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The Resource Interview questions in business analytics, Bhasker Gupta

Interview questions in business analytics, Bhasker Gupta

Creator
Author
Summary
Discover relevant questions--and detailed answers--to help you prepare for job interviews and break into the field of analytics. This book contains more than 200 questions based on consultations with hiring managers and technical professionals already working in analytics. Interview Questions in Business Analytics: How to Ace Interviews and Get the Job You Want fills a gap in information on business analytics for job seekers. Bhasker Gupta, the founder and editor of Analytics India Magazine, has come up with more than 300 questions job applicants are likely to face in an interview. Covering data preparation, statistics, analytics implementation, as well as other crucial topics favored by interviewers, this book: Provides 300+ interview questions often asked by recruiters and hiring managers in global corporations Offers short and to-the-point answers to the depth required, while looking at the problem from all angles Provides a full range of interview questions for jobs ranging from junior analytics to senior data scientists and managers Offers analytics professionals a quick reference on topics in analytics Using a question-and-answer format from start to finish, Interview Questions in Business Analytics: How to Ace Interviews and Get the Job You Want will help you grasp concepts sooner and with deep clarity. The book therefore also serves as a primer on analytics and covers issues relating to business implementation. You will learn about not just the how and what of analytics, but also the why and when. This book will thus ensure that you are well prepared for interviews--putting your dream job well within reach. Business analytics is currently one of the hottest and trendiest areas for technical professionals. With the rise of the profession, there is significant job growth. Even so, it's not easy to get a job in the field, because you need knowledge of subjects such as statistics, databases, and IT services. Candidates must also possess keen business acumen. What's more, employers cast a cold critical eye on all applicants, making the task of getting a job even more difficult. What You'll Learn The 300 questions in this book cover such topics as: • The different types of data used in analytics • How analytics are put to use in different industries • The process of hypothesis testing • Predictive vs. descriptive analytics • Correlation, regression, segmentation and advanced statistics • Predictive modeling Who This Book Is For Those aspiring to jobs in business analytics, including recent graduates and technical professionals looking for a new or better job. Job interviewers will also find the book helpful in preparing interview questions
Language
eng
Work
Publication
Extent
1 online resource (xxiii, 94 pages)
Note
Includes index
Contents
  • At a Glance; Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Introduction to Analytics; Q: What is analytics?; Q: Why has analytics become so popular today?; Q: What has led to the explosion of analytics into the mainstream?; Q: How is analytics used within e-commerce and marketing?; Q: How is analytics used within the financial industry?; Q: How is analytics used within the retail industry?; Q: How is analytics used in other industries?; Q: What are the various steps undertaken in the process of performing analytics?
  • Q: Can you explain why it's important to have an understanding of business?Q: Why is business understanding such an integral part of analytics?; Q: What is modeling?; Q: What are optimization techniques?; Q: What is model evaluation?; Q: What is in-sample and out-of-sample testing?; Q: What are response models?; Q: What is model lift?; Q: Can you explain the deployment of an analytics model? Why is it important?; Q: How are predictive and descriptive analytics differentiated?; Q: How much can we rely on the results of analytics?; Q: Can you briefly summarize the tools used in analytics
  • Chapter 2: Data UnderstandingQ: What are the four types of data attributes?; Q: Can you explain the nominal scale in detail?; Q: What are some of the pitfalls associated with the nominal scale?; Q: Can you explain the ordinal scale in detail?; Q: What are some of the pitfalls of the ordinal scale?; Q: Where are ordinal scales most commonly used?; Q: What is meant by data coding?; Q: Can you explain the interval scale in detail?; Q: What are the two defining principles of an interval scale?; Q: What are the characteristics of the ratio scale?
  • Q: What are the limitations of scale transformation?Q: In 2014, Forbes ranked Bill Gates as the richest man in the United States. According to what scale of measurement is this ranking?; Q: How are continuous and discrete variables differentiated?; Q: How are primary and secondary data differentiated?; Q: Broadly, what are the four methods of primary data collection?; Q: What is meant by primary data collection by observation?; Q: What is primary data collection by in-depth interviewing?; Q: What is primary data collection by focus groups?
