The Power of Queries and Rules in Slate Theresa Jordan & Jessica Oppen University of Colorado Boulder

Background The University of Colorado Boulder adopted Slate (Technolutions) as an application system in 2017. We have 4 instances of Slate on our campus—Undergrad, Grad, Leeds School of Business, and Continuing Education. Not only is it our application system, but we do all processing in Slate as well. Data integrates to Oracle PeopleSoft Campus Solutions daily. We rely heavily on both queries and rules to drive our processes. Jessica: Not sure the experience level of people in the room. We’re going into our 3rd year, so some of you may have much more experience than we do. We just wanted to show you some of the things we’re using queries and rules for in case it gives you any food for thought.

Query functions in admissions Driving processes Our processors run queries daily to identify newly received files that need to be processed. They also run other queries to identify newly received transcripts for files that have already been processed. Communications Our marketing and communications team use queries to identify different populations for different comm streams. Quality control Queries are incredibly flexible and allow us to query for errors on an ongoing or ad hoc basis. Jessica

Batch updating using queries You can use queries to do batch updates instead of updating records manually & individually: Add, update, or clear out field values (e.g. scholarship assignment) Add or remove checklist items. Move batches of files into or out of bins (e.g. at the end of the cycle we remove all files from the bin structure). Mass assign a certain decision. Jessica

Query and rule mechanics Query base – the top level type of query or rule, which controls the type of information you can filter on. Prospects (a person record), Applications (a person record with an app), Forms, Organizations (school, etc.), Relationships, etc. Filter – any custom or Slate-provided field that can be used to narrow your population (e.g. Sex = female). Exports – the columns you would like to see in your query output (e.g. term, major, decision, etc.) Exclusivity groups – a way to bundle a set of rules together and prioritize rules to run in a particular order. Formulas – allows creation of a new value based on values from other exports (fields) without having to know SQL. Caveat: Slate has just fundamentally changed their query design to make them more powerful but perhaps less intuitive. It will be a learning experience for all of us! Jessica

Scheduled Queries for Data Integration We use multiple scheduled queries for exporting data out of Slate to our system of record. Query results are placed on the Slate SFTP server for automated pickup from our legacy system. One example is: Application data export – run 2x a day Mon-Sat A setting in the query sweeps up all applications that meet the criteria and have not been picked up in a previous run of the query. Theresa

To Prevent Duplicates Edit Properties Execution Option – Retrieve only the new records since query was last run. Create a new query for the next app cycle since our cycles overlap. Theresa: Recently started setting interactions as flags that can be used as filter criteria to select out only the new records. Example – Deposit Waiver

Theresa: This shows our filter criteria for our application export query.

Snippet of data exported Theresa

Schedule Export Configuration Another scheduled job triggered from our legacy system picks up the file on the SLATE SFTP server. The file is then processed with a set of batch jobs within our CU-SIS for adding the new applications. Theresa: How our app export query is scheduled. Runs twice a day. Once at night and once in the afternoon 6 days a week.

Rule functions in admissions Rules are similar to queries but don’t have to be run manually, and are used to automate processes. We use rules to: Update certain fields or tags in Slate based on answers to questions in the application. Add or remove checklist items based on certain criteria (e.g. add a personal statement requirement for transfers). Calculate a predicted GPA for an incoming first year student. Move files to the First Read bin when they’ve been fully processed. Jessica

An example of a simple rule: Waive app fee Any freshman who requests a financially-based fee waiver on the Common App is granted an app fee waiver. We built a field to indicate when an app fee is waived for tracking purposes, so we created a rule to automatically set the ‘App fee waiver approved’ field to yes if the applicant chooses any financially- based fee waiver on the Common App. This rule saves us time that was previously spent manually querying on this information and manually updating the field. Jessica

Exclusivity Groups Name the group Assign a priority to each rule in the group with 1 being first Control when and what happens to the records selected in your rule. Create dependencies for a group of rules that are acting on the same group of records Jessica

First Generation Use a rule to create and store a value based on other field values in Slate Combines three “queries” joined by an exclusivity group We use first generation in some of our scholarship awarding criteria. It’s based on the parents’ highest education level. The rule automatically sets the field to yes based on the highest education level parent 1 and/or parent 2 loaded from Common App or the Slate transfer application. This rule only runs once for a record when the application is submitted Theresa

Theresa

Removes parents with no education data Priority: 1 Remove any students who have parent 1 and parent 2 highest education not indicated Theresa

Removes parents with higher education Priority: 2 Remove any students who have parent 1 or parent 2 with a Bachelor’s or higher degree Theresa

Flags parents with less education Priority: 3 Update the flag to yes if parent 1 or parent 2 highest education is less than the level of a Bachelor degree. Theresa

ACT Maximum Composite Example: Use a rule to do mathematical calculations Look at all verified test administrations Choose the highest score for each of the components Average the highest English, Math, Reading, Sci Reasoning for Composite Uses a formula for the calculation Example: round((@ACTMaxEnglish + @ACTMaxMath+ @ACTMaxReading + @ACTMaxScience)/4,0) Theresa

One rule calculation Only one rule is needed for this calculation Filters for records that contain all verified ACT component scores Theresa

Action Theresa: Action is where to configure what the rule will be doing.

Formula Parts of a Formula Change the name of the export. The new name will be used in the formula. Use @exportname for formula Theresa: Need to set up an export for each value used in the formula

Complex formulas Calculate a predicted grade point average depending on the college applied to Utilizes translation codes SQL logic Theresa: Use translation codes for: multiplier values and subtractor values dependent on the student’s college If college is Engineering then multiply by x and or subtract by y

cast(round((select max(x.[value]) from (values( (@hs_gpa * try_convert(real, @hs_gpa_multiplier)) + (@act_eng* try_convert(real, @act_eng_multiplier)) + (@act_math* try_convert(real, @act_math_multiplier)) - try_convert(real, @act_subtractor)), ((@hs_gpa * try_convert(real, @hs_gpa_multiplier)) + (try_convert(real, (select max(x.[value]) from (values (@satr_read), (@sati_cr)) x ([value]))) * try_convert(real, @sat_eng_multiplier)) + (try_convert(real, (select max(x.[value]) from (values (@satr_m), (@sati_m)) x ([value]))) * try_convert(real, @sat_math_multiplier)) - try_convert(real, @sat_subtractor))) x ([value])),2) as decimal (5,3)) Theresa

PGPA – 2 rules in an exclusivity group Theresa

Resets the field to blank Theresa: If a student is missing either test scores or high school gpa

Replaces PGPA value from Formula Theresa

Formula Theresa

Tips & Tricks Use ‘active period’ in your rules so you don’t have to update them every year. Use exclusivity groups whenever possible for optimum system performance. Queries are automatically saved as changes are made, but rules aren’t!!!!! Use check logic to make sure your queries or rules are pulling the correct records. Use the existence export to turn a filter into an export. Pinned filters (in both senses) Jessica: Check Logic is also handy for troubleshooting errors.

Questions? Theresa Jordan theresa.jordan@colorado.edu Jessica Oppen jessica.oppen@colorado.edu Jessica