Chevron Left
Back to Data Storage and Queries

Learner Reviews & Feedback for Data Storage and Queries by DeepLearning.AI

4.8
stars
33 ratings

About the Course

In this course, you will learn about the raw ingredients and processes that are used to physically store data on disk and in memory. You’ll explore different storage systems, including object, block, and file storage, as well as databases, that are built on top of these raw ingredients. You’ll also get a chance to use the Cypher language to query a Neo4j graph database, and perform vector similarity search, a key feature behind generative AI and large language models. You will explore the evolution of data storage abstractions, from data warehouses, to data lakes, and data lakehouses, while comparing the advantages and drawbacks of each architectural paradigm. With hands-on practice, you will design a simple data lake using Amazon Glue, and build a data lakehouse using AWS LakeFormation and Apache Iceberg. In the last week of this course, you’ll see how queries work behind the scenes, practice writing more advanced SQL queries, compare the query performance in row vs column-oriented storage, and perform streaming queries using Apache Flink....

Top reviews

YW

Nov 18, 2024

Insightful overview of a simple yet complicated concept such as storage and queries.

RA

Nov 19, 2024

Clearly structured and all concepts are well explained by the instructor.

Filter by:

1 - 4 of 4 Reviews for Data Storage and Queries

By Yosef A W

•

Nov 18, 2024

Insightful overview of a simple yet complicated concept such as storage and queries.

By rashid a

•

Nov 20, 2024

Clearly structured and all concepts are well explained by the instructor.

By Mildrien I H

•

Dec 2, 2024

worth the time to learn.

By Benjamin W

•

Nov 24, 2024

I've just completed "Data Storage and Queries," the 3rd course in the Coursera Data Engineering Specialization (only one course to go!) This course was a bit of a mixed bag for me. I found it interesting to learn about concepts related to data storage, including: Storage options Query processing Data Lakes Data Lakehouses I also enjoyed the hands-on experience with: Comparing row vs column-based storage with Amazon Redshift and PostgreSQL Graph databases Vector databases Building a Data Lakehouse with AWS Lake Formation and Apache Iceberg. However, I found the advanced SQL section a bit dull, as I use those skills daily. Additionally, I felt the sections on querying streaming data (and using Amazon Managed Service for Apache Flink) would have been more beneficial if we were working with live data instead of static JSON files. Despite these points, I still found the course worthwhile, and I'm looking forward to the next one!