The Data Analyst’s Toolkit: Excel, SQL, Python, Power BI

Data Mastery for the Modern Analyst: Excel, SQL, Python, and Power BI Techniques

Created by: Digital Learning Academy
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What Will I Learn?

• The roles and responsibilities of a data analyst
• The importance of data-driven decision-making in organizations.
• How to use Microsoft Excel for data manipulation and analysis.
• Data cleaning and formatting techniques in Excel.
• How to create and use pivot tables
• Data visualization techniques using Excel charts.
• Writing basic SQL queries for data retrieval from relational databases.
• Advanced SQL techniques, such as filtering, sorting, aggregating, and joining multiple tables.
• The basics of the Python programming language for data analysis.
• How to use Python libraries like Pandas for data manipulation.
• Data visualization techniques using Python libraries such as Matplotlib.
• Connecting to data sources, data cleaning, and transformation in Power BI.
• Creating interactive dashboards and reports using Power BI.

Requirements

• Basic computer literacy: Students should be comfortable using computers and navigating various software applications, as well as have a general understanding of file management.
• Familiarity with Microsoft Office Suite: A basic understanding of Microsoft Office applications, particularly Excel, will be helpful for students as they dive into more advanced data analysis techniques using Excel.
• Problem-solving mindset: A curiosity for solving problems and a willingness to explore various approaches to data analysis will help students succeed in this course.
• No prior programming experience is required, but a basic understanding of programming concepts and logic will be beneficial when learning Python and SQL.
• Access to required software: Students should have access to a computer with Microsoft Excel, Power BI, and a Python development environment (e.g., Anaconda) installed. Access to a SQL database environment (e.g., MySQL, PostgreSQL, or SQL Server) is also recommended for practicing SQL queries.

Target audience

• Aspiring data analysts: Individuals who want to start a career in data analysis and are looking to acquire foundational skills in the field.
• Professionals seeking a career change: Professionals from other fields who want to transition to a data analysis role and need to develop their skillset in the most relevant tools and techniques.
• Existing data analysts: Data analysts who want to expand their knowledge of specific tools, improve their proficiency, or stay up-to-date with the latest industry trends.
• Business professionals and managers: Individuals involved in decision-making processes who want to leverage data-driven insights to make more informed decisions and gain a better understanding of the tools used by their data analysis teams.
• Students: College or university students studying business, economics, computer science, or other related fields who want to complement their academic knowledge with practical skills in data analysis.
• Researchers: Professionals involved in research who need to analyze and visualize large datasets to extract meaningful insights.
• Small business owners and entrepreneurs: Individuals who want to utilize data analysis techniques to optimize their business operations, improve customer experience, or identify new opportunities for growth.
• Freelancers and consultants: Professionals who provide data analysis services to clients and want to expand their toolkit to offer a wider range of services.
• Overall, this course is designed for anyone looking to acquire the skills necessary to efficiently analyze, visualize, and communicate data insights using Excel, SQL, Python, and Power BI.