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API & Performance+

Randall.S.394

Is there API access Performance+ functionality ?

What I am wondering is

Is it possible to drive P+ via remote control. The idea would be to have multiple data sources only 1 of which is D2L and use these other data sources to filter the data presented to the built-in data tools in P+ and then read the results directly. Essentially using the P+ engine but applying constraints generated by another data source and vice versa.

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Comments

Renee.J.194

I think what we do is what you are talking about. We host our own data lake. We collect Brightspace datasets. We use differential upserts for most updates, occasionally we have to go back to fulls. We use the Brightspace API and automate our calls.

Our data lake has other data sources besides, including our SIS, our online syllabus vendor, and other institution-specific data related to courses and students. We write reports joining data that is relevant to our needs. One of several ways we make our reports available is through PowerBI.

Here is where you can learn about the calls. https://docs.valence.desire2learn.com/http-scopestable.html

datasets
	`datasets:bds:read`
	`/d2l/api/lp/(version)/datasets/bds [GET]`
	`/d2l/api/lp/(version)/datasets/bds/(schemaId)/extracts [GET]`
	`/d2l/api/lp/(version)/datasets/bds/(schemaId)/plugins/(pluginId)/extracts [GET]`
	`/d2l/api/lp/(version)/datasets/bds/(schemaId)/plugins/(pluginId)/extracts/(extractId) [GET]`

If you do not have such a data lake set up already, Performance+ would let you host other data with them. I don't know any of the details.

Ian.P.710

So there is currently no api access to the Performance +, with the April 2025 release and having signed the addendum contract then there is an option within Analytics Builder to connect to external data sources

Analytics Builder now supports the following external data sources:

File upload
Salesforce
MySQL
PostgreSQL
ORACLE
SQL Server
Aurora
MariaDB
Presto
Spark
Teradata
Snowflake
Google BigQuery
Timestream
Exasol
Databricks
Trino
Starburst
GitHub
Jira
ServiceNow
Adobe Analytics

Supported file formats for uploads include CSV, TSV, ELF, CLF, JSON, and XLSX file types.

and combine that external data with Brightspace Dataset data to generate visualizations.

The other option is as posted above create your own data lake by downloading the applicable brightspace datasets and adding them to your own database along with data from other sources.

If needed you could also combine the data from the brightspace api's and add the data from the responses into your own database however unless you have a specific time sensitive use case then the datasets are a better option.

Randall.S.394

Thanks. This helps. We also already have a data lake set up or at least a representation of the BDS data model in a DBMS. It is mostly used to produce reports that aren't possible with the ADS. We will have to see what its future will be once we get P+.