Data Analytics Exam 2025 | All
Questions & Answers (100% Correct)
analytics - ANSWER - the process of transforming data into actions through analysis
Support Sentence - ANSWER - .8% probability that ketchup, rolls, and relish are
purchased together
___% of the world's data has been created in the last 2 years - ANSWER - 90
What is the potential value from utilizing data? - ANSWER - $300bil/year
prescriptive analysis - ANSWER - part of business analytics dedicated to finding the
best course of action unknown future events (Optimization and Simulation)
predicitive analytics - ANSWER - branch of analytics which is used to make predictions
about unknown future events- uses many techniques from data mining, statistics,
modeling, machine learning, and AI to analyze current data (Data Mining and Predictive
Forecasting)
Diagnostic analytics - ANSWER - a form of analytics which examines data or content to
answer the question "why did it happen" and is characterized by techniques such as
drill-down, data discovery, data mining, and correlations (Data Modeling and Trend
Lines)
Descriptive analytics - ANSWER - a preliminary stage of data processing that creates a
summary of historical data to yield useful information and possibly prepare the data for
further analysis (Data Visualization and Dash Boards)
Example of descriptive and diagnostic analytics: - ANSWER - obtain and clean 400,000
transactions at an electronics retailer over 5 years. Data modeling, visualization, and
trend lines
Example of predictive analytics: - ANSWER - Model the probability a customer
purchaser product x in their next transaction (Data mining and predictive models)
The process of analysis may be initiated by - ANSWER - the desire to address specific
problems or the need to explore and learn from existing data
optimization - ANSWER - determine which products to promote in real time to a
customer to maximize margin
simulation - ANSWER - simulate retail store to evaluate the how the new real time
promo policy will perform over time
,Companies using analytics - ANSWER - Amazon: first to use the recommend engine
Google: matches queries to search results through a data analytics algorithm
Facebook: uses data for image recognition
LinkedIn: links recruiters and applicants based on internal data analytics
How can companies compete? - ANSWER - It is almost impossible to differentiate
yourself. Here is how some companies apply:
Supply chain: Walmart/Amazon
Customer Selection: Harrah's Capital One
Pricing: Progressive
Human Capital: Patriots/Red Sox
infographics - ANSWER - where data meets design
ratio data - ANSWER - variable that has a natural zero (Age, salary, experience)
Ordinal data - ANSWER - outcomes of a variable express ranked order (education,
grade)
categorical data - ANSWER - variable that is sorted into categories according to
characteristics (employee #, gender, ethnicity, computer)
dimensions - ANSWER - Variable that categorizes. Commonly used dimensions are
people, products, places, and time. In a data warehouse, dimensions provide structured
labeling information
Measurements - ANSWER - Variables that can be measured, aggregated, or used for
mathematical operations. Commonly used measurements are profits, costs, and ages
data mining - ANSWER - the process of finding anomalies, patterns, and correlations
within large data set to identify patterns, make predictions, and establish relationships to
solve problems through data analysis
Some example of data mining - ANSWER - 1. mobile phones and utilities companies
using data mining and business intelligence to predict churn
2. Retailers segment customers into groups and target marketing and promotions to
those different groups
3. Many e-commerce companies use data mining data mining and business intelligence
to offer cross sells and up sells through their website
4. Crime prevention agencies use analytics and data mining to spot trends across
myriad of data
5. Target developed rules to predict if their shoppers were pregnant
Data Mining Applications: - ANSWER - 1. Email spam folders: examine millions of
emails to classify as spam or not
, 2. Banks trying to identify applicants more likely to default on loans
3. Text mining at google or yahoo- helps order websites by relevance to your search
4. US Gov- track down a person of interest; treasury department can predict money
laundering
5. Safeway- Offers safeway savers card: every use, collected data; Users are given a
discount but must giver personal information; identity theft aggregate patters
Why is data mining so effective? - ANSWER - -Data is there: bar coding, scanning,
RFID, internet, ERP systems, and others
-Computing power is cheap
-Competitive pressure
top down - ANSWER - supervised, have a theory and need an experiment to
prove/disprove, hypothesis testing, science
bottom up - ANSWER - unsupervised, start with data, see new patterns, knowledge
discovery, creativity
Data Mining Process - ANSWER - CRISP-DM
CRoss, Industry, Standard, Process for, Data, Mining
CRISP-DM Phases
1. Business Understanding - ANSWER - -Solve a specific problem
-Clear definition helps- measurable success criteria
-Convert business objectives to set of data mining goals (what to achieve in technical
terms)
CRISP-DM
2. Data Understanding - ANSWER - can come from many sources
-internal- erp system, data warehouse
-external- government data, commercial
-created- research
CRISP-DM
3. Data Preparation - ANSWER - -Clean data- format and identify gaps, filter outliers
and redundancies
-Transform and create dataset for modeling
CRISP-DM
4. Modeling - ANSWER - -Data treatment- how many data sets? training set, test set,
others
-Techniques- market basket analysis, clustering, classification/prediction
CRISP-DM
5. Evaluation - ANSWER - -Check for a good model and evaluate to assure nothing is
