Inspiration
We were inspired to take up this project looking at the tremendous potential of the data provided to us. The data provided us with every prospect of solving the business problem posed in front of us in various unique ways.
What it does
Our project is designed in two phases. The first part of our project predicts what hours of the day as well as what days of the week are the best to place business calls. The second part of the project offers insights into what the current trends are and how certain aspects of the business strategy can be improved.
How we built it
We used the Naive Bayes Classifier to clean our data and build our prediction model using R in R studio. Later we used PowerBI to build a Storytelling Dashboard to offer insights on the presented data.
Challenges we ran into
The main challenge was working with data with very minimal numerical values. This made it somewhat difficult to build a correlation between the different attributes.
Accomplishments that we're proud of
Studying the data and identifying the relevant factors to present solutions for the given problems was challenging. But with a lot of effort, we are proud to present an elegant model.
What we learned
Being beginners in the journey of Data Science, we learned how to work with various new tools like R studio, Tableau, and PowerBI.
What's next for Triumph
We hope to move forward in out Data Science journey by solving many more such problems based on real-world datasets.
Built With
- powerbi
- r
- rstudio
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