P20 State Core Logical Data Model September, 2010.

Slides:



Advertisements
Similar presentations
Whats a P20, and why would I want one? Center for Educational Performance and Information (CEPI) Margaret Merlyn Ropp, Ph.D. Director.
Advertisements

Previous Year 3 Overview Grant Budget Resources This presentation allows you to:  Review the overall expectations for Focus Schools, as outlined in Wisconsin’s.
Chapter 13 The Data Warehouse
Michael Pizzo Software Architect Data Programmability Microsoft Corporation.
What is the RIGHT Data? …a Kansas Perspective Strategic Data Project Spring 2012 Convening April 2012 Kathy Gosa, Kansas State Dept of Ed.
Technical BI Project Lifecycle
Management Information Systems, Sixth Edition
1 P-20 Data Dictionary November 16, :15 – 12:15 Kit Goodner, FL Mike McKindles, IL Rod Packard, WI.
Surfing the Data Standards: Colorado’s Path 2012 MIS Conference – San Diego Daniel Domagala, Colorado Department of Education David Butter, Deloitte Consulting.
Basic guidelines for the creation of a DW Create corporate sponsors and plan thoroughly Determine a scalable architectural framework for the DW Identify.
Lecture 5 Themes in this session Building and managing the data warehouse Data extraction and transformation Technical issues.
Chapter 13 The Data Warehouse
Prevalent Database Models (Advantages of a database over flat files)
Previous Year Four Overview Grant Budget Resources This presentation allows you to:  review the overall expectations for Focus Schools, as outlined in.
Agenda Common terms used in the software of data warehousing and what they mean. Difference between a database and a data warehouse - the difference in.
BUSINESS INTELLIGENCE/DATA INTEGRATION/ETL/INTEGRATION AN INTRODUCTION Presented by: Gautam Sinha.
Web Database Design Session 6 and 7 Matakuliah: Web Database Tahun: 2008.
ESCWA SDMX Workshop Session: Role in the Statistical Lifecycle and Relationship with DDI (Data Documentation Initiative)
NCES Forum July 2010 Kathy Gosa Kansas State Department of Education Using Forum Products to Establish a Solid SLDS Framework.
Higher Education Policy Conference Friday, August 11 th 2011 Common Education Data Standards (CEDS): What, Why, and How?
Using CEDS CEDS provides: Common, Voluntary Vocabulary A Robust & Expanding Common, Voluntary Vocabulary drawn from existing sources Tools & Models Powerful.
Margaret Heritage, CRESST Raymond Yeagley, NWEA. National Forum on Education Statistics  Mission: improve the quality, usefulness, timeliness, and comparability.
Presented by: Kathy Gosa Andrea Hall Kansas State Department of Education 26 th Annual Management Information Systems (MIS) Conference February 14, 2013.
Initial Research Findings from Arkansas’ Statewide Longitudinal Data System: Using Standards-Based Research to Solve Real Education Problems Jake Walker,
CEDS Standard Update.
2012 MIS Conference: The Return on Investment From Implementing Common Data Standards Kathy Gosa Shawn Bay Adam Miller Photos are stock, release for web.
Best Practices for Data Warehousing. 2 Agenda – Best Practices for DW-BI Best Practices in Data Modeling Best Practices in ETL Best Practices in Reporting.
6. Implications for Analysis: Data Content. 1 Prerequisites Recommended modules to complete before viewing this module  1. Introduction to the NLTS2.
Eric Westfall – Indiana University Jeremy Hanson – Iowa State University Building Applications with the KNS.
Grant Writing Workshop for Research on Adult Education Elizabeth R. Albro National Center for Education Research.
Oregon Feature Code. Oregon File Member Setup Done at the district level Runs the physical file information for the district Shouldn’t be too concerned.
