1. LET’S GATHER THE DATA
AKIFUMI YAMAMOTO| OMNIUPDATE

2. Requirements for this Workshop
LET’S MAKE SURE YOU’RE IN THE RIGHT PLACE
Knowledge of basic programming concepts
Conditionals (if else), loops (for, foreach), and functions
Knowledge of XML and JSON data formats
Familiar with XSLT syntax
Basic understanding of XSLT Elements
Basic understanding of XPath axes and expressions
Basic understanding of XPath functions

3. Workshop Overview Production Server Aggregation Aggregate on publish
Aggregate on page-load
OU Campus Aggregation via XSL
Make fn:doc() calls
Utilize the OU Campus Tag API

4. Production Server Aggregation
Possible Pros
Possible Cons
Guarantees that only published data is aggregated
Each file must be published to the production environment
Server-side aggregation is usually faster
Production server can be cluttered with data files
Have the option to aggregate on page-load, which means no republish required to update data
Both data and content must be ready for publish to update either data or content
May need to implement a caching functionality if aggregating on page-load

5. OU Campus Aggregation Possible Pros Possible Cons
Cleaner production environment
Harder to ensure work-in-progress data is not aggregated
Data and content can have varying publish timing
OU Campus aggregation can be a little slow
Can leverage OU Tags to find necessary files easily
A publish is required every time a data point is updated
Publishes a single file, so caching functionality is likely unnecessary

6. OU Campus Aggregation Dev Process
PCF Development
XSL for individual data output
Aggregate all data pages

7. OU Campus Aggregation Demo
Manually choose the files to aggregate
Users create a list of files that are meant to be aggregated
Recursively aggregate all data files in a folder tree
Recursively call the fn:doc() function
Use Tag Management to find files with specific tags
Find tagged data files using the Tag API

8. THANK YOU!
PLEASE SHARE YOUR FEEDBACK: #OUTC19