18 Questions
What is the main difference between a data lake and a data warehouse in terms of data storage?
Data lakes store all kinds of data in its raw format, while data warehouses store only modeled/aggregated/structured data.
What is the processing approach for loading data into a data warehouse?
Modeling into a star or snowflake schema on write
How does the retrieval speed from data warehouses differ from that of data lakes?
Data warehouses have faster retrieval speed due to in-database processing.
Which term describes the process of giving shape or structure to raw data when ready to use it in a data lake?
Schema-on-read
What role do algorithms play in the retrieval speed from data warehouses?
Algorithms are developed to enhance the speed of retrieving large and feature-rich data.
Why are data lakes not considered a replacement for data warehouses?
Data lakes and data warehouses serve different purposes and are complementary.
What is the main purpose of a data warehouse?
To process and analyze structured data for business intelligence
Which one of the following is NOT a component of the data warehouse framework?
Real-time data streaming
What is the primary difference between a data warehouse and a data lake?
A data warehouse stores structured data, while a data lake stores unstructured data
Which process is responsible for extracting data from various sources, transforming it, and loading it into the data warehouse?
Extract, Transform, Load (ETL)
What is the purpose of dimensional modeling in the context of a data warehouse?
To create a logical model for organizing and presenting data in a multidimensional way
Which of the following statements about big data and data warehouses is correct?
Data warehouses and big data technologies can coexist and complement each other
What is one of the primary features of Big Data technologies like Hadoop in terms of data storage costs?
They are open-source, reducing the cost of storing data.
What differentiates the structure of a data lake from a data warehouse?
A data lake allows easy configuration and reconfiguration, unlike a data warehouse.
Why are data lakes considered to have more novelty and innovation compared to data warehouses?
Data warehousing technologies have been around for a long time with few recent innovations.
What advantage do data warehouses have over data lakes in terms of security?
Data warehouses have more mature security capabilities.
Which key reason contributes to the low cost of storing data in Hadoop compared to traditional data warehousing?
Hadoop leverages low-cost commodity hardware and is open-source.
What is a distinguishing characteristic of the underlying technologies of data warehousing compared to those of data lakes?
The technologies underlying data warehousing have been around for a much longer period.
Study Notes
Data Lakes vs Data Warehouses
- A data lake is not a replacement for a data warehouse; they are complementary to one another.
Data Storage
- A data warehouse stores structured data that has been modeled/aggregated, whereas a data lake stores all kinds of data (structured, semi-structured, and unstructured) in its native/raw format.
Processing
- Data warehousing requires data to be modeled into a star or snowflake schema before loading, known as schema-on-write.
- Data lakes load raw data and give it a shape or structure when ready to use, known as schema-on-read.
Retrieval Speed
- Data warehouses have developed algorithms to improve retrieval speed, including triggers and columnar data representation.
- Retrieving data from a data lake can be time-demanding due to the variety of data formats.
Storage
- Data warehouses store structured data, whereas data lakes store vast quantities of data in its native/raw format for future analytics consumption.
Agility
- Data warehouses are highly structured repositories, making changes time-consuming due to tied business processes.
- Data lakes lack structure, allowing for easy configuration and reconfiguration of models, queries, and apps.
Novelty
- Data warehousing technologies have been around for a long time, with little innovation in recent years.
- Data lakes are new and undergoing innovation to become a mainstream data storage technology.
Security
- Securing data in a data warehouse is more mature than securing data in a data lake due to decades of development.
Test your knowledge on the content covered in the first lecture of the Data Warehouse course (IS 422) with Dr. Wael Abbas. This quiz covers topics such as DW architectures, dimensional modeling, and course information.
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