Kumaran1987

Prerequisite  1. In All Guidewire xCenters import sample data 2. Create account in Databricks Community edition, In this edition Databricks is Free Step 1: Query H2 tables Step 2: Save Resultsets into CSV files and rename prefix with clm_ Step 3: Upload all these CSV into Databricks Filestore Click Create Table then Below pop up will open and upload all csv files Step 4:   Check it in Catalog--> FileStores --> All Clm_ prefix files are available !! Step 5: Ingested CLM_ csv prefix files now it will be created as delta tables in Databricks as well as migrate to new guidewire raw database PySpark Code has below  import os from pyspark.sql import SparkSession from pyspark.sql.types import IntegerType from pyspark.sql.functions import col # Initialize Spark session (usually pre-initialized in Databricks) spark = SparkSession.builder.appName( "CreateTablesFromCSV" ).getOrCreate() # Define the base path for FileStore base_path = "dbfs:/FileStore/" # Define ...

  Insurance Claim Team Related Fact Dimension table with data mesh Read Full article here  Full Article Introduction In the context of insurance claims, both fact and dimension tables can be managed using different types of Slowly Changing Dimensions (SCDs): 1. SCD Type 1: Overwrites old data with new data. 2. SCD Type 2: Maintains historical data by adding new rows for changes. Example: Dimension Table for Insurance Claims 1. Dimension Table Using SCD Type 1 An SCD Type 1 dimension table for insurance claims only keeps the latest state of attributes, overwriting previous values when changes occur. SQL Script for SCD Type 1 Dimension Table ```sql -- Create a Dimension Table for Claims Adjuster (SCD Type 1) CREATE TABLE IF NOT EXISTS dbo.AdjusterDimension_SCD1 (     AdjusterKey INT IDENTITY(1,1) PRIMARY KEY,     AdjusterID INT,     AdjusterName NVARCHAR(100),     AdjusterRegion NVARCHAR(50) ); -- In...