A Melodious Analysis… ♫

This video clearly indicates what this blog is all about. I am a newbie in data analytics, trying to polish my data analytics skills. Kishore Kumar is my personal favourite, so I came up with this blog to analyze the trends in his professional life.

These are the steps I followed to achieve my final analysis:

Data collection:

The data was acquired from the wikipedia site on Kishore Kumar’s songs.

Songs ranging from the year 1946 to 2019 were arranged in different tables. One table for one year. Only the data from 1946 to 1989 has been considered, as the songs after 1989 are the remixed versions.

This data was brought together in one Excel spreadsheet. Total there are 2575 songs.

Data cleaning:

Software used: Microsoft Excel

The following changes were made in order to make the data consistent:

1. Names of the same singers and musicians were spelt differently. These names are made consistent.
2. Musician duo’s names are conventionally separated with a ‘-’ .
3. 18 musicians’ names were missing, and 18+ lyricist’s names were missing. This information has been manually entered into the table.
4. A few names of musicians and singers were swapped, they have been corrected.
5. Duplicates entries have been removed.
6. Songs with more than one singer, have the names of all the singers listed in one cell. These names are separated in different columns.
7. Columns which are not required are dropped.

Dataset in Excel Sheet

Data Analysis:

Software used: MySQL Workbench.

SQL queries were run to analyze the data.

The following trends were evaluated:

1. Number of songs sung with passing years.
2. Musicians who have composed the maximum number of songs sung by Kishore Kumar.
3. Trend of Top 3 composers across years.
4. How his preferences for duet and solo songs changed over year.
5. Lyricists who wrote the maximum songs for Kishore Kumar.

Snapshot of a query run in MySQL Workbench

Data Visualization:

Software used: Tableau.

The trends analyzed during the analysis phase were visualized using data visualization tools.

The data viz are added into the dashboard for enabling the audience to easily understand the analysis.

Visualizations created:

These visualizations will be used to make a presentation for explaining the analysis.

That was all. Thank you for reading my first blog!!