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Tennessee Longitudinal Data system (TLDS). 26 th Annual MIS Conference February 14, 2013. Answers We Didn’t Have Until Now. Glynn Ligon, Ph.d . ESP Solutions Group. 2. Agenda. Overview Data Domains What can we do with TLDS? Governance Committee Representation
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Tennessee Longitudinal Data system (TLDS) 26th Annual MIS Conference February 14, 2013
Answers We Didn’t Have Until Now Glynn Ligon, Ph.d. ESP Solutions Group 2
Agenda • Overview • Data Domains • What can we do with TLDS? • Governance • Committee Representation • Data Access and Management Policy • User Roles and Data Visibility • Project Delivery • Timeline • Phased/Multi-Agency Project • Phased Deployment • Infrastructure and Security • Modularized Environment • Pre-Production Activities • Security Controls • Performance Analysis • Data and Matching • Data Sources • Database Framework • Unique Identifier (MPI) • Web Portal and Dashboards • Web Portal Overview • Data Visualization Capabilities • Closing Comments and Questions 3
Overview 4
Data Domains • Human Services • Census Bureau • Child Services Beyond • Correc- tions 2011/2012 5
What can we do with TLDS? Make informed decisions based on data • Assess Effectiveness of Policies and Programs • Identify impact/outcomes of services • Example: Unemployment or wage by education attained (i.e., Degree, Program) • Example: Determine success of program participants • Understand and align programs to workforce demand • Example: Adult education programs to develop computer skills when unemployed or incarcerated • Evaluate College and Career Readiness • Curriculum evaluation and reform • Example: Graduates require remediation in math despite taking Algebra II • Develop College and Career Indicators • Identify individual remediation needs and action plan • Example: Student declares desire to study engineering yet has only a basic proficiency in math • Improve Efficiency of Agency Operations • Cross agency information sharing • Example: Provide view of information for federal compliance reporting 6
Tammy Lemon University of Tennessee GOVERNANCE 7
Committee Representation P20 TLDS Steering Committee Data Contributors: TN Higher Education Commission Labor and Workforce Development Education Advisors: Human Services Children Services Governor’s Office UT-CBER TN Board of Regents UT-System TN Independent Colleges and Universities Work Group Committee: • IT Data System Experts • Data Knowledge Experts Project Management: • UT-CBER • ESP Solutions Group • Steering Committee: Data contributors, potential contributors, and project leaders • Establish project governance structure and objectives • Define access policy, who can see data and define procedures • Work Group Committee: Technical and data experts • Establish process for data export • Define business rules for transformation • Resolve data anomalies • Validate transformed data 8
Data Access & Management Policy • Types of Data Sourced • Relevant State and Federal Regulations • Responsibilities of the Agencies and CBER • User Roles for Access • Levels of Data Visibility • Approvals Required for Access • Security Measures to Protect the Data • Additional Procedures: • Annual Policy Review • User Management and Monitoring • Researcher Request for Data 9
User Roles & Data Visibility • Aggregate Data • Public Consumer • Partner Agency Consumer • Masked Individual Records • Agent of Partner Agency Researcher • External Researcher • Identifiable Individual Records • Partner Agency Researcher • Partner Agency Administrator • System/Data Administrator 10
Tom Jenkins University of Tennessee PROJECT DELIVERY 11
Timeline 12
Phased/multi-agency Project • Multi-Phased Deployment • Portal Content Lags Warehouse by 1 Phase • Three Agencies • Labor and Workforce Development • Department of Education • Higher Education Commission 13
Jim RIfe ESP Solutions Group INFRASTRUCTURE and SECURITY 15
Pre-Production Activities • Warehouse Source Analysis (4 Phases) • Discard Analysis • Data Validation • Portal Development • Data Cubes/Analysis Services • Data Visualization • Reporting Capabilities • Security • Performance Analysis 17
Security controls • Data Access Controls • Specified by the Data Governance Committee • Undergoing Security Control Assessment • Based on NIST-FIPS 180-53 • Goal to achieve Mid-Moderate Baseline • Leveraging University of Tennessee OIT’s Data Center • Physical Security • Contingency Management • Network Infrastructure 18
Tom Jenkins University of Tennessee DATA and MATCHING 22
Data Sources 23
Imart data management framework • Data Imported ‘As-Is’ • Transformed to iMart Data Model • Assign Unique Identifier • Publish to Reporting Warehouse • Create Cubes for Analysis 24
Unique Identifier (MPI) Overview • Identify individuals across multiple data domains using matching algorithms • Mask sensitive data to protect identity of individual • Assigns identifiers to uniquely identified individuals • Common elements: SSN, Name, and Birth Date • Not consistently available in all data sources • Can assign multiple identifiers • Flexible when new elements available for matching 25
MPI Process Create Unique ID2 Source Data Apply Unique ID3 Identify New1 Identifies a new combination of data elements to enter matching process Steps through series of algorithms to determine if combination is unique and creates Unique ID Applies Unique ID to all individual records and suppresses identifiable data (Name, SSN/Fed EIN, and Street Address) in the reporting warehouse 26
Tammy Lemon University of Tennessee WEB PORTAL and DASHBOARDS 27
Web portal Overview • Public Portal • Dashboards • Online Training • Secured Portal • Confidential Reports • Collaboration Tools • Data Analysis and Export • Research Request • Applicant Registration • View Data Domains • Request Data • Provide Data/Access 28
Public portal Perspectives • Interactive Dashboards • Role Base Navigation • I am A: Parent, Student, Employer, Job Seeker • Perspective Based • Starting School • Starting Work • Attending College • Second Careers 29
Data Visualization capabilities • Data Domains Linked (K12, Post-Secondary, Staff, Workforce) • FERPA Compliant • Integrated and Sophisticated Design • Deep-dive, Drill-through Exploration of Metrics • Comparison and Trend Analysis • Technology: • Microsoft BI Stack • SQL Server 2008 R2 with SSRSand SSAS • SharePoint 2010 with Performance Point and Power Pivot • Assessing SQL Server 2012/SharePoint 2013 vs. Tableau 30