Data Quality Essentials: From Entry to Excellence

Good data in means good results out. This course teaches you how to apply validation rules, fix errors, and build QA workflows that ensure your HMIS data is accurate, timely, and complete.

Updated September 9, 2025

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High-quality data doesn’t happen by accident — it’s built through consistent practices, validation checks, and careful attention to detail. Poor data entry leads to inaccurate reporting, weaker funding applications, and misleading performance measures that affect real lives. This course equips you with the tools and practices needed to ensure that every piece of data you enter contributes to an accurate, reliable, and trustworthy HMIS.

Through interactive exercises and real-world examples, you’ll learn how to spot and correct errors, follow validation rules, and build workflows that keep your agency’s data strong from start to finish.

What You’ll Learn

  • Why data quality is critical for clients, agencies, and the community
  • Key HUD validation rules and common data entry pitfalls
  • How to correct errors without breaking reporting standards
  • The role of timeliness, accuracy, and completeness in HMIS data quality
  • Quality assurance (QA) workflows and correction cycles
  • Practical strategies to build a culture of data accuracy at your agency

Course Content

Why Data Quality Matters
Garbage In = Garbage Out – The Stakes of Data Quality
Validation & Corrections
Common Data Entry Errors and How to Avoid Them
Validation Rules – What They Are & How They Work
Correcting Mistakes Without Compromising Integrity
QA Workflows & Agency Practice
Building QA Workflows (Monthly, Quarterly, Annual)
Using Reports & Dashboards for Data Quality Monitoring
Creating a Culture of Data Accuracy in Your Agency
Wrap-Up
Practical Case Study – From Bad Data to Clean Reports
Data Quality Mastery Check