Overview
This course covers foundational data analysis skills such as thinking like an analyst, gathering useful data, SQL queries, data cleaning, and more. Are you ready to be an analyst?
Syllabus
Introduction
- Beginning your data analysis journey
- What you should know
- Using the exercise files
1. Getting Started with Data Analysis
- Defining data analysis and data analyst
- Discovering if you are an analyst
- Organizational roles in data
- Understanding types of data job roles
- Discovering skills of the data analyst
2. Fundamentals of Data Understanding
- Learning to identify data
- Learning about data fields and types
- Dealing with the data you don’t have
- Learning syntax
- Learning basic SQL statements
- Challenge: Reading SQL
- Solution: Reading SQL
3. Key Elements to Understand when Starting Data Analysis
- Learning to interpret existing data
- Finding existing data
- Cleaning data
- Understanding data and workflow
- Understanding joins
- Working with joins and validation
- Challenge: Products are not categorized
- Solution: Products are not categorized
4. Getting Started with a Data Project
- Getting started with data projects
- Discovering common beginner mistakes
- Learning Excel datasets
- Learning database datasets
- Maintaining original data
- Understanding truths
5. Data Importing, Exporting, and Connections
- Learning about data governance
- Understanding source data
- Working with flat files
- Working with connections
- Creating datasets for others
6. Getting Started with Data Cleaning and Modeling
- Understanding ETL in data
- Cleaning data using Excel macros
- Cleaning data with Power Query
- Working with reusable data
- Modeling data with queries
- Modeling data in Power Query
- Challenge: Rename headers in Power Query
- Solution: Rename headers in Power Query
7. Applying Common Techniques for All Data Analysts
- Convert data in Power Query
- Finding and removing duplicates
- Changing case and replace values
- Combining data with merge columns
- Creating logical functions
- Building aggregate datasets
- Challenge: Count and amounts of products
- Solution: Count and amounts of products
- More resources for your learning data analytics journey
Conclusion