Liv Buli – Data Analytics in the Music Business
$2,650.00 Original price was: $2,650.00.$512.00Current price is: $512.00.
Digital Download: You will receive a download link via your order email after successful payment.
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.
Data Analytics in the Music Business
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.
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
Syllabus
Lesson 1 What’s Data Got to Do with It?
Lesson 2 Introduction to Statistics
Lesson 3 Charts, Graphs, and Plots: Tools for Examining our Data
Lesson 4 Data-Driven Research A&R
Lesson 5 Finding, Cleaning, and Storing Data
Lesson 6 Introduction to Predictive Analytics
Lesson 7 SQL: Extracting Data
Lesson 8 In Which SQL Meets Data Science . . . Performing Complex Functions on Multiple Tables
Lesson 9 Show, Don’t Tell: Data Visualization and Information Graphics
Lesson 10 Why Transparency and Context Matter
Lesson 11 What On Earth Is the Blockchain and Why Does it Matter?
Lesson 12 Indexes and Benchmarks: Summarizing What We’ve Learned and Setting New Standards for the Industry
Requirements
Proof of a Bachelor’s Degree
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Delivery Method
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