  • Q: What is primary data collection by questionnaires and surveys?Q: What is data sampling?; Q: What are the different types of sampling plans?; Q: What is simple random sampling?; Q: What is stratified random sampling?; Q: What is cluster sampling?; Q: What are the different errors involved in sampling?; Q: What causes a sampling error?; Q: What is a non-sampling error?; Q: What are the three types of non-sampling errors?; Q: Can you identify some errors in data acquisition?; Q: When does selection bias occur?; Q: What is data quality?; Q: What is data quality assurance?
Isbn
9781484205990
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-1-4842-0599-0
Instance
Label
Interview questions in business analytics
Title
Interview questions in business analytics
Statement of responsibility
Bhasker Gupta
Creator
Author
Subject
Genre
Language
eng
Summary
Discover relevant questions--and detailed answers--to help you prepare for job interviews and break into the field of analytics. This book contains more than 200 questions based on consultations with hiring managers and technical professionals already working in analytics. Interview Questions in Business Analytics: How to Ace Interviews and Get the Job You Want fills a gap in information on business analytics for job seekers. Bhasker Gupta, the founder and editor of Analytics India Magazine, has come up with more than 300 questions job applicants are likely to face in an interview. Covering data preparation, statistics, analytics implementation, as well as other crucial topics favored by interviewers, this book: Provides 300+ interview questions often asked by recruiters and hiring managers in global corporations Offers short and to-the-point answers to the depth required, while looking at the problem from all angles Provides a full range of interview questions for jobs ranging from junior analytics to senior data scientists and managers Offers analytics professionals a quick reference on topics in analytics Using a question-and-answer format from start to finish, Interview Questions in Business Analytics: How to Ace Interviews and Get the Job You Want will help you grasp concepts sooner and with deep clarity. The book therefore also serves as a primer on analytics and covers issues relating to business implementation. You will learn about not just the how and what of analytics, but also the why and when. This book will thus ensure that you are well prepared for interviews--putting your dream job well within reach. Business analytics is currently one of the hottest and trendiest areas for technical professionals. With the rise of the profession, there is significant job growth. Even so, it's not easy to get a job in the field, because you need knowledge of subjects such as statistics, databases, and IT services. Candidates must also possess keen business acumen. What's more, employers cast a cold critical eye on all applicants, making the task of getting a job even more difficult. What You'll Learn The 300 questions in this book cover such topics as: • The different types of data used in analytics • How analytics are put to use in different industries • The process of hypothesis testing • Predictive vs. descriptive analytics • Correlation, regression, segmentation and advanced statistics • Predictive modeling Who This Book Is For Those aspiring to jobs in business analytics, including recent graduates and technical professionals looking for a new or better job. Job interviewers will also find the book helpful in preparing interview questions
Cataloging source
N$T
http://library.link/vocab/creatorName
Gupta, Bhasker
Dewey number
331.702
Illustrations
illustrations
Index
index present
LC call number
HF5381
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/subjectName
  • Business
  • Interviewing
  • BUSINESS & ECONOMICS
  • POLITICAL SCIENCE
  • Business
  • Interviewing
  • Computer Science
  • Information Systems and Communication Service
  • Computer networking & communications
  • Databases
Label
Interview questions in business analytics, Bhasker Gupta
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-1-4842-0599-0
Instantiates
Publication
Distribution
Copyright
Note
Includes index
Antecedent source
unknown
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • At a Glance; Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Introduction to Analytics; Q: What is analytics?; Q: Why has analytics become so popular today?; Q: What has led to the explosion of analytics into the mainstream?; Q: How is analytics used within e-commerce and marketing?; Q: How is analytics used within the financial industry?; Q: How is analytics used within the retail industry?; Q: How is analytics used in other industries?; Q: What are the various steps undertaken in the process of performing analytics?
  • Q: Can you explain why it's important to have an understanding of business?Q: Why is business understanding such an integral part of analytics?; Q: What is modeling?; Q: What are optimization techniques?; Q: What is model evaluation?; Q: What is in-sample and out-of-sample testing?; Q: What are response models?; Q: What is model lift?; Q: Can you explain the deployment of an analytics model? Why is it important?; Q: How are predictive and descriptive analytics differentiated?; Q: How much can we rely on the results of analytics?; Q: Can you briefly summarize the tools used in analytics
  • Chapter 2: Data UnderstandingQ: What are the four types of data attributes?; Q: Can you explain the nominal scale in detail?; Q: What are some of the pitfalls associated with the nominal scale?; Q: Can you explain the ordinal scale in detail?; Q: What are some of the pitfalls of the ordinal scale?; Q: Where are ordinal scales most commonly used?; Q: What is meant by data coding?; Q: Can you explain the interval scale in detail?; Q: What are the two defining principles of an interval scale?; Q: What are the characteristics of the ratio scale?
