100% de satisfacción garantizada Inmediatamente disponible después del pago Tanto en línea como en PDF No estas atado a nada 4.2 TrustPilot
logo-home
Examen

Data Analytics for Accounting, Richardson - Exam Preparation Test Bank (Downloadable Doc)

Puntuación
-
Vendido
-
Páginas
204
Grado
A+
Subido en
24-05-2022
Escrito en
2021/2022

Description: Test Bank for Data Analytics for Accounting, Richardson, 2e prepares you efficiently for your upcoming exams. It contains practice test questions tailored for your textbook. Data Analytics for Accounting, Richardson, 2e Test bank allow you to access quizzes and multiple choice questions written specifically for your course. The test bank will most likely cover the entire textbook. Thus, you will get exams for each chapter in the book. You can still take advatange of the test bank even though you are using newer or older edition of the book. Simply because the textbook content will not significantly change in ne editions. In fact, some test banks remain identical for all editions. Disclaimer: We take copyright seriously. While we do our best to adhere to all IP laws mistakes sometimes happen. Therefore, if you believe the document contains infringed material, please get in touch with us and provide your electronic signature. and upon verification the doc will be deleted.

Mostrar más Leer menos
Institución
Grado











Ups! No podemos cargar tu documento ahora. Inténtalo de nuevo o contacta con soporte.

Libro relacionado

Escuela, estudio y materia

Institución
Grado

Información del documento

Subido en
24 de mayo de 2022
Número de páginas
204
Escrito en
2021/2022
Tipo
Examen
Contiene
Preguntas y respuestas

Temas

Vista previa del contenido

Data Analytics for Accounting, 1e (Richardson)
Chapter 1 Data Analytics in Accounting and Business

1) Data analytics is the process of evaluating data with the purpose of drawing
conclusions to address business questions.

2) The process of data analytics aims to transform raw information into data to create
value.

3) Data analytics has the potential to transform the manner in which companies run their
businesses; however, it is not practical in the near future.

4) Auditors can use social media to hear what customers are saying about a company and
compare this to inventory obsolescence and other estimates.

5) Data analytics allows auditors to glean insights that are beneficial to the client, without
breaching independence.

6) The predictive analytics is an important aspect of data analytics for auditors, but is not
applicable for tax accountants.

7) The I in IMPACT Cycle represents Identify the Question.

8) The M in IMPACT Cycle represents Master the Data.

9) The P in IMPACT Cycle represents Predict the Results.

10) The A in IMPACT Cycle represents Analyze the Data.

11) The C in IMPACT Cycle represents Continuously Track.

12) The T in IMPACT Cycle represents Track Outcomes.

13) Data normalization can reduce data redundancy and improve data integrity.

14) The IMPACT cycle is iterative, as insights are gained, outcomes are tracked, and new
questions are identified.

15) Data analytics professionals estimate that they spend between 25 percent and 70
percent of their time cleaning data so it can be analyzed.

16) Data analysis through data manipulation is performing basic analysis to understand
the quality of the underlying data and its ability to address the business question.

17) To be proficient in data analysis, accountants need to become data scientists.

,
,18) By developing an analytics mindset, accountants will be able to recognize when and
how data analytics can address business questions.

19) While it is important for accountants to clearly articulate the business problem,
drawing appropriate conclusions, based on the data, should be left to statisticians.

20) Analytic-minded accountants should report results of analysis in an accessible way to
each varied decision maker, along with their specific needs.

21) With a goal of giving organizations the information they need to make sound and
timely business decisions, data analytics often involves all of the following except:
A) technologies.
B) statistics.
C) growth.
D) databases.

22) Patterns discovered from ________ enable businesses to identify opportunities and
risks in order to better plan for ________.
A) past archives; the future
B) current data; the future
C) current data; today
D) past archives; today

23) Which of the following best describes the data analytics skill of descriptive data
analysis?
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that
allows enhanced analysis
D) comprehend the process needed to clean and prepare the data before analysis

24) Which of the following best describes the data analytics skill of data quality?
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) demonstrate the ability to sort, rearrange, merge, and reconfigure data in a manner that
allows enhanced analysis
D) comprehend the process needed to clean and prepare the data before analysis

25) Which of the following best describes the data analytics skill of data analysis through
data manipulation?
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that
allows enhanced analysis

, D) comprehend the process needed to clean and prepare the data before analysis
26) Which of the following best describes the data analytics skill of data scrubbing and
data preparation?
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) demonstrate the ability to sort, rearrange, merge and reconfigure data in a manner that
allows enhanced analysis
D) comprehend the process needed to clean and prepare the data before analysis

27) Which of the following best describes the data analytics skill of developing an
analytics mindset?
A) recognize when and how data analytics can address business questions
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) recognize what is meant by data quality, be it completeness, reliability or validity
D) comprehend the process needed to clean and prepare the data before analysis

28) Which of the following best describes the data analytics skill of data visualization and
data reporting?
A) recognize when and how data analytics can address business questions
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) recognize what is meant by data quality, be it completeness, reliability or validity
D) report results of analysis in an accessible way to each varied decision maker and their
specific needs

29) Which of the following best describes the data analytics skill of defining and
addressing problems through statistical data analysis?
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) demonstrate ability to sort, rearrange, merge and reconfigure data in a manner that
allows enhanced analysis
D) identify and implement an approach that will use statistical data analysis to draw
conclusions and make recommendations on a timely basis

30) While accountants don't need to become data scientists, they must know how to do
the following except:
A) Clearly articulate the business problem the company is facing
B) Communicate with the data scientists about specific data needs and understand the
underlying quality of the data
C) Build a data repository
D) Comprehend the process needed to clean and prepare the data before analysis
$40.49
Accede al documento completo:

100% de satisfacción garantizada
Inmediatamente disponible después del pago
Tanto en línea como en PDF
No estas atado a nada

Conoce al vendedor

Seller avatar
Los indicadores de reputación están sujetos a la cantidad de artículos vendidos por una tarifa y las reseñas que ha recibido por esos documentos. Hay tres niveles: Bronce, Plata y Oro. Cuanto mayor reputación, más podrás confiar en la calidad del trabajo del vendedor.
tb4u City University New York
Seguir Necesitas iniciar sesión para seguir a otros usuarios o asignaturas
Vendido
970
Miembro desde
3 año
Número de seguidores
776
Documentos
2374
Última venta
1 hora hace

4.0

158 reseñas

5
87
4
27
3
19
2
6
1
19

Recientemente visto por ti

Por qué los estudiantes eligen Stuvia

Creado por compañeros estudiantes, verificado por reseñas

Calidad en la que puedes confiar: escrito por estudiantes que aprobaron y evaluado por otros que han usado estos resúmenes.

¿No estás satisfecho? Elige otro documento

¡No te preocupes! Puedes elegir directamente otro documento que se ajuste mejor a lo que buscas.

Paga como quieras, empieza a estudiar al instante

Sin suscripción, sin compromisos. Paga como estés acostumbrado con tarjeta de crédito y descarga tu documento PDF inmediatamente.

Student with book image

“Comprado, descargado y aprobado. Así de fácil puede ser.”

Alisha Student

Preguntas frecuentes