Data quality for education
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Did you know?
How bad data affects education?
Cross-jurisdictional matching remains a challenge
Inaccurate matches
States and educational institutions miss a significant number of matches during record linkage projects.
Departmental silos
Data residing across disparate sources reduces inter-departmental visibility across the entire organization.
Obsolete IT infrastructure
Lack of systems that can aggregate and prepare data in the required shape without compromising student privacy.
Inefficient stakeholder reporting
Data silos and absence of data standards can affect proper communication to private and public stakeholders.
Wasted resources
Inaccurate data leads to miscalculation of fill rates in various educational sections, resulting in wasted resources.
Poor program evaluation
Incomplete, missing, and duplicate records prevents educators from evaluating the effectiveness of assessments and education programs.
Solution
DataMatch Enterprise – The key to enhancing interagency record linkage
Customer Stories
See what educational organizations are saying...
DataMatch™ has cut my cleaning time down from 10-14 days to approximately 16 hours.
DataMatch Enterprise ™ gives us many facilities for the integration issue. We had a problem of duplication of records in which it helped us and was fantastic to solve in a very simple way.
The idea of linking two groups of records was overwhelming for the research department. The process would be very time-consuming and threaten the timeliness and process of the research activities
Business Benefits
What’s in it for you?
Increase enrollment rates
Access to quality data can help evaluate and improve programs to increase enrollment rates and retain under-performing students.
Implement effective policies
Enhance the reliability of data to plan and execute large-scale education policies and allocate appropriate funds and resources.
Establish master IDs
Define relevant match definitions and criteria to effectively track students from pre-school to the workforce across disconnected systems.
Reduce labor costs
Eliminate or cut significant labor costs associated with inspecting, cleansing, and standardizing thousands of records across multiple databases.
Access insights faster
Save hundreds of hours on manual data cleansing and analysis to ensure insights are accessible to stakeholders in a timely manner.
Secure program funding
Receive funding for educational programs from local or state governments for special-needs and underprivileged areas with reliable data.
Want to know more?
Check out DME resources
Merging Data from Multiple Sources – Challenges and Solutions
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