IBM Data Analyst Capstone Project

Overview

Welcome to the IBM Data Analyst Capstone Project! As a newly hired Data Analyst at a global IT and business consulting firm, you will play a critical role in identifying future skill requirements and trends in the rapidly evolving tech landscape. Your primary goal is to analyze data from various sources to provide insights that will help the organization remain competitive.

Project Objective

Your main task is to collect and analyze data on the most in-demand programming skills. This will include gathering information from:

• Job Postings: Analyzing current job requirements in the tech industry.
• Training Portals: Understanding which skills are being emphasized in training programs.
• Surveys: Collecting insights directly from industry professionals.

Key Questions to Address

• What are the top programming languages in demand?
• What database skills are most sought after?
• Which Integrated Development Environments (IDEs) are popular among developers?

Data Collection

You will utilize various techniques to collect data, including:

• APIs: Accessing structured data from online platforms.
• Web Scraping: Extracting relevant information from job boards and educational sites.
• File Formats: Working with data in formats such as CSV, Excel, and databases.

Data Preparation

Once the data is collected, you will apply data wrangling techniques to ensure it is ready for analysis. This includes:

• Finding and Handling Missing Values: Identifying gaps in the data and determining how to address them.
• Removing Duplicates: Ensuring that your dataset is clean and accurate.
• Normalizing Data: Making sure data is in a consistent format for analysis.

Data Analysis

With the data prepared, you will apply statistical techniques to analyze it. This phase will include:

• Exploratory Data Analysis (EDA): Understanding the distribution of data, identifying outliers, and examining correlations.

Data Visualization

You will create visual representations of your findings, which may include:

• Distribution Visualizations: Showing how data is spread out.
• Relationship Visualizations: Exploring the connections between different variables.
• Composition and Comparison Visualizations: Comparing different groups within the dataset.

Dashboard Creation

Utilizing IBM Cognos Analytics, you will create interactive dashboards that summarize your findings and present the most critical insights effectively.

Presentation of Findings

Finally, you will compile your insights into a compelling presentation. You will showcase your storytelling skills by highlighting key trends and insights that your analysis uncovered.

Modules

Module 1: Data Collection

• Collecting Data Using APIs: Learn how to fetch data from various APIs to gather relevant information.
• Collecting Data Using Web Scraping: Utilize web scraping techniques to extract data from job postings and training portals.
• Exploring Data: Perform initial exploration of the collected data to understand its structure and content.

Module 2: Data Wrangling

• Finding Missing Values: Identify and analyze missing data points.
• Determining Missing Values: Decide how to handle missing data.
• Finding Duplicates: Detect duplicate entries in the dataset.
• Removing Duplicates: Clean the data by removing any duplicates.
• Normalizing Data: Ensure data consistency by normalizing it.

Module 3: Exploratory Data Analysis

• Distribution: Analyze how data is distributed across different variables.
• Outliers: Identify and handle outliers in the dataset.
• Correlation: Explore relationships between variables through correlation analysis.

Module 4: Data Visualization

• Visualizing Distribution of Data: Create visualizations to represent data distributions.
• Relationship Visualizations: Illustrate relationships between different data points.
• Composition and Comparison: Compare various datasets through visual representation.

Module 5: Dashboard Creation

• Dashboards: Create interactive dashboards using IBM Cognos Analytics to display your findings effectively.

Module 6: Presentation of Findings

• Final Presentation: Compile and present your findings, demonstrating your analytical and storytelling skills.

Evaluation

Your progress will be assessed through quizzes in each module, culminating in the final project presentation where you will demonstrate your understanding and application of data analysis techniques.

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This project is designed to help you become an effective IBM Professional Data Analyst, equipping you with the skills to navigate the complexities of data in today’s business environment. Your work will contribute to shaping the future skill requirements for your organization, helping it stay ahead in the competitive landscape.

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