Data Analytics in the Music Business


Authored by Liv Buli


Course Code: OMBUS-537

Accepting applications for the inaugural Sept. 2018 class!

3-Credit, Graduate Level Course

This course will help you gain a deep understanding of the role of data in the business of music, balancing theoretical concepts, illustrative case studies, and practical application. When used correctly, data about artists and music serve as invaluable tools, allowing companies to measure performance accurately and understand the current market, informing decisions with real facts and figures, and providing insight into how existing processes may be made more efficient. You will learn how to implement a data strategy, including its benefits and risks, and gauge how difficult it can be to obtain accurate data. You will apply data analysis, extract data, and perform queries, and you’ll also learn to represent data visually in ways that help with communication and understanding. 

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By the end of the course, you will be able to:

  • Select the appropriate methods, fundamentals, environments, and occasions to apply data analysis
  • Write SQL (Structured Query Language) and Excel formulas in order to extract and analyze data
  • Determine which types of questions it is possible to ask of the data available
  • Apply data to the business of music from album releases to promotional strategies and touring
  • Analyze statistical concepts
  • Assess any available data set, its source, and suggested application
  • Visually represent and communicate data
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Overview Syllabus Requirements Instructors Request Info


Lesson 1: What’s Data Got to Do with It?

  • Introduction to Data for the Music Industry
  • Sales, Radio Spins, Streaming, and Social Data
  • What Is a Data Strategy? Using Data for the Business of Music - Tour Planning, Promotion, Campaigns, and More
  • Case Study: Bombadil
  • Assignment 1: Research a Data Strategy Example

Lesson 2: The Trouble with Percentages Is . . . (Introduction to Statistics)

  • Introduction to Statistics and the Need for Context
  • What are Summary Statistics and Why Are They Useful?
  • Variables: Categorical vs. Numerical
  • Data Collection and Sampling
  • Correlation Does Not Mean Causation
  • Assignment 2: OpenIntro Statistics Exercises

Lesson 3: Charts, Graphs, and Plots: Tools for Examining our Data

  • Exploring Numerical Data, Scatterplots, Histograms, and Calculating Mean
  • Skew, Distribution, Standard Deviation, and Variance
  • Mean vs. Median
  • What Is an Outlier and Why Is it Important?
  • Practical Application Using Google Sheets: The Value of Context
  • Assignment 3: Select an Artist or Band for Case Study Analysis

Lesson 4: Gathering Information

  • What Data Is Available to Us?
  • How Do We Collect and Store Data?
  • What Is a Database?
  • Why Is Data Gathering Such a Difficult Task?
  • What Is a Data Scientist vs. a Data Engineer?
  • Assignment 4: Analyze Data

Lesson 5: Data-Driven Research A&R

  • Case Study: Discovering Lorde
  • Interview with Research A&R Rep
  • Different Approaches to A&R Analysis
  • The Limitations to a Data-Driven Approach to A&R
  • What Defines Success
  • Assignment 5: Define Success for Your Chosen Artist/Band

Lesson 6: The Basics of Computer Programming

  • Introduction to Programming Languages, Including SQL, Python, R, and D3.js
  • Extracting Data with SQL
  • The Data Scientist’s Toolkit: Python, R, and More
  • Javascript and D3 (Data-Driven Documents) Library
  • Interview with a Data Scientist
  • Assignment 6: Analyze Covered Programming Languages

Lesson 7: SQL - Extracting Data

  • Databases, Tables, and SQL Queries
  • Trying Our Hand at SQL
  • Retrieving Data on Artists, Based on Genre
  • Assignment 7: Define the Ideal Structure for a SQL Query

Lesson 8: SQL - Manipulating Data

  • Sum, Count, Order By
  • Cleaning Data - Insert and Delete
  • Inner Join, Selecting Null Values
  • Interview - Data Collection at Interactive, Music Streaming Services
  • Assignment 8: Submit Queries for Musical Tutorial

Lesson 9: Tour Planning with Data

  • Case Study - Where Should [Insert Artist] Perform?
  • What Type of Data Is Relevant? (Geo)
  • What Limitations Are There to a Data-Driven Approach to Tour Planning?
  • Interview with Booking Agent/Artist Manager
  • Assignment 9: Build a Tour Schedule Using Data for Your Artist/Band

Lesson 10:  Show, Don’t Tell - Data Visualization and Information Graphics

  • What Is Data Visualization, and Why Do We Need It?
  • From Bar Charts to Boxplots
  • Practical Application - Building Graphs with Google Sheets
  • Taking It to the Next Level: Interactive vs. Static
  • Presenting Data - Making Your Case Using Charts, Graphs, and Plots
  • Assignment 10: Build a Static Graphic for Your Artist/Band

Lesson 11: Marketing and Promo with Data

  • Case Study - What Promotional Strategy Should [Insert Artist] Employ?
  • The Case for Windowing?
  • Social Media Marketing and Measurement
  • Interview - What Role Does Data Play in Marketing an Artist?
  • What Limitations Are There to a Data-Driven Approach to Business Strategy?
  • Build a Marketing Strategy for Your Artist/Band
  • Assignment 11: Finalize Your Artist/Band Case Study

Lesson 12: Indexes and Benchmarks: Setting New Standards for the Industry

  • Building Context - Artist Stages/Benchmarking
  • Building Benchmark Values
  • What Is the Ideal Data Set or Data Point?
  • What Is the Blockchain and Impact on Future Music Data?
  • Does Data Add Value to the Music Industry?
  • The Future of Data


Required Textbooks

Software Requirements

  • Google account
  • Next Big Sound (student) account

Mac Users

  • OS X 10.9 Mavericks or higher (click here for system requirements)
  • Latest version of Google Chrome

Windows Users

  • Windows 7 or higher (click here for system requirements)
  • Latest version of Google Chrome

Hardware Requirements

  • 500 MB hard drive space
  • Webcam
  • Speakers or headphones
  • Internet connection with at least 4 Mbps download speed ( to verify or download the Speedtest by Ookla app from your mobile app store)



Author & Instructor

Liv Buli is a data journalist and author living in Olive, New York. Previously a senior music data journalist with Pandora Media and Next Big Sound, Buli has spent most of her career working at the intersection of storytelling, data science, and visualization, thinking about how best to tell stories with data and speaking at conferences around the world. She is also the author of Penelope Pie's Pizza Party, the first book in the Vizkidz series: a collection of books that teach the fundamental concepts of data visualization and analysis to children.


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