Data Analytics Final Exam Study
Guide Complete Solutions Updated
version.
Description
This comprehensive Data Analytics Exam resource is designed to support students in mastering
core concepts and excelling in assessments. It features a curated set of exam-relevant questions
and well-explained solutions, covering data preprocessing, visualization techniques, and
analytical methods.
Structured for clarity and efficiency, this guide is ideal for both in-depth study and quick
revision, helping learners build confidence and achieve strong academic performance.
1
,analytics
the process of transforming data into actions through analysis
The process of analysis may be initiated by
the desire to address specific problems or the need to explore and learn from existing data
___% of the world's data has been created in the last 2 years
90
What is the potential value from utilizing data?
$300bil/year
prescriptive analysis
part of business analytics dedicated to finding the best course of action unknown future events
(Optimization and Simulation)
predicitive analytics
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)
2
, Diagnostic analytics
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
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:
obtain and clean 400,000 transactions at an electronics retailer over 5 years. Data modeling,
visualization, and trend lines
Example of predictive analytics:
Model the probability a customer purchaser product x in their next transaction (Data mining
and predictive models)
optimization
determine which products to promote in real time to a customer to maximize margin
simulation
simulate retail store to evaluate the how the new real time promo policy will perform over time
3
Guide Complete Solutions Updated
version.
Description
This comprehensive Data Analytics Exam resource is designed to support students in mastering
core concepts and excelling in assessments. It features a curated set of exam-relevant questions
and well-explained solutions, covering data preprocessing, visualization techniques, and
analytical methods.
Structured for clarity and efficiency, this guide is ideal for both in-depth study and quick
revision, helping learners build confidence and achieve strong academic performance.
1
,analytics
the process of transforming data into actions through analysis
The process of analysis may be initiated by
the desire to address specific problems or the need to explore and learn from existing data
___% of the world's data has been created in the last 2 years
90
What is the potential value from utilizing data?
$300bil/year
prescriptive analysis
part of business analytics dedicated to finding the best course of action unknown future events
(Optimization and Simulation)
predicitive analytics
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)
2
, Diagnostic analytics
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
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:
obtain and clean 400,000 transactions at an electronics retailer over 5 years. Data modeling,
visualization, and trend lines
Example of predictive analytics:
Model the probability a customer purchaser product x in their next transaction (Data mining
and predictive models)
optimization
determine which products to promote in real time to a customer to maximize margin
simulation
simulate retail store to evaluate the how the new real time promo policy will perform over time
3
