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Business Intelligence, Analytics, Data Science, and AI, 5th Edition by Ramesh Sharda, Dursun Delen, Efraim Turban Chapter 3 Descriptive Analytics I: Nature of Data, Big Data, and Statistical Modeling$7.99
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Business Intelligence, Analytics, Data Science, An
Business Intelligence, Analytics, Data Science, an
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Business Intelligence, Analytics, Data Science, and AI, 5th Edition by Ramesh Sharda, Dursun Delen, Efraim Turban Chapter 3 Descriptive Analytics I: Nature of Data, Big Data, and Statistical Modeling
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Business Intelligence, Analytics, Data Science, an
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Business Intelligence, Analytics, Data Science, An
Business Intelligence, Analytics, Data Science, and AI, 5th Edition by Ramesh Sharda, Dursun Delen, Efraim Turban
Chapter 3 Descriptive Analytics I: Nature of Data, Big Data, and Statistical Modeling
1) To respond to the market challenges, SiriusXM decided to focus on production efficiency.
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Business Intelligence, Analytics, Data Science,
and AI, 5th Edition by Ramesh Sharda, Dursun
Delen, Efraim Turban
Chapter 3 Descriptive Analytics I: Nature of Data, Big Data, and Statistical Modeling
1) To respond to the market challenges, SiriusXM decided to focus on production efficiency.
Answer: FALSE
Diff: 1 Page Ref: 147
2) Data is the contextualization of information, also called "information set in context."
Answer: FALSE
Diff: 1 Page Ref: 151
3) Data is the main ingredient, or row material, for any BI, data science, and business analytics
initiative.
Answer: TRUE
Diff: 2 Page Ref: 151
4) Predictive algorithms generally require a flat file with a target variable, so making data
analytics ready for prediction means that data sets must be transformed into a flat-file format and
made ready for ingestion into those predictive algorithms.
Answer: TRUE
Diff: 2 Page Ref: 152
5) Data source reliability means that data are correct and are a good match for the analytics
problem.
Answer: FALSE
Diff: 1 Page Ref: 153
6) Data accessibility means that the data are easily and readily obtainable.
Answer: TRUE
Diff: 3 Page Ref: 89
7) Structured data is what data mining algorithms use and can be classified as categorical or
numeric.
Answer: TRUE
Diff: 1 Page Ref: 155
8) Interval data are numerical variables that have an absolute zero reference point.
Answer: FALSE
Diff: 2 Page Ref: 156
10) Ordinal data is a sub-part of the numerical data category within the data taxonomy.
Answer: FALSE
Diff: 2 Page Ref: 155
11) Unstructured data includes multimedia data, textual data, and web log data.
Answer: TRUE
Diff: 2 Page Ref: 155
12) Datum is what we name the plural form of data.
Answer: FALSE
Diff: 2 Page Ref: 155
13) Data are often viewed as the lowest level of abstraction from which information and then
knowledge is derived.
Answer: TRUE
Diff: 2 Page Ref: 155
14) Data preprocessing is a tedious and time-demanding process necessary to convert the raw
real-world data into a well-refined form for analytics algorithms.
Answer: TRUE
Diff: 2 Page Ref: 157
15) In the first phase of data preprocessing, the data is cleaned for further transformation.
Answer: FALSE
Diff: 2 Page Ref: 158
16) Big data is defined solely by its sheer volume, which can be at the Exabyte or Zettabyte
levels.
Answer: FALSE
Diff: 2 Page Ref: 167
17) A clear business need is amongst the most important big data analytics success factors.
Answer: TRUE
Diff: 2 Page Ref: 171
18) Both commercial and opensource MapReduce libraries are available that provide a wide
range of analytic capabilities.
Answer: TRUE
Diff: 2 Page Ref: 178
19) Hadoop is a big data technology that distributes the analytics processing of very large multi-
structured data files across a large cluster of machines.
Answer: FALSE
Diff: 2 Page Ref: 171
, 20) The main benefit of Hadoop is that it allows enterprises to process and analyze large volumes
of unstructured and semi-structured data in a cost and time-effective manner.
Answer: TRUE
Diff: 2 Page Ref: 177
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