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Data Science for Marketing Analytics - Second Edition

You're reading from Data Science for Marketing Analytics - Second Edition

Product type Book

Published in Sep 2021

Publisher Packt

ISBN-13 9781800560475

Pages 636 pages

Edition 2nd Edition

Languages

Concepts

Authors (3):

Mirza Rahim Baig

Gururajan Govindan

Vishwesh Ravi Shrimali

View More author details

Table of Contents (11) Chapters

Preface

1. Data Preparation and Cleaning

2. Data Exploration and Visualization

3. Unsupervised Learning and Customer Segmentation

4. Evaluating and Choosing the Best Segmentation Approach

5. Predicting Customer Revenue Using Linear Regression

6. More Tools and Techniques for Evaluating Regression Models

7. Supervised Learning: Predicting Customer Churn

8. Fine-Tuning Classification Algorithms

9. Multiclass Classification Algorithms

Appendix

Data Models and Structured Data

When you build an analytical solution, the first thing that you need to do is to build a data model. A data model is an overview of the data sources that you will be using, their relationships with other data sources, where exactly the data from a specific source is going to be fetched, and in what form (such as an Excel file, a database, or a JSON from an internet source).

Note

Keep in mind that the data model evolves as data sources and processes change.

A data model can contain data of the following three types:

Structured Data: Also known as completely structured or well-structured data, this is the simplest way to manage information. The data is arranged in a flat tabular form with the correct value corresponding to the correct attribute. There is a unique column, known as an index, for easy and quick access to the data, and there are no duplicate columns. For example, in Figure 1.1, employee_id is the unique column. Using the data...

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Authors (3)

Mirza Rahim Baig

Mirza Rahim Baig is a Data Science and Artificial Intelligence leader with over 13 years of experience across e-commerce, healthcare, and marketing. He currently holds the position of leading Product Analytics at Marketing Services for Zalando, Europe's largest online fashion platform. In addition, he serves as a Subject Matter Expert and faculty member for MS level programs at prominent Ed-Tech platforms and institutes in India. He is also the lead author of two books, 'Data Science for Marketing Analytics' and 'The Deep Learning Workshop,' both published by Packt. He is recognized as a thought leader in my field and frequently participates as a guest speaker at various forums.

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Gururajan Govindan

Gururajan Govindan is a data scientist, intrapreneur, and trainer with more than seven years of experience working across domains such as finance and insurance. He is also an author of The Data Analysis Workshop, a book focusing on data analytics. He is well known for his expertise in data-driven decision-making and machine learning with Python.

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Vishwesh Ravi Shrimali

Vishwesh Ravi Shrimali graduated from BITS Pilani, where he studied mechanical engineering, in 2018. He also completed his Masters in Machine Learning and AI from LJMU in 2021. He has authored - Machine learning for OpenCV (2nd edition), Computer Vision Workshop and Data Science for Marketing Analytics (2nd edition) by Packt. When he is not writing blogs or working on projects, he likes to go on long walks or play his acoustic guitar.

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