Knowledge quiz

It's time to put what you've learned to the test, get 8 right to pass this unit.

What is a primary driver behind the evolution of data architecture from traditional centralized data warehouses to more modern, distributed approaches?

Choose the correct answer.

A decrease in the volume of data that enterprises generate and need to analyze.

A reduced emphasis on data governance and security within organizations.

The increasing need for agility, scalability, and the ability to handle diverse data types.

The standardization of all enterprise data into structured formats.

A "Data Product" is best described as:

Choose the correct answer.

A dashboard or a report.

A reusable, trusted, and self-contained unit of value built from data, designed to solve a specific business problem.

Any raw table in a database.

A one-time data extraction for analysis.

What is the primary architectural difference between ETL and ELT?

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ETL runs on the cloud, while ELT runs on-premise.

ETL is only for structured data, while ELT is only for unstructured data.

ETL is an outdated pattern, while ELT is the only modern pattern.

ETL transforms data before loading it into the target system, while ELT transforms data after loading it, using the target system's compute.

Which architecture is a hybrid evolution that merges the flexibility of a Data Lake with the structure and governance of a Data Warehouse?

Choose the correct answer.

Data Mesh

Data Fabric

Data Lakehouse

Data Mart

Which of the following is not one of the six key characteristics of a data product?

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Consumer-Focused

Addressable & Discoverable

Centralized & Monolithic

Live, Trustworthy, and Reliable

The concept of "Data as a Product" is the fundamental building block of which data architecture paradigm?

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Data Warehouse

Data Fabric

Data Lake

Data Mesh

The ETL pattern is still a good choice when:

Choose the correct answer.

You prioritize agility and experimentation with raw data.

Data requires heavy pre-processing or strict auditability for compliance.

You want to leverage the scalable compute power of a cloud platform.

You want to store raw data once to support many different use cases.

According to the "Architect's Decision Framework," which paradigm is the "integration solution" best for solving data sprawl and integration chaos in a heterogeneous (hybrid/multi-cloud) landscape?

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Data Warehouse

Data Mesh

Data Fabric

Data Lakehouse

According to the "Architect's Decision Framework," which paradigm is the "sociotechnical solution" best for solving the organizational bottleneck of a centralized data team?

Choose the correct answer.

Data Warehouse

Data Mesh

Data Lakehouse

Data Fabric