LFC Architecture 2

Question 1

In a Lakehouse architecture, what role does the metadata layer play?

Accepted Answer

It provides schema, versioning, and ACID transaction management over object storage

Answer

The metadata layer (e.g., Delta Lake, Iceberg, Hudi) tracks schema evolution, file statistics, and transaction logs to enable ACID semantics on object storage.

Question 2

Which characteristic distinguishes a Lakehouse from a traditional two-tier Lambda architecture?

Accepted Answer

The Lakehouse eliminates the separate serving layer by enabling direct BI access on the storage tier

Answer

A Lakehouse collapses the separate data warehouse serving layer so BI tools can query the same open-format storage used for ML and data science.

Question 3

What is the purpose of Z-ordering (data skipping) in Delta Lake's storage layer?

Accepted Answer

To co-locate related data within Parquet files so queries scan fewer files

Answer

Z-ordering multidimensionally sorts data so that frequently filtered columns are co-located, enabling Delta Lake to skip irrelevant files during query execution.

Question 4

In Databricks Lakehouse architecture, what does the concept of 'medallion architecture' describe?

Accepted Answer

A multi-hop data refinement pattern using Bronze, Silver, and Gold layers

Answer

The medallion architecture organizes data into Bronze (raw), Silver (cleaned/conformed), and Gold (business-aggregated) layers for progressive data quality.

Question 5

Which component in the Databricks Lakehouse platform serves as the unified governance layer for data and AI assets?

Accepted Answer

Unity Catalog

Answer

Unity Catalog provides centralized access control, auditing, lineage, and data discovery across all workspaces in a Databricks account.

(LFC) Lakehouse Fundamentals Certification Practice Test

(LFC) Lakehouse Fundamentals Certification Practice Test

LFC Architecture 2