Question 1

A gigabyte of data can contain ________.

Accepted Answer

A)  a single character of text 
B)  all the X-rays in a large hospital 
C)  a small novel 
D)  Beethoven's 5th Symphony 
A)  a single character of text 
B)  all the X-rays in a large hospital 
C)  a small novel 
D)  Beethoven's 5th Symphony

Question 2

Achieving value through big data requires a thorough understanding of the goals and objectives of a business.

Accepted Answer

A) True 
 B)False

Question 3

Structured querying language is a language developed by IBM and used to access and update data stored in a database.

Accepted Answer

A) True 
 B)False

Question 4

Streaming data, the continuous transfer of data from numerous sources in different formats, cannot be included to capture customer data.

Accepted Answer

A) True 
 B)False

Question 5

A common adage used in data management and utilization circles about poor data quality is

Accepted Answer

A)  "a bad workman always blames his tools." 
B)  "a cat has nine lives." 
C)  "garbage in, garbage out." 
D)  "adversity and loss make a man wise." 
A)  "a bad workman always blames his tools." 
B)  "a cat has nine lives." 
C)  "garbage in, garbage out." 
D)  "adversity and loss make a man wise."

Question 6

In data aggregation, employing the COUNT () function within a dataset returns the

Accepted Answer

A)  average value within the dataset. 
B)  sum of values within the dataset. 
C)  number of rows corresponding to a certain feature. 
D)  maximum value within the dataset. 
A)  average value within the dataset. 
B)  sum of values within the dataset. 
C)  number of rows corresponding to a certain feature. 
D)  maximum value within the dataset.

Question 7

In data aggregation, the ________ function helps in obtaining the total values within a dataset.

Accepted Answer

A)  SUM () 
B)  MAX () 
C)  MIN () 
D)  AVG () 
A)  SUM () 
B)  MAX () 
C)  MIN () 
D)  AVG ()

Question 8

Which of following characteristics of big data means the data can be converted into meaningful, quality information that can be used to achieve tangible business benefits?

Accepted Answer

A)  velocity 
B)  variety 
C)  value 
D)  volume 
A)  velocity 
B)  variety 
C)  value 
D)  volume

Question 9

Data inconsistencies can lead to uncoordinated strategic decision making and embarrassing dilemmas for businesses.

Accepted Answer

A) True 
 B)False

Question 10

Hadoop, a data warehouse built using HIVE, provides SQL-like query to access data stored in different file systems and databases that are used by HIVE.

Accepted Answer

A) True 
 B)False

Question 11

In the context of data preparation, a power calculation helps determine

Accepted Answer

A)  if any data observations have a considerable distance to other data clusters. 
B)  whether an existing, valuable customer is likely to leave the business. 
C)  the what, when, and who of the analysis. 
D)  what outcomes will be estimated from a sample with a sufficient level of precision. 
A)  if any data observations have a considerable distance to other data clusters. 
B)  whether an existing, valuable customer is likely to leave the business. 
C)  the what, when, and who of the analysis. 
D)  what outcomes will be estimated from a sample with a sufficient level of precision.

A gigabyte of data can contain ________.

Achieving value through big data requires a thorough understanding of the goals and objectives of a business.

Structured querying language is a language developed by IBM and used to access and update data stored in a database.

Streaming data, the continuous transfer of data from numerous sources in different formats, cannot be included to capture customer data.

A common adage used in data management and utilization circles about poor data quality is

In data aggregation, employing the COUNT () function within a dataset returns the

In data aggregation, the ________ function helps in obtaining the total values within a dataset.

Which of following characteristics of big data means the data can be converted into meaningful, quality information that can be used to achieve tangible business benefits?

Data inconsistencies can lead to uncoordinated strategic decision making and embarrassing dilemmas for businesses.

Hadoop, a data warehouse built using HIVE, provides SQL-like query to access data stored in different file systems and databases that are used by HIVE.

In the context of data preparation, a power calculation helps determine

Introduction to Marketing Analytics

Exploratory Data Analysis Using Cognitive Analytics

Data Visualization

Regression Analysis

Neural Networks

Automated Machine Learning

Cluster Analysis

Market Basket Analysis

Natural Language Processing - Text Mining and Sentiment Analysis

Social Network Analysis

Web Analytics

Filters

Exam 2: Data Management

A gigabyte of data can contain ________.

Achieving value through big data requires a thorough understanding of the goals and objectives of a business.

Structured querying language is a language developed by IBM and used to access and update data stored in a database.

Streaming data, the continuous transfer of data from numerous sources in different formats, cannot be included to capture customer data.

A common adage used in data management and utilization circles about poor data quality is

In data aggregation, employing the COUNT () function within a dataset returns the

In data aggregation, the ________ function helps in obtaining the total values within a dataset.

Which of following characteristics of big data means the data can be converted into meaningful, quality information that can be used to achieve tangible business benefits?

Data inconsistencies can lead to uncoordinated strategic decision making and embarrassing dilemmas for businesses.

Hadoop, a data warehouse built using HIVE, provides SQL-like query to access data stored in different file systems and databases that are used by HIVE.

In the context of data preparation, a power calculation helps determine

Introduction to Marketing Analytics

Exploratory Data Analysis Using Cognitive Analytics

Data Visualization

Regression Analysis

Neural Networks

Automated Machine Learning

Cluster Analysis

Market Basket Analysis

Natural Language Processing - Text Mining and Sentiment Analysis

Social Network Analysis

Web Analytics

Filters