Go back
Harmonizing Data and Tackling Quality Challenges for Leading Insurance Firm
5 Scenarios
7 Hours 30 Minutes
Intermediate
Industry
insurance
Skills
batch-etl
cloud-management
data-wrangling
data-storage
data-quality
Tools
databricks
Learning Objectives
Parse and Ingest Data in Databricks
Authoring Reusable code to tackle schema and data inconsistencies
Implementation of delta lakes as a part of medallion architecture
Implementation of schema evolution in Delta lake
Overview
Prerequisites
- Knowledge of how Databricks and ADLS works
- Proficiency in Data Analysis, Data Processing and Data cleaning using Pyspark
- Understanding on Capabilities of Delta table
- Knowledge of ETL using Medallion Architecture