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Solution Manual for Data Analytics for Accounting 3rd Edition/ Chapter 1-3 Covered/ Practice Questions with 100% Correct Answers.

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Solution Manual for Data Analytics for Accounting 3rd Edition/ Chapter 1-3 Covered/ Practice Questions with 100% Correct Answers.

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Solution Manual for Data Analytics for Accounting
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Solution Manual for Data Analytics for Accounting

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Subido en
6 de octubre de 2024
Número de páginas
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Escrito en
2024/2025
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Examen
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Solution Manual for Data Analytics for Accounting 3rd Edition/
Chapter 1-3 Covered/ Practice Questions with 100% Correct
Answers.



Chapter 1 Questions with Correct Answers




Data analytics

✓ The process of evaluating big data to draw conclusions for business questions.



Volume

✓ One of the characteristics of big data, referring to the large amount of data being analyzed.



As mentioned in the chapter, which of the following is not a common way that data will need to be
cleaned after extraction and validation?

Multiple Choice

A. Remove headings and subtotals.

B. Format negative numbers.

C. Clean up trailing zeroes.

D. Correct inconsistencies across data. - ANSWER - C. Clean up trailing zeroes.



Why is Supplier ID considered to be a primary key for a Supplier table? –

✓ It contains a unique identifier for each supplier.



What are attributes that exist in a relational database that are neither primary nor foreign keys? –

✓ Descriptive attributes

, 2




what is Similarity matching –

✓ An approach in data analytics that identifies similar individuals based on known data about
them.



what is Clustering –

✓ An approach in data analytics that divides individuals into groups in a useful or meaningful way.



Variety –

✓ One of the characteristics of big data, referring to the different types and sources of data being
analyzed.



Veracity –

✓ One of the characteristics of big data, referring to the accuracy and reliability of the data being
analyzed.



Big Data Value –

✓ One of the characteristics of big data, referring to the potential insights and value that can be
derived from analyzing the data.



Velocity –

✓ One of the characteristics of big data, referring to the speed at which data is generated and
needs to be analyzed.



Analyzing data –

✓ The process of examining and interpreting data to identify patterns, relationships, and insights.



Testing hypotheses –

✓ A method of analyzing data by formulating and testing theories or assumptions.

, 3


Why is data analytics important to businesses? –

✓ CEOS think that data analytics create lasting value, and are strategically important



Data Engineer (Job and required skills)
✓ Converts raw data into usable data. Skills required:
Data modeling, Hardware, Networking, Database administration



Data Analyst (Job and required skills) –
✓ Uses the data to generate insights. Skills required:
Data transformation, Programming or coding, Business processes



Data Scientist (Job and required skills) –

✓ Uses data analytics and data engineering to predict the future using past data. Skills required:
Data modeling, Statistics, Programing/coding, high-level math



Business Analyst (Job and required skills) –

✓ Uses the insights and predictions to drive decisions that benefit and grow business. Skills
required: Data transformation, Business processes, Visualization



Asking further and better questions –

✓ A step in the data analytics process that involves refining and expanding the initial question
based on the insights gained from analysis.



what is Co-occurrence grouping –

✓ An approach in data analytics that discovers associations between individuals based on
transactions involving them.



what is Profiling –

✓ An approach in data analytics that characterizes the typical behavior of an individual, group, or
population by generating summary statistics about the data.
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