Management Information Systems By Effy Oz & Andy Jones
Hans P. L’Orange State Higher Education Executive Officers October 20, 2009.
The Next Generation of Educational Data Systems SHEEO 2011 Jack Buckley, Ph.D. Commissioner National Center for Education Statistics
Overview A project funded by the US Department of Education Coordinated by the Council of Chief State School Officers An overview of NEDM The National.
Higher Education Policy Conference Common Data Standards: tsup? Higher Education Policy Conference August 12, 2010 John Blegen, State Higher Education.
Building Applications with the KNS. The History of the KNS KFS spent a large amount of development time up front, using the best talent from each of the.
Information Systems & Databases 2.2) Organisation methods.
Database Design and Management CPTG /23/2015Chapter 12 of 38 Functions of a Database Store data Store data School: student records, class schedules,
TSDS PEIMS Submission I Training Joe Perez PEIMS Director Javier Guevara PEIMS Supervisor September 15 & 16, 2015.
 Three-Schema Architecture Three-Schema Architecture  Internal Level Internal Level  Conceptual Level Conceptual Level  External Level External Level.
SLDS P ROGRAM U PDATE J UNE 12, : OO A. M. – 9:00 A. M. Statewide Longitudinal Data Systems (SLDS) Program Florida Department of Education.
P-20 Statewide Longitudinal Data System (SLDS) Update Center for Educational Performance and Information (CEPI)
Massachusetts Tiered System of Supports State Personnel Development Grant National Meeting Fall 2014 Madeline Levine
An Update from WICHE’s Multistate Data Exchange Project NCES Forum July 9, 2012.
Improvement Planning Mischele McManus Infant/Toddler and Family Services Office of Early Childhood Education and Family Services July 20, 2007
What is a data model?. National Education Data Model Mission Statement Create an open framework for education data systems based on current standards.
District Leadership Team Process. Leadership Team Active Coordination FUNCTIONS Implementation support Data-based action plan Coordination Capacity building.
7 Strategies for Extracting, Transforming, and Loading.
Renewable Energy Statistics Keep-on-Track! 1 st Policy Workshop 23 January
Common Education Data Standards (CEDS) and ED Facts …What’s Next Jack Buckley, Commissioner – NCES Ross Santy, Director – ED Fact s U.S. Department of.
State of Michigan’s P-20 Longitudinal Data System and MI School Data Portal Progress.
V 2.1 Version 2.1 School-wide PBIS Tiered Fidelity Inventory.
Creating and submitting Cal-PASS Data files California Partnership for Achieving Student Success.
Kansas Education Longitudinal Data System Update to Kansas Commission on Graduation and Dropout Prevention and Recovery December 2010 Kathy Gosa Director,
Using MI School Data Michigan Association of Secondary School Principals EdCon 2016 Conference- June 28, 2016 Nicholas Armit- MI School Data Portal Manager-
Databases and DBMSs Todd S. Bacastow January 2005.
Early Childhood Data System
Data warehouse and OLAP
Chapter 13 The Data Warehouse
Staff/Curriculum Development Network
Data, Databases, and DBMSs
Entity – Relationship Model
Data Model.
Database Systems Instructor Name: Lecture-3.
Calendar Reporting OAEP Spring Conference 2018
Chapter 2 Database Environment Pearson Education © 2014.
National Center for Higher Education Management Systems (NCHEMS)
David Gilmore & Richard Blevins Senior Consultants April 17th, 2012
Implementing ETL solution for Incremental Data Load in Microsoft SQL Server Ganesh Lohani SR. Data Analyst Lockheed Martin
Presentation transcript:

