DAX Training for Improved Decision Making

DAX Overview
(Module 1)
Improving Decision Making
with Data

Module 1: Agenda
• What is DAX?
• Why use DAX?
• How does DAX work?
• What data is in DAX?
• What reports are in DAX?

Purpose
The Data Access and Exchange (DAX) System is a system
that facilitates the Alabama Community College
System in the collection and distribution of accurate
data in an organized and timely manner
DAX is a data mining and data reporting
tool.

History of DAX
• Initial discussions - 2002
• Formation of DAX Steering Committee - 2004
• Data/file definitions - 2004-2006
• Initial development - 2007
• Beta testing - 2008
• Full implementation of collection - January
2009 (Fall 2008 data)
• Migration from relational data structure to
analytical data structure – 2013 to present

Initial Goals
• Promote sharing of aggregated data
• Promote exchange of information
• Standardize reporting processes (ACHE,
IPEDS, etc.)
• Provide reliable, valid, real-time data to
decision makers
• Create a system-wide data warehouse

Why use DAX instead of internal data?
• DAX data is “frozen” each term. Institution data may
change. The frozen data allows better benchmarking.
• Reports are vetted by functional leaders as “best
practices.”
• This is the data that is reported to ACHE, NCES, and
OVAE.
• Visualize state-wide trends and connect
with colleagues of similar nature.
• Understand your institution in context of
the system.

Changing the culture of how to use data
Culture of Assessment Culture of Performance
Data collected end of term
or year
Data collected quarterly,
monthly, weekly
Data is a means unto itself Data is a means to an end
Data used for accreditation
or end-of-year reports
Data used for decision-
making and improvements
Many measures Few key measures
Aligned with professional
interests
Aligned with strategic
priorities
Reactive / Inactive Proactive
VS

The Components of DAX
• Data Collection System
• The Validation Engine
• Reporting Website (https://dax.accs.edu)
• Data Management Website (https://ddm.accs.edu)

Data Collection
• Colleges enter data into local administrative
systems
• Administrative systems generate files daily
• Every night, DAX picks up data from
colleges
DPE has access to fresh data daily

Data Validation
• DAX processes files against validation
routines
• DAX generates error reports
• Once a week, DAX sends error e-mails for
each file to persons as designated by each
college (weekly on Sunday)
• After mid-term, President of institution
gets a weekly error email on Tuesday

Data Validation
• Validated for sanity
• Validated for conformance to Board Policy
and Guidelines
• Validated for conformance to other business
rules
Goal of accurate and valid data in a timely
manner met.

DATA Warehouse
A central repository of “loosely related” databases.
Non-CreditCredit Adult Ed. GED Testing ATN Human
Resources

Data Repository
• Credit Student Data
(including Schedule
data)
• Human Resources
(Personnel) Data
• Financial Data
• Adult Ed
• GED
• Non-Credit Activity
Available Databases Databases to be Added

Personnel Data – 3 Tables
• PER – contains demographic, descriptive,
and summary data on all personnel paid by
the institution.
• JOBS – contains details about each job
and/or contract of an employee.
• JOBACCTS – contains accounting
information for each job and/or contract for
personnel paid by the institution.

Student Data – 9 Tables
• STU – contains demographic and academic
information on all credit students enrolled
in the reporting term. There is only one
record per student.
• SPECPOP - contains a separate record for
each special population associated with a
student enrolled for the reporting term.

• ASSESS – contains pre-placement scores
for registered students
• AWARD – contains awards conferred by
institution to students
• FINAID - contains a list of all financial aid
awarded to registered students for the
reporting term.

Schedule Files
• SCHMST - contains detailed information
for each credit course section in which
students are enrolled at the institution for
the reporting term.
• SCHDET - contains a record of every
meeting day and time combination for each
credit course section in which enrollment
exists for the reporting term.

• SCHINS - contains all instructors teaching
any portion of a credit course section for
the reporting term.
• REG - contains all credit courses for which
a student has enrolled for the reporting
term. There will be one entry per student
per enrolled course. The table will include
the grade earned for each course.