  • Q: What are the limitations of scale transformation?Q: In 2014, Forbes ranked Bill Gates as the richest man in the United States. According to what scale of measurement is this ranking?; Q: How are continuous and discrete variables differentiated?; Q: How are primary and secondary data differentiated?; Q: Broadly, what are the four methods of primary data collection?; Q: What is meant by primary data collection by observation?; Q: What is primary data collection by in-depth interviewing?; Q: What is primary data collection by focus groups?
  • Q: What is primary data collection by questionnaires and surveys?Q: What is data sampling?; Q: What are the different types of sampling plans?; Q: What is simple random sampling?; Q: What is stratified random sampling?; Q: What is cluster sampling?; Q: What are the different errors involved in sampling?; Q: What causes a sampling error?; Q: What is a non-sampling error?; Q: What are the three types of non-sampling errors?; Q: Can you identify some errors in data acquisition?; Q: When does selection bias occur?; Q: What is data quality?; Q: What is data quality assurance?
Dimensions
unknown
Extent
1 online resource (xxiii, 94 pages)
File format
unknown
Form of item
online
Isbn
9781484205990
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Note
SpringerLink
Other control number
10.1007/978-1-4842-0599-0
Other physical details
illustrations (some color)
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)956376270
  • (OCoLC)ocn956376270
Label
Interview questions in business analytics, Bhasker Gupta
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-1-4842-0599-0
Publication
Distribution
Copyright
Note
Includes index
Antecedent source
unknown
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • At a Glance; Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Introduction to Analytics; Q: What is analytics?; Q: Why has analytics become so popular today?; Q: What has led to the explosion of analytics into the mainstream?; Q: How is analytics used within e-commerce and marketing?; Q: How is analytics used within the financial industry?; Q: How is analytics used within the retail industry?; Q: How is analytics used in other industries?; Q: What are the various steps undertaken in the process of performing analytics?
  • Q: Can you explain why it's important to have an understanding of business?Q: Why is business understanding such an integral part of analytics?; Q: What is modeling?; Q: What are optimization techniques?; Q: What is model evaluation?; Q: What is in-sample and out-of-sample testing?; Q: What are response models?; Q: What is model lift?; Q: Can you explain the deployment of an analytics model? Why is it important?; Q: How are predictive and descriptive analytics differentiated?; Q: How much can we rely on the results of analytics?; Q: Can you briefly summarize the tools used in analytics
  • Chapter 2: Data UnderstandingQ: What are the four types of data attributes?; Q: Can you explain the nominal scale in detail?; Q: What are some of the pitfalls associated with the nominal scale?; Q: Can you explain the ordinal scale in detail?; Q: What are some of the pitfalls of the ordinal scale?; Q: Where are ordinal scales most commonly used?; Q: What is meant by data coding?; Q: Can you explain the interval scale in detail?; Q: What are the two defining principles of an interval scale?; Q: What are the characteristics of the ratio scale?
  • Q: What are the limitations of scale transformation?Q: In 2014, Forbes ranked Bill Gates as the richest man in the United States. According to what scale of measurement is this ranking?; Q: How are continuous and discrete variables differentiated?; Q: How are primary and secondary data differentiated?; Q: Broadly, what are the four methods of primary data collection?; Q: What is meant by primary data collection by observation?; Q: What is primary data collection by in-depth interviewing?; Q: What is primary data collection by focus groups?
  • Q: What is primary data collection by questionnaires and surveys?Q: What is data sampling?; Q: What are the different types of sampling plans?; Q: What is simple random sampling?; Q: What is stratified random sampling?; Q: What is cluster sampling?; Q: What are the different errors involved in sampling?; Q: What causes a sampling error?; Q: What is a non-sampling error?; Q: What are the three types of non-sampling errors?; Q: Can you identify some errors in data acquisition?; Q: When does selection bias occur?; Q: What is data quality?; Q: What is data quality assurance?
Dimensions
unknown
Extent
1 online resource (xxiii, 94 pages)
File format
unknown
Form of item
online
Isbn
9781484205990
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Note
SpringerLink
Other control number
10.1007/978-1-4842-0599-0
Other physical details
illustrations (some color)
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)956376270
  • (OCoLC)ocn956376270

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