WPC 300 Midterm Exam Questions with
Complete Solutions
What is analytics? - Answer-- It all starts with data
- Businesses capture moments of transactions to deliver economic value
- Analytics is the process of developing actionable decisions or recommendations for
actions based on insights generated from historical data
Principles of Problem Framing - Answer-Tell an interesting and complete story
- The problem you address should be meaningful
- Solution could be reused for related problems
- Assumptions, boundaries
Find an appropriate solution framework
- Break down the problem into pieces
- Iterative process (agile vs waterfall)
- Identify appropriate analytical/modeling techniques
Routinize the procedure
- Documentation
- Next similar questions can be solved quickly
- Build a system (marcos, codes, programs)
Data - Answer-- Collection
- Communication
- Cleaning
- Analyses
- Gathering
- Storing
- Retrieving
- Interpreting
Primary Data - Answer-- Survey
- Interviews (marketing firm's telephone interviews)
- Used a lot in marketing research
Secondary Data - Answer-- Firm's proprietary database
- Internet data (crawlers)
- Stock/capital market data
- Accounting disclosure data
Simulated Data - Answer-- Data based on assumption and simulation
- Used a lot in scheduling, routing and queuing
, Data Extraction - Answer-Extract data from primary/secondary source
Data Transformation - Answer-Transform/clean data into proper format or structure for
the purpose of querying and analysis
Data Load - Answer-Load data into final target database, more specifically an
operational data store, data mart or data warehouse
Descriptive Analytics - Answer-This is 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
Questions:
- What happened? What is happening?
- What are our sales since last year?
- Which customer is frequenting our store ore often and what are they buying?
Methods:
- Standard reporting
- Dashboards
- Visual analytics
Outcome
- Well defined business problems and opportunities
Predictive Analytics - Answer-The use of data, statistical algorithms and machine
learning techniques to identify the likelihood of future outcomes based on historical
data, the goal is to go beyond knowing what has happened to providing a best
assessment of what will happen in the future
Questions:
- What will happen next? Why will it happen next?
- What will be our likely revenue in the next five years?
- Who will respond to our advertisement?
Methods:
- Data mining
- Text mining
- Forecasting
Outcome:
- Accurate projections of future outcomes and events
Explanatory/Diagnostic Analytics - Answer-This is about looking into the past and
determining why a certain thing happened, this type of analytics usually revolves around
working on a dashboard
Complete Solutions
What is analytics? - Answer-- It all starts with data
- Businesses capture moments of transactions to deliver economic value
- Analytics is the process of developing actionable decisions or recommendations for
actions based on insights generated from historical data
Principles of Problem Framing - Answer-Tell an interesting and complete story
- The problem you address should be meaningful
- Solution could be reused for related problems
- Assumptions, boundaries
Find an appropriate solution framework
- Break down the problem into pieces
- Iterative process (agile vs waterfall)
- Identify appropriate analytical/modeling techniques
Routinize the procedure
- Documentation
- Next similar questions can be solved quickly
- Build a system (marcos, codes, programs)
Data - Answer-- Collection
- Communication
- Cleaning
- Analyses
- Gathering
- Storing
- Retrieving
- Interpreting
Primary Data - Answer-- Survey
- Interviews (marketing firm's telephone interviews)
- Used a lot in marketing research
Secondary Data - Answer-- Firm's proprietary database
- Internet data (crawlers)
- Stock/capital market data
- Accounting disclosure data
Simulated Data - Answer-- Data based on assumption and simulation
- Used a lot in scheduling, routing and queuing
, Data Extraction - Answer-Extract data from primary/secondary source
Data Transformation - Answer-Transform/clean data into proper format or structure for
the purpose of querying and analysis
Data Load - Answer-Load data into final target database, more specifically an
operational data store, data mart or data warehouse
Descriptive Analytics - Answer-This is 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
Questions:
- What happened? What is happening?
- What are our sales since last year?
- Which customer is frequenting our store ore often and what are they buying?
Methods:
- Standard reporting
- Dashboards
- Visual analytics
Outcome
- Well defined business problems and opportunities
Predictive Analytics - Answer-The use of data, statistical algorithms and machine
learning techniques to identify the likelihood of future outcomes based on historical
data, the goal is to go beyond knowing what has happened to providing a best
assessment of what will happen in the future
Questions:
- What will happen next? Why will it happen next?
- What will be our likely revenue in the next five years?
- Who will respond to our advertisement?
Methods:
- Data mining
- Text mining
- Forecasting
Outcome:
- Accurate projections of future outcomes and events
Explanatory/Diagnostic Analytics - Answer-This is about looking into the past and
determining why a certain thing happened, this type of analytics usually revolves around
working on a dashboard
