Solving the Data Quality Moving Target for Data Teams

Modern organizations exchange massive volumes of data every day with customers, vendors, partners, suppliers and internal teams. That data fuels everything from marketing and fulfillment to analytics and compliance. The catch? Before data can be trusted, it has to be validated, cleansed, standardized and enriched.

That sounds simple in theory. In practice, it’s a moving target.

File formats change. Columns get added, removed or reordered. New data fields appear with little notice. Short-term initiatives pop up. Systems evolve. Meanwhile, data stewards are expected to ensure accuracy, consistency and usability while technical teams scramble to keep pipelines from breaking.

So how do you balance automation with flexibility? How do you empower business users to manage data quality?

The Data Quality Challenge

Most organizations rely on technical teams to build automated data workflows using ETL tools, scripts, APIs or integration frameworks. When data structures are stable, this works well. Automation saves time, reduces manual effort and keeps processes consistent.

But when inputs constantly change, full automation becomes painful. Developers and DBAs spend more time firefighting than building. At the same time, data stewards are stuck waiting on technical updates for even small validation or cleansing changes.

What’s missing is a way for data stewards and power users to actively participate in data quality workflows, without needing to write code or rebuild pipelines every time something shifts.

A More Flexible Approach to Data Quality

Unison by Melissa was designed to solve exactly this problem.

Unison is a data quality platform built for collaboration between technical teams and data stewards. It allows organizations to standardize core processes while giving business users the flexibility to validate, cleanse, enrich and prepare data before it ever reaches production systems.

Instead of forcing every change through custom code, Unison provides a project-based, visual workflow that supports:

• Data validation and standardization
• Address, name, phone and email cleansing
• Enrichment using postal-certified reference data
• Import and export from databases, spreadsheets and flat files

• Reusable workflows and scheduled jobs

All without requiring programming expertise.

How Unison Works

At a high level, Unison follows a simple three-step process:

1. Define the input source: Data can come from databases, spreadsheets or flat files. Unison automatically detects file structures and previews data, while still allowing manual configuration when needed.
2. Configure data quality tasks: Users select the validation and cleansing tasks they need, such as address verification, name parsing, or email and phone validation. Each task maps input fields to standardized, validated output fields using Melissa’s data quality algorithms and global reference data.
3. Specify the output: Cleaned data can be written back to files or databases, filtered based on validation results, reordered or compressed for downstream use.

Before running a job, users can preview outputs, adjust columns and confirm everything looks right, reducing errors before data moves further downstream.

Built for Real-World Data Complexity

Unison is designed for the messy reality of modern data environments and offers:

• Global address validation across 240+ countries
• Postal-certified accuracy with regular metadata updates
• High-performance processing capable of handling tens of millions of records per hour
• Collaboration-friendly workflows that allow teams to reuse, modify and schedule projects
• Deployment flexibility, including on-premises and containerized environments to meet security and performance needs

Most importantly, it puts data quality control in the hands of the people who know the data best, without removing oversight from technical teams.

The Payoff

Organizations using Unison can:

• Reduce time spent fixing data issues downstream
• Lower the burden on DBAs and developers
• Improve consistency and trust in customer and operational data
• Introduce data quality earlier in business processes
• Adapt faster when requirements change

Instead of reacting to data problems after the fact, teams can proactively manage quality at the source.

Next Steps

If your organization struggles with constantly changing data inputs, fragile pipelines or overloaded technical teams, it may be time to rethink how data quality is handled.

Unison helps bridge the gap between automation and flexibility so data stewards can do their jobs effectively, and technical teams can focus on building and scaling systems that matter. You can request a Unison demo on our website, or call 1-800-MELISSA. Don’t forget to subscribe to our blog for everything related to data quality!