Milestones in Data Quality
U.S. Department of Education - Delivered technology & methodology to ensure high-quality data in federal education data collection system.
School District Data Management - CertifyTM - 250+ districts use Certica’s data quality SaaS application to validate application & compliance data.
K-12 Application Interoperability - Data ConnectTM is a unique application interoperability platform, based on the Ed-Fi open source data standard & technology.
What have We Learned?
- Districts have a myriad of information systems with hundreds – or thousands – of users interacting with data daily.
- District staff has limited resources, with increasing data requirements and demands.
- Manual data “cleaning” processes are time-consuming, inconsistent, error-prone and unmeasurable.
- Staff members’ relationship with data is negative/stressful, nagging usually involved.
The Ramifications of Poor Data Quality
- Missed funding.
- State reporting errors, audits and penalties.
- IT investments such as dashboards are under-utilized.
- Embarrassing mistakes on public-facing reports.
- Lack of accountability and data ownership.
- Students are not adequately served.
Key Strategies for Successful Data Quality
1. Focus on source data, every day.
- Validating, monitoring and correcting data in source databases (SIS, HR & Finance, Special Education, etc.) on a daily basis minimizes potential contamination of downstream systems.
- With a daily source system validation process, data discrepancies are identified before small issues result in bigger problems.
2. Use a single, secure process.
- Running reports and ad hoc queries, emailing spreadsheets and manually hunting for data errors is time consuming and risks exposure of student data.
- A better approach is to employ a proven data quality process district-wide for all data users, departments and school staff.
3. Tackle business rule integrity.
- Single-field data validations are easy, but testing data continuously for business rule integrity is where you’ll find lost funding, compliance violations and accountability concerns.
- Data should be checked for potential basic and complex issues pro-actively, before data is submitted to state and federal entities.
4. Seize the learning opportunity.
- Involving school staff in the process of reviewing and cleaning up data is an opportunity to reinforce data rules, processes and policies.
- Including clear instructions for data clean-up will lead to better data entry in the future.
- Empowering school staff to take ownership of a data quality process will lead to greater accountability.
5. Quantify your progress.
- Remember the adage “you can’t manage what you can’t measure”? Data quality can be measured.
- Apply metrics and make them visible across your district.
- Examples: How many fewer data errors since the start of the year? Which schools have the highest quality data? How much is bad data costing the district?
What is Certify?
- Data quality platform.
- Business rules engine.
- Continual validation and refresh of data.
- Push model for daily data quality results.
- Designed to scale.
The Certify Results Difference
What Our Users Are Saying
"Having Certify is like having a team of people comparing hundreds of data points every night. It not only saves us time, but money as well.”
“I am telling everyone who does not have Certify to get it if they can. When I have meetings with my data entry personnel they are always telling each other their Data Certification Score to see which school is better. Everyone wants to be at 100.”
“It's just amazing how simple Certify makes it to look at the data. I love how it points out instances BEFORE they become problems!”