DOCUMENTATION AND VALIDATION DATA
Hands On Demonstration

PREBUILT REPORTS AVAILABLE
DEMO

Questions and Comments
Randy Bowman
Acting Director of the Information Technology, Data, Planning and
Research Division
(334) 293-4542
randy.bowman@dpe.edu

DAX Operations
(Module 2)
Best Practices to Improving Data
Accuracy and Timeliness

Module 2: Agenda
• User Types and Roles
• Error Emails
• Interpreting Error Reports
• Reporting Deadlines
• Affidavit Signing

User Types and Roles
• President
• DAX Data Verifier
• Data Maintenance
• Data Access
• Report Detail Access
• Report Access
• Error Email Access

Error Emails
• Emails sent each Monday at 7:00 AM
• Click on link in email
• Enter the Pickup Code
• Print the list of validation errors

Error Report
• My Data Overview
• Click a table that has errors to see table
details
• Click Errors button in table footer
– Select a row
– Read the error in the sub-table
– Use definitions to determine best course of
action
• Alternatively, click Printable View of All

ERROR REPORTS AND INTERPRETATION
Hands on Demonstration

Reporting Schedule
• Data may be used throughout the term, but labeled “as of <date>”
• Important to keep errors to a minimum at all times, not just end of
term
• Term data is collected for terms using the following dates:
– Fall term data August 15 – January 15
– Spring term data January 1 – June 30
– Summer term data May 1 – September 15
• Term data is “frozen” (not picked up and processed) when the
affidavit is signed or on the last date of that term’s collection
• Class start and stop dates should fall between:
– Fall term July 1 – December 31
– Spring term December 1 – June 1
– Summer term April 1 – August 30

DAX Affidavit Dates
• DAX Affidavits may be generated and signed
between the following dates:
– Fall term data December 15 – January 15
– Spring term data May 15 – June 30
– Summer term data August 15 – September 15

Affidavit Signing Best Practices
• 3 weeks before due date, all errors should be
cleared.
• 2 weeks before due, generate affidavit begin
verification process.
– Generate Affidavit
– Print copy for each functional user
– Highlight data that functional user should confirm
– Send to functional user with due date of confirmation
– Goal: All data confirmed 1 week prior to due date
• 1 week before date, generate affidavit and route to
President for approval.

DAX Governance
(Module 3)
Improving System-Wide Data
Accountability

Module 3: Agenda
• What is the DAX Steering Committee?
• How are reports added to DAX?
• How are validations added?
• How are differences between local reports
and DAX reports resolved?

DAX Steering Committee
• The DAX Steering Committee is in charge of all DAX functions
including data standards, validations, reports, documentation and
notification of changes to DAX contacts
• DAX Steering Committee Members:
– Mr. Randy Bowman (System Office) - Chair
– Mr. Tim Carter (Gadsden)
– Ms. Jamie Glass (Lawson)
– Mr. Anthony Hardy (Jefferson Davis)
– Ms. Linda Hodges (Enterprise)
– Ms. Angie Stone (Northwest-Shoals)
– Ms. Lisa Stephens (Bevill)
– Ms. Linda McIntosh (Jefferson State)

DAX Steering Committee Goals
• To ensure data provided for reports from the DAX
database is timely and accurate
• To ensure false errors are eliminated from validation
procedures
• To ensure proper communication between ACCS and
Alabama Supercomputer Authority
• To provide training on DAX policies/procedures and usage
• To provide assistance with data definitions and review
reports to be generated from DAX data

DAX Report Process
• A need for a new report is identified
• A mockup of the report is designed
• Data elements needed are determined and
defined for the programmers
• The report specification is scrutinized by the
committee and given to ASA programmers
• Programmers create the report
• Steering Committee vets the results of the
report prior to releasing it

New Validation Rule
• A need for a new rule is identified
• The rule is written in plain English by the
committee
• The rule is pseudo-coded by committee
• The rule specification is scrutinized by the
committee and given to ASA programmers
• Programmers create the rule
• Steering Committee tests the rule

