Welcome to this blog post. In this post, we will see what is big query and how to integrate Pega with big query with an use case
Pega introduced BigQuery dataset in 24.2 by which we can connect to Google's BigQuery Tables and Views.
Let's start with understanding what is BigQuery
What is Google BigQuery?
So, BigQuery is a data warehouse which handles very large amount of data mainly used for data analytics.
So, A question comes into our mind. In what cases we integrate Pega and BigQuery - There might be use cases where Pega needs the analytical data to be Ingested to make decisions in Customer Decision Hub or Case management
Lets talk about a simple use case
- An organization maintains Customer's Credit Score data in a table in BigQuery which will be refreshed daily after the calculations
- Pega CDH needs the Customer Credit Score information to make NBA decisions
- So, we decided to use BigQuery dataset to connect to that table and use Data Jobs to Ingest the data daily
I have made a video for the detailed understanding of BigQuery and Its Integration with Pega.
I hope you followed the process mentioned in the video and able to do the use case in cloud instances. If you have any questions, Please reach me out on LinkedIn - Syam Kumar Muvvala
Please note that, for every table you want to Integrate, you need a separate BigQuery Instance created inside Pega
Assignment:
Let's say Pega also needs Customer model scores to be Ingested from BigQuery.
Create a model score table in BigQuery and add two columns
- CustomerID
- ExternalModelScore
Create required data model, table, dataset in Pega
Create a BigQuery Instance in Pega and followed by data set creation and Data Job creation
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