missing
Questions & Answers (100% Correct)
analytics - ANSWER - the process of transforming data into actions through analysis
Support Sentence - ANSWER - .8% probability that ketchup, rolls, and relish are
purchased together
___% of the world's data has been created in the last 2 years - ANSWER - 90
What is the potential value from utilizing data? - ANSWER - $300bil/year
prescriptive analysis - ANSWER - part of business analytics dedicated to finding the
best course of action unknown future events (Optimization and Simulation)
predicitive analytics - ANSWER - branch of analytics which is used to make predictions
about unknown future events- uses many techniques from data mining, statistics,
modeling, machine learning, and AI to analyze current data (Data Mining and Predictive
Forecasting)
Diagnostic analytics - ANSWER - a form of analytics which examines data or content to
answer the question "why did it happen" and is characterized by techniques such as
drill-down, data discovery, data mining, and correlations (Data Modeling and Trend
Lines)
Descriptive analytics - ANSWER - a preliminary stage of data processing that creates a
summary of historical data to yield useful information and possibly prepare the data for
further analysis (Data Visualization and Dash Boards)
Example of descriptive and diagnostic analytics: - ANSWER - obtain and clean 400,000
transactions at an electronics retailer over 5 years. Data modeling, visualization, and
trend lines
Example of predictive analytics: - ANSWER - Model the probability a customer
purchaser product x in their next transaction (Data mining and predictive models)
The process of analysis may be initiated by - ANSWER - the desire to address specific
problems or the need to explore and learn from existing data
optimization - ANSWER - determine which products to promote in real time to a
customer to maximize margin
simulation - ANSWER - simulate retail store to evaluate the how the new real time
promo policy will perform over time
,Companies using analytics - ANSWER - Amazon: first to use the recommend engine
Google: matches queries to search results through a data analytics algorithm
Facebook: uses data for image recognition
LinkedIn: links recruiters and applicants based on internal data analytics
How can companies compete? - ANSWER - It is almost impossible to differentiate
yourself. Here is how some companies apply:
Supply chain: Walmart/Amazon
Customer Selection: Harrah's Capital One
Pricing: Progressive
Human Capital: Patriots/Red Sox
infographics - ANSWER - where data meets design
ratio data - ANSWER - variable that has a natural zero (Age, salary, experience)
Ordinal data - ANSWER - outcomes of a variable express ranked order (education,
grade)
categorical data - ANSWER - variable that is sorted into categories according to
characteristics (employee #, gender, ethnicity, computer)
dimensions - ANSWER - Variable that categorizes. Commonly used dimensions are
people, products, places, and time. In a data warehouse, dimensions provide structured
labeling information
Measurements - ANSWER - Variables that can be measured, aggregated, or used for
mathematical operations. Commonly used measurements are profits, costs, and ages
data mining - ANSWER - the process of finding anomalies, patterns, and correlations
within large data set to identify patterns, make predictions, and establish relationships to
solve problems through data analysis
Some example of data mining - ANSWER - 1. mobile phones and utilities companies
using data mining and business intelligence to predict churn
2. Retailers segment customers into groups and target marketing and promotions to
those different groups
3. Many e-commerce companies use data mining data mining and business intelligence
to offer cross sells and up sells through their website
4. Crime prevention agencies use analytics and data mining to spot trends across
myriad of data
5. Target developed rules to predict if their shoppers were pregnant
Data Mining Applications: - ANSWER - 1. Email spam folders: examine millions of
emails to classify as spam or not
, 2. Banks trying to identify applicants more likely to default on loans
3. Text mining at google or yahoo- helps order websites by relevance to your search
4. US Gov- track down a person of interest; treasury department can predict money
laundering
5. Safeway- Offers safeway savers card: every use, collected data; Users are given a
discount but must giver personal information; identity theft aggregate patters
Why is data mining so effective? - ANSWER - -Data is there: bar coding, scanning,
RFID, internet, ERP systems, and others
-Computing power is cheap
-Competitive pressure
top down - ANSWER - supervised, have a theory and need an experiment to
prove/disprove, hypothesis testing, science
bottom up - ANSWER - unsupervised, start with data, see new patterns, knowledge
discovery, creativity
Data Mining Process - ANSWER - CRISP-DM
CRoss, Industry, Standard, Process for, Data, Mining
CRISP-DM Phases
1. Business Understanding - ANSWER - -Solve a specific problem
-Clear definition helps- measurable success criteria
-Convert business objectives to set of data mining goals (what to achieve in technical
terms)
CRISP-DM
2. Data Understanding - ANSWER - can come from many sources
-internal- erp system, data warehouse
-external- government data, commercial
-created- research
CRISP-DM
3. Data Preparation - ANSWER - -Clean data- format and identify gaps, filter outliers
and redundancies
-Transform and create dataset for modeling
CRISP-DM
4. Modeling - ANSWER - -Data treatment- how many data sets? training set, test set,
others
-Techniques- market basket analysis, clustering, classification/prediction
CRISP-DM
5. Evaluation - ANSWER - -Check for a good model and evaluate to assure nothing is
missing