Problem Resolution Process
• Each school has a DAX Primary Contact
• Primary Contacts are single point of contact to the
DAX Steering Committee and the System Office
• E-mail daxhelp@accs.edu for
– Questions/concerns
– Add/remove/change requests to validation codes
– Validation issues

Troubleshooting a report
• Two reasons a DAX report might not match
a locally produced report
1. The “logic” used might be different
2. The data used might be different

DAX Logic Right
&
DAX Data Right
Local Report must be
wrong
DAX Logic Right
&
DAX Data Wrong
Determine root cause
of incorrect data & fix
DAX Logic Wrong
&
DAX Data Right
DAX report will be
fixed
DAX Logic Wrong
&
DAX Data Wrong
DAX report fixed and
root cause of
incorrect data fixed

DAX Reports
(Module 4)
Using the DAX Reports

Module 4: Agenda
• What reports are available in DAX?
• How do I understand what the report
means?
• How can I use these reports to make
decisions?

USING PREBUILT REPORTS AND EXCEL

DAX and Outside Agency
Reporting
(Module 6)
Using the DAX System to complete IPEDS
Surveys, Perkins Reports, and ACHE

Module 6: Agenda
• ACHE Submissions
• IPEDS Surveys
• Using Excel to compare local data to DAX
data

ACHE State Student Database (SSD)
• ACT 96-509 (Alabama Code 16-5-7)
requires reporting of unit record data to
ACHE SSD
• Every term data is pulled from DAX and
submitted to ACHE SSD
• System office “locks” the data
• Institutions are required to confirm the
data

ACHE Graduation Database
• Annual submission of awards granted by student.
• Summer Year 1 – Spring Year 2
• Pulled from DAX Award file for Summer Year 2.
• Should match the IPEDS Completions Survey.
• Best Practice Alert: Run the Award Summary by
Program CIP Code (DAXAWARD-003L) and
IPEDS Completion report and compare totals
during the Summer Term.

IPEDS Surveys – Race & Ethnicity
• Race/Ethnicity Calculation
– Count all Non-Resident/Alien, regardless of
race/ethnicity
– Count all Hispanic ethnicity, regardless of race
– Count for each race
• DAX treats the criteria as 3 different fields

IPEDS Survey/Perkins Report - Gender
• Neither report usually has a place for
“Unknown”
• Must try to capture gender on every student
and faculty member, even if they refuse to
self-identify

IPEDS Surveys - Exclusions
• Exclusions are lists of students/personnel that
were excluded from the DAX Report because
DAX did not have enough data to properly
categorize the person.
• DAX is “smart” enough to realize that the person
needs to be counted, but the missing data prevents
DAX from knowing which part/column the
person is to be reported.
• These people should be reviewed and
appropriately placed in the IPEDS Survey.

Getting Details
• IPEDS Reports – Use “Show Query” and
look for the “Backing Query”
• Perkins Reports – Click the “Get Details”
link above each column

Using Excel to compare detail lists
• Import details from DAX
• Import details from local administrative
system
• Use the MATCH(), ISNA(), and NOT()
functions
• Filter list as appropriate
https://www.youtube.com/watch?v=58RrUXr_SGI

Best Practices
• Run reports DURING the terms which are going to
be included in the report
– This gives you time to see EXCLUSIONS and fix them
before DAX Freeze dates
• Know which data fields are used as “decision”
points and pay careful attention to those
• Start preparing IPEDS and Perkins reports early
• Have a deep understanding of IPEDS Definitions
• Watch the tutorials provided by AIR every year
prior to starting the surveys

Custom Queries in DAX
(Module 5)
Using the DAX Query Page

Module 5: Agenda
• Querying Data (SELECT statement)
• Joining Tables
• Using Functions
• Using subqueries

USING THE QUERY PAGE
BASIC SQL

SQL Resources and Tutorials
• http://www.myassignmenthelp.net/basic-structure-of-an-sql-
query.php
• http://www.firstsql.com/tutor2.htm
• http://www.w3schools.com/sql/
• http://sqlzoo.net/wiki/Main_Page
• https://www.khanacademy.org/computing/computer-
programming/sql

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