Spa Design Consultants Interview Questions and Answers

ETL pipeline ecosystem in Azure Databricks involves data extraction, transformation, and loading processes using various tools and services.

• ETL process involves extracting data from various sources such as databases, files, and streams.

• Data is then transformed using tools like Spark SQL, PySpark, and Scala to clean, filter, and aggregate the data.

• Finally, the transformed data is loaded into target systems like data warehouses, data lakes, or BI tools.

• Azure Databricks provides...read more

Star schema for simple queries, Snowflake schema for complex queries with normalized data.

• Star schema denormalizes data for faster query performance.

• Snowflake schema normalizes data for better data integrity and storage efficiency.

• Use Star schema for simple queries with less joins.

• Use Snowflake schema for complex queries with multiple joins and normalized data.

• Example: Star schema for a data warehouse used for reporting, Snowflake schema for OLTP systems.

SCD (Slowly Changing Dimensions) manages historical data changes in data warehouses.

• SCD Type 1: Overwrite old data (e.g., updating a customer's address without keeping history).

• SCD Type 2: Create new records for changes (e.g., adding a new row for a customer's address change).

• SCD Type 3: Store current and previous values in the same record (e.g., adding a 'previous address' column).

• Implementation can be done using ETL tools like Apache NiFi or Talend.

• Database triggers can als...read more

Incremental loading is the process of adding new data to an existing dataset without reloading all the data.

• Identify new data since the last load

• Update the existing dataset with the new data

• Maintain data integrity and consistency

• Use timestamps or unique identifiers to track changes

• Avoid duplicate entries and ensure data quality