A University Step-by-Step Guide to Data Cloud Unification

Fragmented Student Data

Meet Amina Patel, a second year student at Solution Junkies School of IT, studying Software Engineering.

Over the past term, Amina has interacted with the university in many ways, but her data is scattered across multiple, disconnected systems.

What Data Do We Have on Amina?

Over the past term, Amina's data has been captured in various silos.

The Impact of No Single Source of Truth

This data fragmentation at the SJ School of IT leads to significant challenges.

• Incomplete Picture: Lecturers, personal tutors, and student services staff only see fragments of Amina’s situation. For example, the IT helpdesk sees her support ticket volume but has no context about her academic performance or engagement levels.
• Disconnected Student Experience: Amina receives multiple messages from different departments. These messages are sometimes repetitive and sometimes irrelevant because the systems aren’t speaking to each other.
• Missed Signals: Crucially, nobody has connected the dots between Amina’s missed classes, support requests, and interest in well-being resources. These are all indicators that she may be struggling.
• Limited Personalisation: Without unified data, it’s nearly impossible to offer timely, relevant support, such as recommending academic mentoring or mental health check-ins, before issues escalate.

The Solution: Building a Unified View with Data Cloud

To address these challenges for Amina and their students, the SJ School of IT embarked on a data unification journey with Data Cloud. We were their trusted implementation partner in this process, which unfolded in three key stages.

1. Ingest

The first step is to get all of Amina's scattered data flowing into Data Cloud.

a. Create Data Streams

For each source system (e.g., LMS, Helpdesk, Events App, Student Finance), we configure data streams using Salesforce’s native connectors or external APIs. These create dedicated flows for each data source. 

b. Define Data Lake Objects (DLOs)

Each data stream populates a Data Lake Object (DLO). A DLO is essentially a raw, structured representation of the data from its source. For Amina, this includes fields like:

At this stage, all of Amina's touch points across the university exist as real-time data streams feeding into DLOs within Data Cloud. The data isn't mapped or cleaned yet, but it's all accessible.

Now, let’s harmonise it!

2. Harmonise

Now that all of Amina’s raw data is flowing into Data Cloud via Data Lake Objects (DLOs), it’s time to standardise and align it.

a. Map to the Canonical Data Model

We map each DLO to Salesforce’s Standard Data Model (sometimes called the Canonical Model).

This turns messy, inconsistent field names into clean, consistent fields across all systems.

This process creates Data Model Objects (DMOs). These are harmonised versions of the data, ready to be used across the platform.

b. Clean, Flatten and Enrich

We then perform transformations to prepare the data for unification:

• Flatten relationships (e.g., convert complex structures (like nested JSON) into simpler formats. 
• Standardise formats (e.g., date of birth formats, name capitalisation)
• Enrich records with calculated fields (e.g., number of support tickets in the last 30 days)

Now, Amina's data is harmonised, clean, consistent, and mapped to a standard model. However, a single, unified profile for her doesn't exist yet. Let’s get to it.

3. Unify

Now that Amina’s data is harmonised and structured in Data Model Objects (DMOs), it’s time to build a single, unified view of her across all systems.

Identity Resolution and Unified Profile Creation

We create a Unified Individual (Student) Profile using identity resolution rules in Salesforce Data Cloud.

If a Helpdesk record says "A. Patel" and the LMS says "Amina Patel" and they share the same email or ID we link them.

Once matched, Data Cloud builds a Unified Student Profile that combines all of Amina’s touchpoints:

All this information is now in one place, tied directly to Amina, and updated in real-time. By undertaking this journey of ingesting, harmonising, and unifying student data with Data Cloud, SJ School of IT can move from fragmented information to a powerful, student-centric approach. Now, all the hard work is done!

Join us next time to see what the SJ School of IT can do with this unified student profile!