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Hadoop Blueprints

Hadoop Blueprints

By : Sudheesh Narayan, Anurag Shrivastava, Deshpande
5 (1)
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Hadoop Blueprints

Hadoop Blueprints

5 (1)
By: Sudheesh Narayan, Anurag Shrivastava, Deshpande

Overview of this book

If you have a basic understanding of Hadoop and want to put your knowledge to use to build fantastic Big Data solutions for business, then this book is for you. Build six real-life, end-to-end solutions using the tools in the Hadoop ecosystem, and take your knowledge of Hadoop to the next level. Start off by understanding various business problems which can be solved using Hadoop. You will also get acquainted with the common architectural patterns which are used to build Hadoop-based solutions. Build a 360-degree view of the customer by working with different types of data, and build an efficient fraud detection system for a financial institution. You will also develop a system in Hadoop to improve the effectiveness of marketing campaigns. Build a churn detection system for a telecom company, develop an Internet of Things (IoT) system to monitor the environment in a factory, and build a data lake – all making use of the concepts and techniques mentioned in this book. The book covers other technologies and frameworks like Apache Spark, Hive, Sqoop, and more, and how they can be used in conjunction with Hadoop. You will be able to try out the solutions explained in the book and use the knowledge gained to extend them further in your own problem space.
Table of Contents (9 chapters)
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Finding the right dataset


We need a good historical dataset to build our model. We will mine this dataset to build our model. To continue with the example to our fictitious company, Furnitica, we will use historical campaign response data from a previous campaign run by Furnitica.

This is synthetic data, which means it has been synthesized using a random data generation algorithm. A few sample rows in our dataset are presented in Table 2:

Age

Income

Gender

Folder

Response

61

30974

0

1

0

42

38260

0

3

0

40

20135

0

4

0

88

30645

0

5

0

58

38078

1

3

0

73

20445

0

4

0

34

66198

0

3

0

65

48657

0

2

0

68

39309

0

1

0

Table 2 Sample credit card approval data

This dataset is generated from the response data of a campaign after joining it with the data in the customer relationship management system of the company. In the dataset preparation step, we have removed several features which are not directly useful in building our model. As a result, our...

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