Before learning any topic, I believe it is always better to first understand these three simple questions in very very smple ways:
What? → Why? → How?
- What is it? — Understand the concept and what it actually means.
- In previous post, we already undestand What is Data Cloud?
- Why do we need it? — Understand the problem it solves and its real-world value.
- In previous post, we already undestand Why do we need it?
- How does it work? — Understand how to implement or use it in practice.
- Now we will learn very simple way How to implement it?
After this POC we will get a very good understanding of Data Clould and then we can explorer more by ourself by mulitiple Data Cloud realted lerning documents/trainings.
POC: Check the below diagram and this will be our 1st Data Clould Project in very simple way.
🎯 Project: Identify ABC Company's High-End Customers
🏢 Business Scenario
Let's say ABC Company sells products through two different platforms:
1️⃣ Physical Store
Customers purchase products from ABC's physical stores.
Their sales/order information is maintained in Excel.
2️⃣ Online Website
Customers purchase products from ABC's website.
Their sales/order information is stored in Salesforce.
The problem is: ABC doesn't have one complete view of a customer's total purchases.
For example:
| Customer | Physical Store | Online Website | Total Purchase |
|---|---|---|---|
| Rahul | ₹10,000 | ₹15,000 | ₹25,000 |
| Amit | ₹2,000 | ₹15,000 | ₹17,000 |
| Priya | ₹1,000 | ₹5,000 | ₹6,000 |
Rahul may look like a ₹15,000/- customer in Salesforce, but when his physical-store purchases are added, ABC discovers that he has actually purchased ₹25,000 worth of products and he is a High End Custoper for ABC Company.
🏢 Solution
Now we will use Salesforce DATA Cloud Platform as sohown in below diagram and then perform the below action items like we learn in previould post.
1. External Data Sources (Salesforce, Excel).
2. Establish connections from Data Cloud to external Salesforce.
3. Ingest data by creating Data Streams both from external Salesforce (using connecctor) and from Excel (using file upload option).
4. Data Lake Objects (Auto + Manual based on our needs).
5. Use of Data Explorer / Query Editor to check/validate the data.
6. Data Transforms (Join the mulitple DLOs created from 2 different external sources in a single Talbe or single DLO).
7. Organize data into a meaningful structure by mapping with proper DMOs.
8. Identity Resolution - removed dulicate customer or in other teram identify the unique customer.
9. Calculated Insights - group the customer based on the total purchase amount.
10. Segmenting customers based on the total purchase amout.
11. Activation - Send data/audiences.
