Path overview
You’ll learn the fundamentals of data analysis in Excel, including how to explore and extract data from datasets using SQL, how to perform descriptive statistical analysis, and how to present insights using dashboards and visualizations in Power BI.
Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser. You’ll apply your skills to several guided projects with realistic business scenarios to build your portfolio and prepare for your next interview.
By the end of the career path, you’ll be ready for the official Microsoft Power BI Data Analyst certification PL-300, an in-demand assessment that certifies your skills in Power BI.
Key skills
- Using and applying foundational math and statistics to perform data analysis
- Retrieving and manipulating data from databases using SQL
- Importing, preparing, analyzing, and summarizing data with Excel
- Conveying insights effectively to tell a story using Microsoft Power BI
Path outline
Part 1: Introduction to Data Analysis with Excel [5 courses]
Introduction to Data Analysis in Excel 3h
Objectives- Define, categorize, and evaluate data
- Identify ways data is used in business and everyday life
- Organize data
- Describe key steps of the data analysis process
Preparing Data in Excel 6h
Objectives- Import data into an Excel spreadsheet from more than one data source
- Organize data into a spreadsheet using worksheets and tables
- Clean, manipulate, and modify the data
- Consolidate the data for analysis
Visualizing Data in Excel 5h
Objectives- Visualize data using pie, column, histogram, line, scatter, and combo charts
- Select the appropriate data visualization
- Create charts using design principles
- Design visualizations for your intended audience
Exploring Data in Excel 4h
Objectives- Define descriptive statistics
- Identify the different types of descriptive statistics
- Identify when to use each descriptive statistic
- Apply and compare different descriptive statistics to a single column, to multiple columns, and to groups of data
- Create visualizations to explore and analyze data
Analyzing Data in Excel 4h
Objectives- Analyze data and discover business insights using PivotTables
- Identify trends over time in time-series data
- Summarize and visualize relationships between categorical and quantitative variables
- Confirm a relationship between an independent and dependent variable using linear regression
- Estimate the sensitivity of an output to given inputs
Part 2: Fundamentals of SQL [5 courses]
Introduction to SQL and Databases 2h
Objectives- Define the structure of SQL
- Create basic queries to extract data from tables in a database
- Define databases
- Identify different versions of SQL
- Write good SQL code
Filtering and Sorting Data in SQL 4h
Objectives- Define binary operations and functions
- Define datatypes
- Filter results based on logical constraints
- Order results
Summarizing Data in SQL 3h
Objectives- Employ SQL to compute statistics
- Provide statistics by group
- Filter results over groups
Combining Tables in SQL Course 3h
Objectives- Combine tables using inner joins
- Employ different types of joins
- Employ other SQL clauses with joins
- Join on complex conditions
- Employ set operators like UNION and EXCEPT
SQL Subqueries 5h
Objectives- Nest a query inside another query
- Employ different types of subqueries
- Employ common table expressions
- Scale your project with complex queries
Part 3: Analyzing Data with Microsoft Power BI [5 courses]
Introduction to Data Analysis in Microsoft Power BI 4h
Objectives- Navigate Power BI and use its building blocks
- Import data from common sources into Power BI
- Rename objects, pivot data, and select valuable data for your analysis
- Simplify a complicated model and change data types
- Combine data and find anomalies
Model Data in Power BI 7h
Objectives- Design a data model in Power BI
- Understand dimensions, define data granularity, and work with relationships and cardinality
- Create measures using Data Analysis Expressions (DAX) in Power BI
- Optimize a model for performance in Power BI
Visualize data in Power BI 5h
Objectives- Create Power BI visuals
- Create a data-driven story using Power BI reports
- Design report layout and navigation
- Create dashboards in Power BI
Data Analysis in Power BI 3h
Objectives- Perform data analysis using Microsoft Power BI
- Group and bin data
- Perform time series analysis
- Apply artificial intelligence insights to your data
Manage Workspaces and Datasets in Power BI 2h
Objectives- Create and manage a workspace in Power BI
- Import and update assets in a Power BI workspace
- Configure data protection in a Power BI workspace
- Create dynamic reports with parameters
- Implement static and dynamic row-level security
The Dataquest guarantee
Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.
We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.
Master skills faster with Dataquest
Go from zero to job-ready
Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.
Build your project portfolio
Build confidence with our in-depth projects, and show off your data skills.
Challenge yourself with exercises
Work with real data from day one with interactive lessons and hands-on exercises.
Showcase your path certification
Impress employers by completing a capstone project and certifying it with an expert review.
Projects in this path
Guided Project: Preparing Data with Excel
In this guided project, you’ll import a dataset, organize it, clean it, and then consolidate it into a single table, preparing it for analysis.
Guided Project: Visualizing the Answer to Stock Questions Using Spreadsheet Charts
In this project, we will apply the knowledge and skills we developed in the preceding lessons to present stock data clearly and help answer important questions about the underlying data.
Guided Project: Identifying Customers Likely to Churn for a Telecommunications Provider
In this project, we’ll conduct an Exploratory Data Analysis (EDA) on data from a telecommunications provider to create profiles on customers that are at risk of churn.
Guided Project: Analyzing Retail Sales
Work with retail sales data to explore trends and relationships. Build basic models to confirm the statistical significance of your insights.
Guided Project: Customers and Products Analysis Using SQL
Work on a real-life project using SQL
Plus 3 more projects
Build your project portfolio with the Data Analyst in Python path.
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