The Credit hours are calculated based on the host institution of the course, and FTE, course enrollment, and students' demographic are based on students' home institution. Below is the SQL code for the semantic model for Power BI.
select
x.strm,
x.institution,
x.um_dist_class,
x.um_class_dlv_mode,
x.um_in_out,
x.um_region,
x.um_site_category,
x.um_location_descr,
x.um_student_level,
x.um_stud_level_sort,
SUM(x.headcount),
SUM(x.FTE) as FTE,
SUM(x.Credits)
from
(select
b.strm,
b.institution,
b.um_dist_class,
b.um_class_dlv_mode,
a.um_in_out,
b.um_region,
b.um_site_category,
b.um_location_descr,
a.um_student_level,
a.um_stud_level_sort,
COUNT(Distinct A.EMPLID) as headcount,
sum(B.UNT_PRGRSS / A.UM_FTE_DIVISOR) as FTE,
0 as Credits
FROM sysadm.PS_UM_STD_ENR_C_VW B
join sysadm.PS_UM_STUD_CENS_VW A on A.EMPLID = B.EMPLID AND A.INSTITUTION = B.INSTITUTION AND A.STRM = B.STRM
WHERE B.STRM >= 1910
GROUP BY b.strm, b.institution, b.um_dist_class, b.um_class_dlv_mode, a.um_in_out, b.um_region, b.um_site_category, b.um_location_descr, a.um_student_level, a.um_stud_level_sort
union
select
b1.strm,
b1.um_inst_host,
b1.um_dist_class,
b1.um_class_dlv_mode,
a1.um_in_out,
b1.um_region,
b1.um_site_category,
b1.um_location_descr,
a1.um_student_level,
a1.um_stud_level_sort,
0,
0,
sum(B1.UNT_PRGRSS) as Credits
FROM sysadm.PS_UM_STD_ENR_C_VW B1
join sysadm.PS_UM_STUD_CENS_VW A1 on A1.EMPLID = B1.EMPLID AND A1.INSTITUTION = B1.INSTITUTION AND A1.STRM = B1.STRM
WHERE B1.STRM >= 1910
GROUP BY b1.strm, b1.um_inst_host, b1.um_dist_class, b1.um_class_dlv_mode, a1.um_in_out, b1.um_region,
b1.um_site_category, b1.um_location_descr, a1.um_student_level, a1.um_stud_level_sort) x
GROUP BY
x.strm,
x.institution,
x.um_dist_class,
x.um_class_dlv_mode,
x.um_in_out,
x.um_region,
x.um_site_category,
x.um_location_descr,
x.um_student_level,
x.um_stud_level_sort