Configuring dbt Crosswalks in EDU#
This document provides brief descriptions and usage examples for the available dbt seed crosswalks in the EDU framework.
For an introduction to dbt seeds, see dbt's article. To add or edit a crosswalk, go to /seeds/ within your dbt project directory.
In EDU, we use dbt seeds to crosswalk values from source data to analytically-useful values. Most commonly, this means mapping Ed-Fi descriptor values to their analytic interpretations, e.g. 'uri://ed-fi.org/In Attendance' -> is_absent = 0 (as seen here). Most EDU crosswalks come with default values configured, but these should be updated by the implementation to ensure completeness, and maintained over time.
The default set of EDU seed crosswalks is found in the edu_project_template and is kept up to date with EDU. These updates are not automatically applied to implementations - it is the job of the implementation repository maintainer to keep up-to-date with EDU crosswalk additions. If the crosswalk addition is required for a new breaking change to the code, that breaking change will align with a breaking release and will be communicatede via release notes.
During initial project setup, you should look through the default values and compare to the descriptors from your implementation of Ed-Fi to determine if new values need to be configured. For many implementations, the Attendance, Calendar, and Students crosswalks are highest priority to check. In some cases, EDU has tests built-in to check for values that are missing configuration.
Assessments#
assessments/xwalk_student_assessment_subject#
Assign subject to a student assessment record based on a score result. This is necessary when an assessment identifier does not map to a single subject.
assessments/xwalk_assessment_scores#
Normalize student assessment score names across assessments to a determined set of scores to be used as columns in fct_student_assessment
assessments/xwalk_objective_assessment_scores#
Normalize student objective assessment score names across assessments to a determined set of scores to be used as columns in fct_student_objective_assessment
Attendance#
xwalk_attendance_events.csv#
Give attendanceEventDescriptors an analytic interpretation for whether a student is absent or not.
metrics_thresholds/absentee_categories.csv#
Assign thresholds to arbitrary number of categories for absenteeism.
Calendars#
xwalk_calendar_events.csv#
Determine which calendarEventDescriptors are and are not school days.
Course#
xwalk_course_level_characteristics.csv#
Give course characteristics an analytic interpretation in standard categories for grouping of courses.
xwalk_id_types_course.csv#
Assign types of course codes; common are local and state.
xwalk_letter_grades.csv#
Give letter grades an analytic interpretation about whether to include in GPA calculations, GPA points, D/F categorization, and sort orders.
Discipline#
xwalk_discipline_actions.csv#
Assign severity order and indicator (e.g. in-school, out-of-school, expulsion, minor) to discipline actions.
xwalk_disicpline_behaviors.csv#
Assign severity order to behaviors.
Education Organizations#
xwalk_id_types_ed_org.csv#
Assign types of education organization IDs; common are state, local, and NCES codes.
Networks#
xwalk_network_association_types.csv#
Assign network_purpose values to a named association, to pull into dim_school or dim_lea as a new foreign key, e.g. k_network__region generated by this configuration:
Parents/Contacts#
xwalk_parent_email_types.csv#
Assign ElectronicMailTypeDescriptor for parents to a normalized name.
xwalk_parent_phone_number_types.csv#
Assign TelephoneNumberTypeDescriptor for parents to a normalized name.
Staff#
xwalk_id_types_staff.csv#
Assign types of educator IDs, common are state and district / local.
Students#
xwalk_grade_levels.csv#
Assign integer values (for sorting or displays) to each grade level.
xwalk_id_types_student.csv#
Assign types of student IDs; common are state and district / local.
student/xwalk_student_characteristics.csv#
Standardize student characteristics into binary indicators.
student/xwalk_student_indicators.csv#
Map student indicators from studentEducationOrganizationAssociations to analytically useful indicator columns in dim_student.
student/xwalk_student_programs.csv#
Map student program types from studentProgramAssociations to analytically useful indicator columns in dim_student. Set is_{agg_type} to true to create the associated columsn with rules defined in bld_ef3__student_programs.
Example configuration:
program_name,indicator_name,is_active,is_annual,is_ever
IEP,IEP,true,true,true
ALP,gifted,true,true,true
504 Plan,504,true,true,true
ELL,ELL,true,true,true
student/xwalk_subgroup_category_display_names.csv#
Assign display names for subgroup categories generated by dim_subgroup.
students/xwalk_subgroup_value_display_names.csv#
Assign display names for subgroup values generated by dim_subgroup.