Feedback submission

[peremateu]

Assignment Proposal

Title

Feedback on Database visualisation with Sampler

Names and KTH ID

• Siham Shahoud ([email protected])
• Pere Mateu Raventós ([email protected])

Deadline

• Task 3

Category

• Feedback

Description

Executable Tutorial being given feedback: Database visualisation with Sampler.

Authors: Peiyang Zheng and Florian Jerome Immig
Feedback by: Pere Mateu Raventós and Siham Shahoud

Date Received: 2024-10-08 at 15:35.
Number of words: 635

Code of Conduct

We certify that generative AI, incl. ChatGPT, has not been used to write this feedback. Using generative AI without permission is considered academic misconduct.

Introduction

We have the pleasure of going through the executable tutorial “Database visualisation with Sampler” provided by the authors Zheng and Immig via KillerCoda and Github. And we would like to thank them for giving us the chance to provide our feedback.

Our feedback is aimed at providing constructive, actionable insights on both strengths and areas for improvement, while also suggesting ways to make the tutorial even more engaging and comprehensive.

High-level strengths and positive comments

One of the most significant strengths of this tutorial is its clarity and structure from the beginning to the end. The introduction provides a well defined overview which contains clear intended outcomes. This helps users understand from the beginning what they will achieve by the end of the tutorial, providing clear goals and direction. Moreover, the tutorial’s importance in Devops is clearly motivated, stating that it is sometimes hard to set up monitoring tools. And we think that is an important point, as it addresses a real challenge many Devops developers face.

In addition, the tutorial has appropriate grammar, spelling, and punctuation, making it easy for users to read and understand the content. Overall, the tutorial is easy to follow, providing flexibility and satisfaction for the reader. It does not require users to open complex or paid accounts for the grader, enhancing accessibility. Additionally, the tutorial is illustrated with informative figures, such as when installing PostgreSQL, the authors attached a figure to make sure the user has installed the database correctly. And that actually helps the reader to understand the tutorial in an effective manner.

High-level weaknesses about the work

While the tutorial has many strengths, there are a few areas where improvements could be made to enhance the overall learning experience.

Lack of background: Firstly, the tutorial assumes a certain level of prior knowledge in database management. The target of this tutorial are computer science students in master level, who might not have worked much with data science before. Therefore, we think there is a lack of background about the topic.

Lack of context: Some of the commands used throughout the tutorial are not explained in sufficient detail. For example, when demonstrating how to create a new database and user, there is no explanation of the commands used to give or remove privileges.

Installing the sampler tool: The tutorial provides commands to install the Sampler tool but does not include descriptions of what each command does. This may leave users confused about the purpose of each step.

Suggestion for Improvement

So, to address the issues we found, we first suggest adding a paragraph or a section in the introduction where you can find some background. To do that you can explain what is the basic process in which you should use the sampler tool.

Additionally, if you introduce data science terms, make sure to explain them. For example, when you talk about monitoring, you should think that not everyone knows what it is like, so in order to get your message clear, you should point out what the practices monitoring are?

The way to improve the lack of context would be to explain a bit at least the commands that might feel a bit confusing and not trivial, such as when using the syntax of a specific tool, like MySQL. In addition, to improve clarity and structure we suggest writing the title of the figure and number.

Additional material:

The material we can give you is related to the background we were talking about. In this post they explain clearly the concept with a bit of history and clear examples. It also gives the key points included in database monitoring in a nice structure. This way you can get ideas on how to explain what database monitoring is, as well as the concepts around it.

[javierron]

Hi @peremateu. Before I merge this submission, please post the feedback as a comment in the corresponding pull request. #2623

[peremateu]

Okay, done! :)