Data Analytics

This is a 10-week part-time or 1-week accelerated course.

The Big Picture: Confidently make—and defend—critical decisions using the results of your data analysis.

Skills, Tools, & Strategies: Use Excel, SQL, and Tableau to spot trends and drive business decisions with real-world data.

Analytics in Practice: Share your insights and tell compelling stories using data visualizations and dashboards.

What You'll Learn:

Unit 1: Exploring Data with Excel
Understanding the Value of Data

• Explore the value of data.
• Work your way through the data analytics workflow.
• Unlock the power of Microsoft Excel to utilize its analytical tools — no matter your experience level.
• Practice applying the data analytics workflow to a sample business case.

Preparing Data in Excel

• Discuss data cleaning best practices.
• Review strategies to prepare and clean a data set.
• Practice asking the “right” questions of our data.

Referencing Data in Excel

• Use named ranges to easily reference data subsets.
• Use the VLOOKUP and HLOOKUP functions to manipulate data sets.
• Look up values in other tables using the functions INDEX and MATCH.

Aggregating Data in Excel

• Summarize data using pivot tables.
• Execute Excel aggregation commands (SUM, AVERAGE, COUNT, etc.) and their conditional variants (COUNTIF, COUNTBLANKS, etc.) to summarize data sets.
• Explore data using conditional formatting for categorization and analysis.

Visualizing Data in Excel

• Use scatter plots, bar graphs, and histograms to visualize data.
• Explore color theory and how it applies to data visualization.
• Build your own data dashboard using industry best practices.
• Apply visual design principles to your dashboard to present your findings clearly.

Applying Statistics for Data Analysis

• Understand the value of descriptive and inferential statistics.
• Learn to describe data and identify outliers using its mean, median, mode, range, and variance.
• Practice applying statistical functions in Excel.

Building Data Narratives

• Learn best practices for describing analysis techniques.
• Communicate insights and implications for stakeholders.
• Deliver short, effective presentations sharing your findings.
• Provide context for your audience by identifying and presenting the salient statistics.

Unit 2: Managing Data with SQL

Foundations of Databases and SQL

• Learn about data structures and the role of structured query language (SQL).
• Filter data using advanced SQL commands (Where, Group By, Having, Order By, Limit).
• Obtain data by creating relationships between tables using Joins.
• Gather filtered data using SQL Boolean operators (AND and OR) and SQL conditional operators (=,!=,>,<,IN, and BETWEEN).

Aggregating Data in SQL

• Create relationships between tables and data points (including has_many and many_to_many) using Join tables and multiple Joins.
• Write Boolean statements with SQL conditional operators (=, !=, >, <, IN, and BETWEEN).
• Summarize data sets by employing aggregation commands (“Sum,” “Average,” “Count,” etc.).
• Determine data trends by applying aggregation methods.

Using Logic and Functions in SQL

• Explain the differences between NULL and zero.
• Use SQL NULL to create Boolean functions and handle zeros.
• Apply string functions to manipulate how data is presented.
• Apply math functions to add value to the data you are working with.
• Apply date logic to your SQL queries.

Writing Efficient, Dynamic Queries and Subqueries

• Use CASE statements to structure data and create new attributes.
• Combine multiple subqueries into one using “WITH AS.”
• Optimize queries using WHERE, LIMIT, and COALESCE.

Unit 3: Communicating Data Analysis with Tableau

Exploring the Fundamentals of Tableau

• Get hands-on, practical experience navigating the Tableau software interface.
• Connect your data to Tableau and identify the best ways to visualize and display your results.

Visualizing Data and Text Manipulation in Tableau

• Use bubble graphs and a variety of visualizations to identify and communicate data insights.
• Create a number of calculated fields to clean and manipulate strings of text using LEFT, MID, FIND, and REPLACE.

Text and Sentiment Analysis in Tableau

• Use the Twitter web data connector to bring tweet data into Tableau.
• Analyze and visualize your data pull in Tableau in order to answer basic questions.

Designing Data Dashboards in Tableau

• Contextualize analysis results by creating Tableau dashboards.
• Incorporate charts and conditional formatting into your dashboard using supporting information specific to a particular data set.

Working with Data Across Excel, SQL, and Tableau

• Understand the use of specific data analysis software.
• Apply all the tools and skills you’ve acquired in Excel, SQL, and Tableau to analyze a data set from start to finish.

Final Project Presentations

• Identify strengths and areas for improvement in your analytical skills with feedback from peers, instructors, and guest panelists.