Analytics and big data for accountants / Jim Lindell

By: Lindell, Jim [author]
Language: English Series: AICPAPublisher: Durham, NC : John Wiley & Sons, Inc, 2017Description: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781119512332 ; 9781119512363 (electronic bk.)Subject(s): Accounting -- Data processing | Big data -- Analysis | Accounting -- Information technologyGenre/Form: Electronic books.Online resources: Full text is available at Wiley Online Library Click here to view
Contents:
Table of contents Overview 1 Chapter 1 1-1 What Are Big Data and Analytics? 1-1 Practice Questions 1-13 Chapter 2 2-1 Big Data History Big Data Sources and Characteristics 2-1 Practice Questions 2-19 Chapter 3 3-1 What Are the Trends in Big Data? 3-1 Practice Questions 3-12 Chapter 4 4-1 What Are the Strategy and Business Applications of Big Data? 4-1 Practice Questions 4-13 Chapter 5 5-1 Big Data Platforms and Operating Tools 5-1 Practice Questions 5-21 Chapter 6 6-1 Big Data End User and Accounting Tools 6-1 Practice Questions 6-26 Chapter 7 7-1 Examples of Big Data 7-1 Practice Questions 7-17 Chapter 8 8-1 Big Data in the Accounting Department 8-1 Practice Questions 8-14 Chapter 9 9-1 Ethics and Privacy With Big Data 9-1 Practice Questions 9-17 Index 1 Solutions 1 Chapter 1 Solutions 1 Chapter 2 Solutions 2 Chapter 3 Solutions 4 Chapter 4 Solutions 5 Chapter 5 Solutions 6 Chapter 6 Solutions 8 Chapter 7 Solutions 10 Chapter 8 Solutions 12 Chapter 9 Solutions 14
Summary: Analytics is the new force driving business. Tools have been created to measure program impacts and ROI, visualize data and business processes, and uncover the relationship between key performance indicators, many using the unprecedented amount of data now flowing into organizations. Featuring updated examples and surveys, this dynamic book covers leading-edge topics in analytics and finance. It is packed with useful tips and practical guidance you can apply immediately. This book prepares accountants to: Deal with major trends in predictive analytics, optimization, correlation of metrics, and big data. Interpret and manage new trends in analytics techniques affecting your organization. Use new tools for data analytics. Critically interpret analytics reports and advise decision makers.
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Item type Current location Home library Call number Status Date due Barcode Item holds
EBOOK EBOOK COLLEGE LIBRARY
COLLEGE LIBRARY
658.05 L641 2017 (Browse shelf) Available CL-50286
Total holds: 0

Table of contents

Overview 1

Chapter 1 1-1

What Are Big Data and Analytics? 1-1

Practice Questions 1-13

Chapter 2 2-1

Big Data History Big Data Sources and Characteristics 2-1

Practice Questions 2-19

Chapter 3 3-1

What Are the Trends in Big Data? 3-1

Practice Questions 3-12

Chapter 4 4-1

What Are the Strategy and Business Applications of Big Data? 4-1

Practice Questions 4-13

Chapter 5 5-1

Big Data Platforms and Operating Tools 5-1

Practice Questions 5-21

Chapter 6 6-1

Big Data End User and Accounting Tools 6-1

Practice Questions 6-26

Chapter 7 7-1

Examples of Big Data 7-1

Practice Questions 7-17

Chapter 8 8-1

Big Data in the Accounting Department 8-1

Practice Questions 8-14

Chapter 9 9-1

Ethics and Privacy With Big Data 9-1

Practice Questions 9-17

Index 1

Solutions 1

Chapter 1 Solutions 1

Chapter 2 Solutions 2

Chapter 3 Solutions 4

Chapter 4 Solutions 5

Chapter 5 Solutions 6

Chapter 6 Solutions 8

Chapter 7 Solutions 10

Chapter 8 Solutions 12

Chapter 9 Solutions 14

Analytics is the new force driving business. Tools have been created to measure program impacts and ROI, visualize data and business processes, and uncover the relationship between key performance indicators, many using the unprecedented amount of data now flowing into organizations. Featuring updated examples and surveys, this dynamic book covers leading-edge topics in analytics and finance. It is packed with useful tips and practical guidance you can apply immediately.

This book prepares accountants to:

Deal with major trends in predictive analytics, optimization, correlation of metrics, and big data.
Interpret and manage new trends in analytics techniques affecting your organization.
Use new tools for data analytics.
Critically interpret analytics reports and advise decision makers.

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