Hadoop for Finance Essentials
- Length: 168 pages
- Edition: 1
- Language: English
- Publisher: Packt Publishing
- Publication Date: 2015-04-30
- ISBN-10: 1784395161
- ISBN-13: 9781784395162
- Sales Rank: #4007716 (See Top 100 Books)
Harness big data to provide meaningful insights, analytics, and business intelligence for your financial institution
About This Book
- Explore practical big data use cases for banking, financial services, and the insurance sector to build your own financial models
- Develop solutions for small- and large-scale data projects on the Hadoop platform
- Get hands-on experience with various Hadoop tools for better insights into both risks and opportunities
Who This Book Is For
This book is perfect for developers, analysts, architects or managers who would like to perform big data analytics with Hadoop for the financial sector. This book is also helpful for technology professionals from other industry sectors who have recently switched or like to switch their business domain to financial sector. Familiarity with big data, Java programming, database and data warehouse, and business intelligence would be beneficial.
In Detail
With the exponential growth of data and many enterprises crunching more and more data every day, Hadoop as a data platform has gained a lot of popularity. Financial businesses want to minimize risks and maximize opportunities, and Hadoop, largely dominating the big data market, plays a major role.
This book will get you started with the fundamentals of big data and Hadoop, enabling you to get to grips with solutions to many top financial big data use cases including regulatory projects and fraud detection. It is packed with industry references and code templates, and is designed to walk you through a wide range of Hadoop components.
By the end of the book, you’ll understand a few industry leading architecture patterns, big data governance, tips, best practices, and standards to successfully develop your own Hadoop based solution.
Table of Contents
Chapter 1: Big Data Overview
Chapter 2: Big Data In Financial Services
Chapter 3: Hadoop In The Cloud
Chapter 4: Data Migration Using Hadoop
Chapter 5: Getting Started
Chapter 6: Getting Experienced
Chapter 7: Scale It Up
Chapter 8: Sustain The Momentum
