Chapter 3 Capturing the Value of the Lakenhouse Approach

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What is a key difference between a data warehouse and a lakehouse?

The time period they were introduced

The type of data they handle (correct)

The level of vendor lock-in

The structure of their architecture

What is vendor lock-in a result of?

Storing data in a data warehouse

Storing data in a data lake

Using proprietary formats to store data (correct)

Using open-source formats to store data

What is a major difference between a data lake and a lakehouse?

The type of data they handle

Their architecture is fundamentally different (correct)

The level of vendor lock-in

The time period they were introduced

What is the primary advantage of using a lakehouse over a data warehouse?

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

When was the lakehouse approach introduced?

2020 Signup and view all the answers

What is a major challenge in the current data landscape?

Vendor lock-in and high operational costs Signup and view all the answers

What is the primary advantage of a lakehouse approach?

Unifying all data teams and allowing them to run analytics and ML in a single place Signup and view all the answers

What is a key benefit of using a lakehouse approach in terms of data freshness?

It can process batch and streaming data in a continuous manner, updating tables and dashboards in near real-time Signup and view all the answers

According to the lakehouse approach, where is the complete and firm copy of all data stored?

In a centralized location, accessible by all teams Signup and view all the answers

What is a benefit of the lakehouse approach in terms of vendor lock-in?

It uses open formats and open standards, making it easy to move data to a different vendor or technology Signup and view all the answers

What is a challenge that can be overcome with a lakehouse approach?

Unifying data teams and facilitating the breaking of data silos Signup and view all the answers

What is a key advantage of a lakehouse approach in terms of data management?

It enables the management of both structured and unstructured data Signup and view all the answers

What can compromise data integrity in a data lake?

Concurrent data pipelines Signup and view all the answers

What is a common outcome of complex and inefficient data pipeline setups?

Unreliable data processing jobs Signup and view all the answers

What can cause expensive overhead costs and limited workload scalability in data pipelines?

Static infrastructure resources Signup and view all the answers

What is a common challenge in processing both batch and streaming data jobs?

Meeting requirements for streaming data Signup and view all the answers

What can result from manual cleanup and reprocessing after failed data processing jobs?

Lead time delay Signup and view all the answers

What is the outcome of nonscalable processes with tight dependencies, complex workflows, and system downtime?

Undesirable for any company Signup and view all the answers

What is a primary reason behind the emergence of lakehouse architecture?

To address the limitations and complexity of separate stacks for business intelligence and machine learning Signup and view all the answers

What is a key feature of a lakehouse in terms of its data structures and management?

It uses similar data structures and data management features to those in a data warehouse, but on a different type of storage Signup and view all the answers

What is a primary benefit of using a lakehouse architecture?

It enables users to do everything from BI, SQL analytics, data science, and ML on a single platform Signup and view all the answers

What is a characteristic of a lakehouse in terms of its storage requirements?

It uses low-cost object storage, similar to data lakes Signup and view all the answers

What is the primary goal of the lakehouse approach in terms of data management?

To create a single platform for all data management needs Signup and view all the answers

What is the relationship between lakehouses and data warehouses in terms of their design?

A lakehouse is a redesign of a data warehouse, but with modern storage capabilities Signup and view all the answers

What is a major challenge in managing ML environments?

The diversity of ML frameworks Signup and view all the answers

What makes handoffs difficult to manage efficiently between teams?

The disparate tools and process steps Signup and view all the answers

What is a built-in risk from a security and compliance perspective?

Data dependency Signup and view all the answers

What is a challenge in ML due to tracking difficulties?

Tracking experiments, models, dependencies, and artifacts Signup and view all the answers

What is a key benefit of the lakehouse approach?

Quick access to clean and reliable data Signup and view all the answers

What is a feature of the lakehouse approach?

One-click access to pre-configured clusters Signup and view all the answers