Welcome to my IBM Data Analyst Capstone Project , where I served as a Data Analyst for an IT and Business Consulting organisation. The firm was well-regarded for its expertise in IT solutions and its team of highly skilled professionals. To remain competitive in the rapidly evolving technological landscape, the company regularly analysed data to identify future skill requirements. My role involved collecting data from various sources and spotting trends for that year’s report on emerging trends.
The data analysis process was documented in uploaded files covering six modules.
Module 1 focused on data collection, where I compiled a list of in-demand programming skills from job ads, training websites, and surveys. I employed web scraping techniques and Application Programming Interface (APIs) to gather data in various formats, including .csv files and Excel sheets.
Module 2 involved data wrangling, where I utilised techniques to prepare the collected data for analysis. In Module 3, I performed exploratory data analysis using statistical methods to analyze the cleaned data.
Module 4 was dedicated to data visualisation, during which I created charts and graphs to effectively illustrate the findings. In Module 5, I built a dashboard using IBM Cognos Analytics and Google Looker Studio to consolidate all data, enabling me to identify trends and insights, such as the most in-demand programming languages and popular database skills.
Finally, in Module 6, I presented my findings using storytelling techniques to communicate the insights effectively. This project aimed to provide valuable information on the evolving skill requirements in the tech industry.
