(Delta) Ch 10: Build a Lakehouse on Delta Lake (Multiple Choice)

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Questions and Answers

What makes data lakes appealing for organizations with diverse skills and tools?

The use of standardized APIs for integration (correct)

The requirement of specific tools and skills

The need for on-premise infrastructure

The ability to use a single programming language

Why is replication useful in cloud data lakes?

To eliminate the need for data archiving

To increase data storage costs

To meet compliance requirements and enable failover (correct)

To reduce data latency

What is the purpose of lifecycle policies in cloud data lakes?

To move data across different storage availability classes (correct)

To eliminate the need for data replication

To reduce data availability

To increase storage costs for infrequently accessed data

How does cloud data lakes affect costs?

You pay for what you use, and costs align with data volumes Signup and view all the answers

What is an advantage of having a single storage layer in cloud data lakes?

Less data movement across systems Signup and view all the answers

What is the benefit of decoupled storage versus compute in cloud data lakes?

Minimized costs for data storage Signup and view all the answers

What is a benefit of cloud data lakes in terms of storage?

Minimized costs for data storage Signup and view all the answers

What is the foundation of the Apache Spark ecosystem?

Spark Core and Spark SQL engine Signup and view all the answers

What type of SQL does Spark SQL support?

ANSI SQL Signup and view all the answers

How can you query a Delta table in PySpark?

Using the sql() method Signup and view all the answers

What is the purpose of the Spark SQL library?

To allow users to query and analyze data using SQL syntax Signup and view all the answers

What is the interface that analysts and report builders typically use to interact with data?

SQL interface Signup and view all the answers

What is the benefit of using Spark SQL?

It allows users to query and analyze data using familiar SQL syntax Signup and view all the answers

What is the relationship between Spark SQL and the DataFrame API?

Spark SQL allows users to interact with datasets and tables using the DataFrame API Signup and view all the answers

What is the purpose of the %sql magic command in notebooks or IDEs?

To write Spark SQL queries directly in a cell Signup and view all the answers

What is the primary purpose of the Bronze layer in the Medallion architecture?

To store an exact copy of the data received from the source, with no transformations Signup and view all the answers

What is a key characteristic of the Silver layer?

Data is denormalized and read-optimized Signup and view all the answers

What is the primary focus of the Gold layer?

Providing a format that is easy for business users to navigate Signup and view all the answers

What type of data models are used in the Gold layer?

Denormalized data models Signup and view all the answers

What is the purpose of data quality checks in the Silver layer?

To identify and correct errors in the data Signup and view all the answers

What type of transformations are applied in the Gold layer?

Precalculated, business-specific transformations Signup and view all the answers

How is data typically stored in the Bronze layer?

In folders based on the date received Signup and view all the answers

What is the primary focus of the Bronze layer?

Storing an exact copy of the data received from the source Signup and view all the answers

What is the purpose of the Medallion architecture?

To provide a landing zone for raw data and enable the creation of a data lakehouse Signup and view all the answers

What type of modeling is used in the Silver layer?

Light modeling for data discovery and self-service Signup and view all the answers

What is one of the benefits of using time travel in machine learning models?

It enables easy auditing or reproduction of models Signup and view all the answers

What is the primary goal of using Delta Lake in an organization?

To reduce silos and unify workloads between data engineers and data scientists Signup and view all the answers

What is the primary benefit of using a lakehouse architecture in machine learning?

It enables faster and more efficient management of machine learning models Signup and view all the answers

Which of the following is NOT a feature of the Spark ecosystem?

Data visualization tools Signup and view all the answers

What is the primary role of a lakehouse environment in machine learning?

To unify data engineering and data science workloads Signup and view all the answers

What is the relationship between Delta Lake and a lakehouse architecture?

Delta Lake is a key feature of a lakehouse architecture Signup and view all the answers

What is the primary benefit of using a high-performance query engine in a lakehouse environment?

It enables faster and more efficient querying of data Signup and view all the answers

What is the primary role of Apache Spark in a lakehouse environment?

It provides a high-performance query engine Signup and view all the answers

What is the main characteristic of the data in a cloud-based data lake?

Structured, semi-structured, and unstructured data Signup and view all the answers

Which of the following is NOT a characteristic of a cloud-based data lake?

High-maintenance Signup and view all the answers

What type of data processing is supported in the data lake?

Both batch and streaming processing Signup and view all the answers

Which of the following is a cloud-based data storage provider?

All of the above Signup and view all the answers

What is the data in the curated layer?

Filtered, cleansed, and augmented Signup and view all the answers

Study Notes

Data Lakes

Data lakes offer simple integration through standardized APIs, allowing users with different skills, tools, and programming languages to perform various analytics tasks simultaneously.

Replication

Cloud providers offer easy setup of replication to different geographical locations for data lakes, useful for meeting compliance requirements, failover for business-critical operations, disaster recovery, and minimizing latency.

Availability

Cloud systems offer different types of data availability for cloud data lakes, allowing for lifecycle policies to move data across different storage availability classes for compliance, business needs, and cost optimization.
Availability can be defined through service-level agreements (SLAs), guaranteeing a minimal level of service, typically greater than 99.99% uptime for business-critical resources.

Cost

With cloud data lakes, users typically pay for what they use, and costs always align with data volumes.
A single storage layer, minimal data movement, and decoupled storage versus compute minimize costs for data storage.

Apache Spark Ecosystem

The Apache Spark ecosystem consists of different libraries, with Spark Core and Spark SQL engine as the substrate.
Spark SQL supports ANSI SQL, allowing users to query and analyze data using SQL syntax.
Spark SQL library allows users to interact with datasets and tables using the DataFrame API.
Time travel enables easy auditing or reproduction of machine learning models.

Lakehouse Architecture

The lakehouse architecture bridges the gap between data engineers and data scientists, unifying workloads and reducing silos.
The architecture enables organizations to build and manage machine learning models in a faster, more efficient way.

Medallion Architecture

The medallion architecture consists of Bronze, Silver, and Gold layers.
Bronze layer: landing zone for raw data, no schema required, fast and easy to get new data.
Silver layer: first layer useful to the business, prioritizes speed to market, enables data discovery, self-service, ad hoc reporting, advanced analytics, and ML.
Gold layer: data is in a format easy for business users to navigate, prioritizes business use cases, highly performant, and pre-calculated, business-specific transformations.

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Description

Data lakes offer simple integration and cloud providers offer easy replication to different geographical locations for data lake management.