Marketing Analytics Exam 1

_______ is useful when considering categorical variables.

Dummy coding

New column

Aggregation

Normalization

Dummy coding

Cognitive analytics and knowledge discovery applications use advanced capabilities to ________ and ________ hidden in large volumes of data.

Clean data & conduct price optimization

Draw conclusions & develop insights

Ensure a perception of seamless transitions & improve

computational performance

Communicate & extract design elements

Draw conclusions & develop insights

The cognitive technology of ________ facilitates the extraction of text in a readable, natural form through translators and chatbots.

Deep learning

Computer vision

Machine Learning

Natural language processing

Natural language processing

Which of the following offers the ability to answer the question "What should happen?" in marketing analytics?

Forecasting

Data query

Image recognition

Text recognition

Forecasting

Showing a subset of raw data is an effective way to communicate a story based on data.

True or False

False

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?

Value

Velocity

Volume

Variety

Value

Which of the following cognitive technologies extracts meaning from image pixels such as faces, objects, and scenes?

Deep learning

Computer vision

Machine learning

Natural language processing

Computer vision

Identify a difference between natural language processing (NLP) and computer vision.

Computer vision technology supports virtual assistants, whereas NLP supports image identification.

NLP extracts meaning from text, whereas computer vision extracts meaning from image pixels.

NLP utilizes a customer's purchase history, whereas computer vision employs website chatbots.

Computer vision learns from new data without explicit programming, whereas NLP predicts target variables.

NLP extracts meaning from text, whereas computer vision extracts meaning from image pixels.

Which of the following improves itself by learning from new data without being explicitly programmed?

Machine learning

Descriptive statistics

Cluster analysis

Traditional data exploration

Machine learning

In the context of relational databases, a(n) ________ is a set of one or more columns in a table that refers to the primary key in another table.

Foreign key

Unique key

Undefined figure

Alien number

Foreign key

Which one of the following is false?

"Marketing Analytics uses ____ to solve marketing problems."

Bias

Data

Mathematics

Technology

Statistics

Bias

In the context of database management systems, primary keys and foreign keys are important in relational databases because they help

Customers search for products online effectively

Manage the volume and speed of incoming data

Databases consistently maintain the same properties

Database users collate data from different tables

Database users collate data from different tables

Which of the following businesses would most likely determine demand for its product/service based on the season and the type of technology employed by users?

a food delivery mobile app

a matchmaking app

a travel services website

a medical information website

a travel services website

Identify the chart or graph that is used to show the changes in a variable over a period.

a histogram

a line chart with a time series

a scatterplot

a bar chart with rankings

A line chart with a time series

Identify a valid difference between descriptive analytics and predictive analytics.

Descriptive analytics mimics human-like intelligence, whereas predictive analytics identifies the best optimal decision

Descriptive analytics uses data to explain the past, whereas predictive analytics uses data to explain the future

Descriptive analytics can identify patterns in data, whereas predictive analytics can recognize objects from an image

Descriptive analytics predicts new needs and opportunities, whereas predictive analysis reinforces existing beneficial practices

Descriptive analytics uses data to explain the past, whereas predictive analytics uses data to explain the future

Imagine a company wants to send a follow-up email to its best customers immediately after a purchase. However, email addresses were not collected from the customers at the time of purchase. This is an example of missing the data quality of ________.

Consistency

Variety

Accuracy

Timeliness

Timeliness

Asking the question "Is the data correct, reliable, and precisely measured?" will help in determining the data quality of ________.

Format

Timeliness

Consistency

Accuracy

Accuracy

Toyota Financial Services used ________ to enable call center representatives to obtain structured and unstructured data about customers.

IBM Cognos

Cogito

Attivio

IBM Watson

IBM Watson

In the SMART analytics principle, the letter "A" refers to an ________ goal-setting technique.

Acceptable

Attainable

Accurate

Applicable

Attainable

In the context of questions that help identify a business problem, which of the following questions helps to determine the context of the problem (such as the elevator problem)?

What are the ethical implications of the analysis?

What is the current problem that needs solving?

What divisions are impacted by this problem?

What do you think continues to drive this problem?

What is the current problem that needs solving?

In the context of modeling types, supervised learning is called classification when

an unlabeled dataset is used to develop ann algorithm

the target variable is categorical

a testing dataset is used to evaluate the final selected algorithm

the target variable is continuous

The target variable is categorical

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

MIN ( )

MAX ( )

AVG ( )

SUM ( )

SUM ( )

In the context of database management systems, relational data is accessed by a database management language called ________.

Structured querying language

Machine and assembly language

Business-oriented language

Object-oriented language

Structured querying language

Symmetrical, asymmetrical, and radial are three elements of the design principle of ________.

Proportion

Emphasis

Rhythm

Balance

Balance

Which of the following is one of the most popular data visualization software tools in the business world?

R

Tableau

IBM Cognos

SQL

Tableau

A sales manager that lines up the names of salespeople based on their performance, from the highest to lowest, is using the ________ method to visualize data.

Correlation

Ranknings

Time series

Frequency Distribution

Rankings

In supervised learning, the training dataset is used to

build the algorithm and "learn" the relationship between the predictors and the target variable

assess how well the algorithm developed using the validation dataset estimates the target variable

evaluate the final selected algorithm and see how well it performs

select the model that most accurately predicts the target value of interest

Build the algorithm and "learn" the relationship between the predictors and the target variable

Data is an asset only when it quickly and easily provides value

True or False?

True

Which of the following is NOT an objective of graphical depictions?

Exploring results

Helping companies eliminate quantitative methods because graphical illustrations are sufficient to make decisions

Providing a simple and intuitive way to communicate complex topics

Comparing results

Helping companies eliminate quantitative methods because graphical illustrations are sufficient to make decisions

A marketing analyst at a gaming company is studying the effect of school holidays on sales of video games. In this study, what type of variable is school holidays?

