About This Chapter
Data Modeling for Marketing - Chapter Summary
This corporate training chapter presents data modeling for marketing in an easy-to-follow format. Work with your employees on topics such as the uses of data modeling and the use of predictive marketing in business. Utilize this chapter to train new employees, head up a meeting or run a training workshop.
How It Helps
- Includes examples: In addition to learning about the use of Python, R and Hadoop for marketing analytics, your teams will also review examples of each to see how they work in a real-life application.
- Offers knowledge: After finishing this chapter, your employees will understand more about the uses for data modeling and predictive modeling.
- Builds confidence: Employees who understand these marketing concepts about data modeling will feel more confident completing their job duties.
This chapter is designed to assist your employees in doing the following:
- Define data modeling as it pertains to marketing and recognize its uses
- Outline the challenges in data modeling
- Examine predictive modeling as it is used in business and marketing
- Discuss the benefits of using R in marketing analytics
- Use Python as it relates to marketing analytics
- Explain why it's beneficial to use Hadoop for marketing analytics
1. Data Modeling in Marketing: Definition & Uses
In this lesson, we'll define data modeling. You'll learn about its uses in gaining valuable customer information, creating marketing initiatives, and evaluating marketing campaigns.
2. Challenges in Data Modeling for Marketing
In this lesson, we'll define data modeling and discuss the challenges in the process, including garbage in and garbage out and simplicity versus complex models.
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