The aim of this project is to analyze all the factors that affect the salary of a data specialist.
The readme file will just include a preview about the project , but the detailed description will be in the project's docs.
Project.Preview.mp4
In the project files you will see some files:
- Project Preview.mp4: Video Preview for the project.
- Dashboard.pbix: The Power BI file that includes the analysis' dashboard.
- Project Docs.pdf: The project's documentations.
- eda_data.csv-glassdoor_jobs.csv: The datasets used for the analysis.
- Cleaned Jobs.csv: The cleaned dataset imported from Power Query, after the data modeling phase.
The Power BI Dashboard consists of five report pages:
-
Explore: Includes some visuals that will help us understand the dataset (Exploratory Data Analysis).
-
Basic Analysis: Includes some basic (level 1) analysis mainly focused on the most basic factors that affect the salary.
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Drill: Contains the ratio of each skill, which represents how many rows in the dataset have a skill like Python or Excel.
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More Analysis: Includes deeper analysis which visualizes some factors that affect the expected salary of a data specialist.
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Complex Analysis: As a data specialists there are tons of skills we need to master like:
- Python
- Excel
- R
- etc
But Which skill is really vital?
This report page is mainly focused on analyzing the impact of having each skill on your expected salary as a data Engineer.
- Each step we have done throughout the project
- Data Definition: Which describes the dataset in details.
- Data Cleaning steps explained.
- Questions We want the dasboard to answer.
- Exploratory Visuals To help us understand the data.
- The Insights We have extracted from the analysis along with the visuals used to communicate those insights.
- All insights are illustrated.