P20 State Core Logical Data Model September, 2010

Page 2 NEDM k12 State Core and CCSSO P20 State Core Model EXISTING STATE LONGITUDINAL DATA SYSTEM P20 STATE CORE (ODS-EAV-RDS)

Page 3 The P20 State Core Logical Data Model  Developed as part of the Common Data Standards (CDS) adoption work with funding from the Gates Foundation  Based on NCES handbook, NEDM v2.0, SIF v2.4, PESC, SHEEO State of State PS Data Systems report, and Common Data Standards v1.0  Includes early childhood, elementary and secondary, post-secondary, and workforce data (aka P20) and detailed maps to all 657 files states are required to submit to USED  Designed to support dropout early warning intervention systems (DEWIS), positive behavior intervention systems (PBIS) and response to intervention (RTI)  May be maintained and governed as a model by a joint task force of SIFA and PESC on behalf of CCSSO and SHEEO and their member states (to be determined).  Intended for SEAs and to help guide the relationships, business rules, and entity factoring validate state maps to views of a common P-20 SLDS model including:  source files with different and or non-existent start and end dates  complex relationships between organizations  people with multiple roles in multiple organizations including student-teacher linkage

Page 4 Organization SEA/StateREA/RegionLEA/DistrictSchoolGradeSection Each level of an educational system share common attributes, or data points, that allow us to represent all levels as ‘Organizations’ without losing the business relationship. All can be represented as Organizations Directory - the core of the core, Org-Org Relationships

Page 5 Johnny… is a K12 Student Person Roles K12 Student PS Student TeacherPrincipalParent Each person shares common attributes, or data points, that allow us to represent all levels as ‘Persons.’ Each Person has one or more ‘roles.’ Jane… is a PS Student is a Parent of Johnny is a K12 Teacher People and Roles, the Person – Org Relationship

Page 6 Operational Data Store Organization Person Organization Relationship Person The Person Organization Relationships

Page 7 ODS: Operational Data Store  ODS represents the most current data that the State has  ODS includes the most current view of some historical data (such as prior assessment data and enrollment records)  ODS is a relational database  A “record” is added for each Person.Org Relationship change event in the system.  Other updates to entity.attributes edit records in ODS and update in EAV

Page 8 ODS – Conceptual Model

Page 9 ODS – Physical View of Logical Model (Partial)

Page 10 ODS – Physical View of Logical Model (Full)

Page 11 ODS – Organization

Page 12 ODS – Organization Indicators and Statistics

Page 13 ODS – Person

Page 14 ODS – Person [K12 Student]

Page 15 ODS – Person [K12 Staff]

Page 16 ODS – Location

Page 17 ODS – Assessment [K12 – SIF]

Page 18 ODS – Learning Standards [K12-SIF]

Page 19 ODS – Transcript [K12 SIF]

Page 20 ODS – Person-Org [K12 Student.Enrollment]

Page 21 ODS – Person-Org [K12 Student.Program]

Page 22 EAV: Entity Attribute Value  EAV is the auditing schema for ODS  All ODS data manipulation operations result in or are caused by an EAV record  EAV is a “no edit” database. Records are added, not edited.  A record is added for each change in Entity.Attribute value

Page 23 EAV: Logical Model

Page 24 RDS: Reporting Data Store  The RDS is a view of the ODS as of a specific date  The RDS can be an unchanging snapshot or can remain synchronized to changes in the ODS  The RDS contains both granular and derived /aggregated attributes to support reporting  The RDS is more of a “flat” “star schema” focused on facts of people and organization as of a specific dates

Page 25 ODSRDS ODS data is transformed and copied into RDS, time-stamping the data to allow that dataset to represent a specific point in time. The ODS populates each RDS

Page 26 Each RDS represents a particular “As of” Date Prior YearOct 1Current RDS Objects Attendance by District Metric Assessment Metric Student Race by School Metric And all additional reporting objects… RDS Objects Attendance by District Metric Assessment MetricStudent Race by School Metric And all additional reporting objects… RDS Objects Attendance by District Metric Assessment MetricStudent Race by School Metric And all additional reporting objects…

Page 27 K12 Official Reporting Data Store (RDS) - Logical

Page 28 Tying everything in the model together, “Data Set”.

Page 29 The model is built on PCG’s metadata methodology

Page 30 ETL Data Model Validation Metadata Policies Reporting (Outputs) Reporting (Outputs) Extensibility Data Sources Usage Scenarios 17 The model addresses the complete SLDS system cycle

Page 31 Inman DW 2.0 – The Importance of Metadata