Data Analytics And Visualisation
Data Analytics And Visualisation
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Logic And Mathematics
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It covers mathematical processes for developing algorithms in computing and other real-life applications. In addition, students are also taught the data analytics lifecycle, including gathering, cleaning, processing and visualizing of data.
It covers mathematical processes for developing algorithms in computing and other real-life applications. In addition, students are also taught the data analytics lifecycle, including gathering, cleaning, processing and visualizing of data.
Projects:
Project 1: Worked with a dataset about hotel bookings
Cleaning of data
Linear regression
Usage of mathematical functions
Investigation of the dataset through analysis
Project 2: Worked with three others on a dataset regarding COVID-19 cases in Singapore
Data Preparation and Cleaning
Defined two new fields mathematically that are useful to the decision-making of the government
Get 5 insights from the data and present using PowerBI on a dashboard
Project 1
Project 1
A sample workflow of Project 1
A sample workflow of Project 1
The screenshot on the left shows the workflow for Project 1. Some of the nodes that I had learnt are the CSV Reader node and Scatter Plot node.
Project 2
Project 2
1st Page of the Dashboard
1st Page of the Dashboard
2nd Page of the Dashboard
2nd Page of the Dashboard
Some of the graphs that were used to demonstrate our inferences in PowerBI using the cleaned data from KNIME
Workflow of Project 2
Workflow of Project 2
Our workflow in KNIME used for the project.
What I learnt from the projects:
Both projects taught me a lot about analyzing data and visualizing them. I learnt how to use KNIME, a platform to prepare data, and PowerBI, a data visualization platform, where I could create dashboards with various graphs to better understand the data. In addition, I was able to learn more about the importance and usefulness of data analysis.
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