the start: Use Semarchy’s Application Builder to create structured domains with clear relationships and validation logic. Good initial modeling simplifies future scale.
• Publish incrementally: Deploy and test individual data models and workflows before scaling to enterprise-wide domains.

For additional guidance on deployment architecture, permissions, and job orchestration, refer to the official documentation.

Real-World Use Cases and Applications

Semarchy xDM offers flexible, Snowflake-native capabilities that make it well-suited for various data management applications. Here’s how different teams might apply it across domains.

1. Data Quality Management in Financial Services

Financial institutions depend on trusted, consolidated records to meet regulatory requirements and support customer-facing operations. Using Semarchy xDM, a data team could:

• Consolidate customer records from CRM, billing, and support systems into a unified domain
• Use phonetic or fuzzy matchers to identify duplicate or inconsistent records
• Enforce validation rules (e.g., missing required fields, invalid formats) through the Application Builder
• Route flagged records through approval workflows, assigning tasks to compliance or data stewards
• Monitor remediation efforts using role-based dashboards and data quality KPIs

Because all of this runs directly inside Snowflake, there’s no need to export sensitive data for cleansing, keeping the process compliant and efficient.

2. Supply Chain Integration for Manufacturing

Manufacturing and logistics teams often work with fragmented supplier and shipment data coming from ERP, inventory, and order systems. With Semarchy xDM, they can:

• Create a supplier domain that maps relationships between vendors, products, and shipping locations
• Load structured data via Snowflake staging tables or external APIs
• Apply survivorship logic to prioritize the most complete or recent records
• Use built-in or external enrichment to validate addresses or standardize naming
• Certify and publish golden records that can be reused across procurement, inventory, or analytics dashboards

This approach simplifies operational reporting and reduces the risk of duplicated or conflicting supplier records.

3. AI and ML Data Readiness

Semarchy xDM can help data science teams prepare high-quality, structured datasets for training and inference. Typical activities might include:

• Defining and enforcing consistent taxonomy across product, customer, or transaction records
• Removing duplicates and resolving inconsistencies across data sources before training
• Tagging data with enrichment metadata such as categories, segmentation flags, or external ratings
• Creating certified, versioned records that feed directly into Snowflake-based ML pipelines (e.g., using Snowpark or integration with tools like dbt)

By centralizing this data prep in Semarchy, teams can streamline ML model development and reduce the manual data wrangling that often slows projects down.

Conclusion

Semarchy xDM brings a modern, developer-ready approach to data management inside Snowflake. With its low-code tools, powerful matching logic, and built-in governance workflows, it empowers data teams to model, certify, and operationalize high-quality data, right where it resides.

Whether you’re reconciling customer identities, standardizing supply chain inputs, or preparing machine learning datasets, xDM allows you to do it natively, securely, and at scale.

Ready to get started?

• Try xDM free for 7 days on Snowflake 
• Read our Modern MDM for Snowflake eBook
• Explore our Snowflake partner page
• Review the technical deployment guide