The Data Engineering team at a large manufacturing company needs to engineer data coming from many sources to support a
Posted: Thu Apr 06, 2023 1:25 pm
The Data Engineering team at a large manufacturing company needs to engineer data coming from many sources to support a wide variety of use cases and data consumer requirements which include:
1. Finance and Vendor Management team members who require reporting and visualization
2. Data Science team members who require access to raw data for ML model development
3. Sales team members who require engineered and protected data for data monetization
What Snowflake data modeling approaches will meet these requirements? (Choose two.)
A. Consolidate data in the company’s data lake and use EXTERNAL TABLES.
B. Create a raw database for landing and persisting raw data entering the data pipelines.
C. Create a set of profile-specific databases that aligns data with usage patterns.
D. Create a single star schema in a single database to support all consumers’ requirements.
E. Create a Data Vault as the sole data pipeline endpoint and have all consumers directly access the Vault.
1. Finance and Vendor Management team members who require reporting and visualization
2. Data Science team members who require access to raw data for ML model development
3. Sales team members who require engineered and protected data for data monetization
What Snowflake data modeling approaches will meet these requirements? (Choose two.)
A. Consolidate data in the company’s data lake and use EXTERNAL TABLES.
B. Create a raw database for landing and persisting raw data entering the data pipelines.
C. Create a set of profile-specific databases that aligns data with usage patterns.
D. Create a single star schema in a single database to support all consumers’ requirements.
E. Create a Data Vault as the sole data pipeline endpoint and have all consumers directly access the Vault.