A dependent variable

An independent variable

An outcome variable

A target variable

Sn independent variable

Which one of the following characteristics does not represent big data?

Volume

Velocity

Vocabulary

Variety

Vocabulary

A company combined monthly sales data into a single group to calculate the total sales by a quarter or a year. This is an example of the ________ step of data transformation.

Dummy Coding

Normalization

Aggregation

Feature Construction

Aggregation

_______ uses data, statistics, mathematics, and technology to solve marketing business problems

Marketing analytics

What are these facts describing?

- Modeling software drive marketing decisions

- The fastest growing filed of analytics applications

- Increasingly applied, and the impact and benefits are evident

Marketing analytics

What are the analytics levels?

Descriptive, Predictive, Prescriptive, Al/Cognitive

(They each impact COMPETITIVE ADVANTAGE)

are techniques used to explain or quantify the past.

- Data queries

- Visual reports

- Descriptive statistics.

Descriptive Analytics

is used to build models based on the past to explain the future

For example: historic sales can predict future sales

- Forecasting

- Predictive Modeling

- Association Rules

- Cluster Analysis

Predictive Analytics

identifies the optimal course of action or decision

UPS route optimization, Amazon's price optimization

- Optimization Modeling

- Decision Analysis

Prescriptive Analytics

are designed to mimic human-like intelligence for certain tasks, like discovering patterns

Artificial Intelligence (AI) & Cognitive Analytics

What does SMART stand for?

Specific, Measurable, Attainable, Realistic, Timely

The goal should be clearly determined (SMART)

Specific

Progress of the goal should be trackable and have a measurable outcome (SMART)

Measurable

The goal should be reasonable to accomplish (SMART)

Achievable

The goals should solve the analytics problem and align with business objectives (SMART)

Relevant

A timeframe to successfully complete the analytics project should be determined (SMART)

Timely

The ______ can be a goal-setting technique

SMART principles

Data consists of both ________ and _________ data

primary, secondary

___________ is collected for a specific research purpose

Primary research

___________ relies on existing data collected for another purpose

Secondary data

Sources of Secondary Data Include:

public datasets

online sites

mobile data

channel partners

___________ is made up of records organized in rows and columns

Structured data

What can be stores in a database or spreadsheets formula, includes numbers, dates, and text Strongs and is also easy to access and analyze?

Structured data

____________ includes text, images, videos, and sensor data

Unstructured data

What has non defined structure, the content does not fit into a table format, requires advanced analytics to prepare and analyze, and the technology has advanced to support manipulation and exploration of this data?

Unstructured data

__________ can be discrete (integer) or continuous

Numerical data

______________ is measured in whole numbers

Discrete data

_____________ can include values with decimals

Continuous data

______________ exists when values are selected from categories

Categorical data

_________ can have two values

_________ has no meaningful order

_________ data has meaningful values

Binary, Nominal, Ordinal

Metric scales can be measured as _________ or __________

intervals, ratios

Both of these scales possess meaningful, constant units of measure and the distance between each point of the scale are equal

intervals or ratios

_________ do not include an absolute zero

Interval

_______ scales have an absolute zero point and can be discussed in terms of multiple;es

Ratio scales

___________ are characteristics or features that pertain to a person, place, or object

Variables

Independent variable can also be called the ___________

Predictor

The dependent variable can also be called the ___________

Target

_____________ learning suggests the target variable is known

Supervised

A ________ dataset helps "learn" the relationship

training

A _______ dataset assesses the algorithm's accuracy

validation

A _______ dataset evaluates the final selected algorithm

testing

True or False? If the target variable is continuous, results are a prediction

True

True or False? If the target variable is categorical, supervised learning is called a classification?

True

___________ learning has no previously defined target variables

Unsupervised

The goal of what is: to model data to discover and confirm patterns

Unsupervised Learning

True or False? The pace of data collection is accelerating due to the web and mobile apps and social media

True

______ datasets are a core organizational asset

Large

_______ is a relative term describing massive amounts of data with the following characteristics Volume, Variety, Veracity, Velocity, and Value

Big Data

What are the characteristics of big data?

Volume, Variety, Veracity, Velocity, and Value

______ is data per time unit (BIG DATA)

Volume

_____ is structured or unstructured (BIG DATA)

Variety

______ is accuracy or missing data (BIG DATA)

Veracity

_____ is the speed at which data arrives (BIG DATA)

Velocity

_______ is the usefulness of the data in making accurate decisions (BIG DATA)

Value

Many are moving away from the term "big data" and adopting "______________"

smart data

A __________ contains current data from company operations

database

A _____________ database is a DBS storing data in rows and columns

relational

_______ (features, predictors, variables) store many records

Columns

_____ (records) have a unique primary key

Rows

A __________ is a set of columns that refers to a primary key in another table

foreign key

Relational data is accessible by a database management language called ____________

structured querying language (SQL)

Timeliness, Completeness, Accuracy, Consistency, Format

Data Quality

True or False? There is no tangible benefit to data in a raw form

True

__________ may be determined using a power calculation unit of analysis

Sample size

Anything over 3 standard deviations above the mean is considered what?

An outlier

Another method of identifying outliers is the use of ___________

cluster analysis

A key process to prepare data for valuable insights

Aggregation

Brings all variables to the same scale

Normalization

__________ is useful when considering nominal categorical values

Dummy coding

(geometric location is non metric and needs dummy coding)

________________ provides a summary of main characteristics in data

- using visualization versus a data table enables quick comprehension

Exploratory data

Can help detect:

- anomalies or outliers

- the most important variables

changes occurring within each variable

patterns or relationships between variables

Exploratory Data