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.

Preparing Data in Excel

• Learn best practices for collecting and cleaning data in Excel to ensure accurate analysis results.
• Manipulate real-world data sets using advanced nested logical functions (IF, OR, and AND).

Cleaning Data in Excel

• Clean large, unruly data sets by removing duplicate rows and performing text manipulations.
• Transform and rearrange columns and rows within spreadsheets to prepare data for analysis.
• Gain insight into data analysis by manipulating data formats.

Referencing Data in Excel

• 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.

Visualizing Data in Excel

• Derive insights from data by highlighting cells based on conditionals.
• 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.
• Make predictions about larger populations using sample data.

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.

Understanding the Fundamentals of Databases and SQL

• Practice the fundamentals of Structured Query Language (SQL).
• Use database schema to design appropriate queries using SQL.
• Explore the differences between relational databases (tabular data storage) and document-based databases (key-value pairs).

Querying Large Databases in SQL

• Collect data using standard SQL commands (Create, Update, Truncate, etc.).
• 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.
• Write Boolean statements with SQL conditional operators (=,!=,>,<,IN, and BETWEEN) and null functions (“IS NULL,” “IS NOT NULL,” and “NVL”).
• Clean data using SQL mathematical functions (ABS, SIGN, MOD, etc.).
• Summarize data sets by employing aggregation commands (“Sum,” “Average,” “Count,” etc.).
• Determine data trends by applying aggregation methods.

Writing Efficient, Dynamic Queries

• Use CASE statements to structure data and create new attributes.
• Combine multiple subqueries into one using “WITH AS.”

Creating a Local Database

• Create a local database using data sets you bring into the classroom.
• Upload and export data using a local database.

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 Mapping in Tableau

• Use bubble graphs to visualize data.
• Display geocoded information for your data.

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.