In this comprehensive tutorial, we're set to explore the creation of an Insights data model, employing the customizable insights capability offered by Data Distiller. Through a detailed step-by-step demo, I aim to improve your data workflows by adapting insights data models to meet your unique requirements.
Step 1: Introduction to Insights Data Model Creation
The purpose here is to create an insights data model that can handle various KPIs and trends over time, leveraging the powerful capabilities of Data Distiller. Adobe Real-Time Customer Data Platform offers a range of out-of-the-box data models, but the focus will be on how to customize these to fit our specific requirements.
Step 2: Creating the Data Model
First, it's essential to create the necessary database, schema, and tables that will store information. Then give the insights data model a user-friendly name which will be displayed in the Dashboard section.
Step 3: Populating the Model with Historical Data
The next step is to populate the model with historical data either by creating a dataset or from any existing dataset based on your needs. After preparing the dataset, use Data Distiller to transfer this data into the newly created Insights model from Step 2.
Step 4: Scheduling Regular Updates
To keep the model up to date, it's crucial to schedule a query that updates the insights model daily. This process involves accessing system datasets such as profile export snapshots, aggregating counts, and/or applying transformations before updating the insights model.
Step 5: Creating a Dashboard
Finally, to visualize the loyalty status data effectively, create a dashboard. This step is straightforward and showcases the data in an easily digestible format.
Optional: Integrating with BI Tools
Lastly, if you are already using a BI tool of choice for example Power BI, then point to the same insights data model through Query Service.
Here is a detailed blog I wrote about integrating Power BI: Link
This demo is designed to provide a solid foundation for your insights data workflows, empowering you to customize and enhance insights models to meet your specific needs.
Author: @annamalai