kiinda-2/DataCompensation

Analysed data from a survey carried out on data proessional to gain insights to understand the data market in Kenya ## DataCompensation Analysed data from a survey carried out on data proessional to gain insights to understand the data market: salary range of data proessionals, tools popularly used, benefits gotten from the job etc. Data Source: Phoenix Analytics Group ### Assumptions 1. The analysis is limited to the number of responses provided. 2. I categorized related industries into one 'umbrella category' such as school and edtech under Education. 3. That salaries are similar for roles and levels that are similar: which I used to populate missing salaries. ### Data Cleaning - Checked data for duplicates - Transformed data for consistency in values by updating values - Handled missing values ### Tools - SQL: Data Cleaning, Aggregate Functions, JOINS, CTEs - Power BI: Visualization ### Insights - The average salary is 113k - Excel, SQL, Power BI and Python are top tools mostly used. - Other popular tools include: STATA, Power Automate and Oracle - Industries in Agriculture, gaming, Development and Telecommunications earn highly. - Those in senior levels i.e managers earn highly while entry level earn relatively low - Most people - twice as much as work in an established organization - Data engineers earn highly as compared to Data Scientists or Data Analysts - A hybrid setup pays highly, 30k higher than remote and 40k higher than full office roles - Health Insuarance, Mobile Credit Top-up, Pension are top beneits received from the job - Females are earning higher than men, most of them are in Development, Telecommunication and Gaming working in already established setups and are Data Scientists and Analysts - Males are in Agriculture and Media and are Data Engineers working in established organizations ### Recommendations For new data professionals, I would recommend: 1. Excel, SQL, Power BI and Python are tools to focus on learning 2. When negotiating for benefits health insuarance is key to consider 3. Consider working in an already established organization and roles …