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Data Quality – By Chance or Design?

The Oregon DATA Project. Data Quality – By Chance or Design?. Data driven decision making Data teams High Stakes Accountability State collections. Data is in demand. Components of Quality Data Accuracy Timeliness Security Usefulness Quality data is needed for quality decisions.

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Data Quality – By Chance or Design?

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  1. The Oregon DATA Project Data Quality – By Chance or Design?

  2. Data driven decision making Data teams High Stakes Accountability State collections Data is in demand

  3. Components of Quality Data • Accuracy • Timeliness • Security • Usefulness • Quality data is needed for quality decisions Quality Data is mandatory

  4. Factors Affecting Components Quality Data Factors impacting quality Technology Hardware Policies & Regulations Timeliness Software Security Standards & Guidelines Network Utility Data Entry Environment Timelines & Calendars Accuracy Training & Professional Development By chance or design?

  5. Data Entry Environment • Setting supports data entry accuracy • Quiet, free from interruptions, provides privacy • Training • Annual review of data requirements • Data documentation (protocols, procedures) • Timelines • Data calendar • Who is collecting what and when Controlling the factors by design

  6. Policies and Regulations • Confidentiality expectations • Data security • Standards and Guidelines • Data entry performance standards • Expectations for accuracy and following protocols • Clear guidelines for process/responsibility • Technology • Supports data entry, spotting/correcting errors Controlling the factors by design

  7. Quality Data Roles Who has responsibility for quality? Directors Superintendent Board Member Teacher Office Staff Principal Technology Support Staff

  8. At an individual level • Creator • Takes responsibility for data elements they create and understands the impact of data accuracy • Confirmer • Understands the importance of accurate data confirmation to ensure data integrity • Consumer • Understands how to use appropriate data in appropriate ways to support instruction and student achievement Responsibility by design

  9. Factors Affecting • Leadership at the building/director level • Assumes overall ownership for data quality • Controls most of the factors that impact data quality Responsibility by design Technology Hardware Policies & Regulations Software Standards & Guidelines Network Data Entry Environment Timelines & Calendars Training & Professional Development

  10. Leadership at the building/director level • Assumes overall ownership for data quality • Controls most of the factors that impact data quality • Sets expectation for data accuracy, security, timeliness, and usefulness • Creates data steward oversight to maintain data quality (participates in district DQOC mtgs) • Identifies (holds accountable) those who consume, confirm, or create data at the building level Responsibility by design

  11. Superintendent • Sets district benchmarks that use data • Expects others to use data to drive decisions • Identifies a district data steward • Establishes data quality oversight committee (DQOC) – mtgs quarterly • Sets “data ownership” expectations • Building principals,district leaders (special ed, ELL, business, etc.) ResponsibilITY by design

  12. a Culture of data quality WHAT IF? Staff Reduction or Change No Data Stewardship Technology Changes - SIS BY CHANCE OR DESIGN? Increased Training Needs

  13. Create a culture of data quality within the district Use the concept map as a framework for discussing and improving data quality issues Insure that the responsibilities of a data steward are met within the district Data quality by design

  14. It is the belief that good data is an integral part of the educational enterprise. Everyone in the enterprise demonstrates that shared belief by using appropriate data to achieve the enterprise’s goal of student achievement. The enterprise is willing to invest resources to obtain quality data Everyone in the enterprise shows respect for the effort taken to produce quality data Defining a Culture of Data Quality

  15. Coordinate data collection process Provide training Resolve errors Establish audit procedures (data certification) Create Data Collection Calendar Develop and disseminate data entry standards Interpret data entry manuals for end-users Data Steward Responsibilities

  16. Collaborate with others (directors of curriculum, special education, assessment, etc.) Collaborate with the IT Director to enhance computer software for data entry, correction, and auditing Be the driving force for maintaining data accuracy, utility, timeliness, and security Be aware of the complexity and changing nature of the data required for state and federal accountability (State Collections, NCLB, etc.) Data Steward Responsibilities

  17. Developed easy to follow activities that can help build a culture of data 97 districts attended trainings across the state All ESDs had representation at the trainings www.oregondataproject.org The Oregon data project

  18. An outside voice to begin the discussion Provide consultation to district leadership on building a culture of data quality Facilitate activities Available until August 2011 The oregon data project

  19. Contact Ron Hoppes, Technical Training Coordinator ron.hoppes@state.or.us The Oregon data project

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