WGU C207 OA DATA DRIVEN DECISION
MAKING FINAL PAPER FULL QUESTIONS
AND ANSWERS BUNDLED SOLUTION
●● Weighted Index
Answer: assign a weight to allow for significant differences in the index.
●● Reasons for including analytics in decision-making
Answer: decrease cost of data storage
increase processing power
●● Descriptive Analytics
Answer: using current and past data for strictly descriptive purposes.
i.e. car price data shows a 2% increase over the prior year
a manager wants to know why sales spiked during the prior quarter
●● Simple indexing
Answer: Common analytic measure to improve performance. Compares
current data with data during a base period.
,(Price / Price during "Base Period") x 100
i.e. Big Mac was 1.60 in 1968 which is base period. what is index for
2014 if price was 4.80 then?
(4..60) * 100 = 300 (means price is 3x greater than base period)
Used to identify price fluctuations of supplies, materials, products, etc.
●● Predictive / Inferential Analytics
Answer: using current and past data to predict/estimate future.
i.e. based on the past 10 years of data for car prices, we predict an
increase of 1.5% over the upcoming year.
●● Prescriptive Analytics
Answer: using past data to PREDICT or ESTIMATE future in order to
optimize operations
includes experimental design and optimization to aid in DECISION-
MAKING. MANAGERIAL DECISIONS.
,i.e. based on past data, sales prices for electric cars could increase by 5%
if we increased charging stations by 7%
●● Big data
Answer: Data so big that it's difficult to process using traditional
methods.
Stored in a Data Warehouse.
Mined to identify patterns and trends
Primary purpose is to encourage buying behavior.
Enables products to be more tailored to customer base.
Improves decision-making.
Supports development of next generation products/services.
watch for keywords in test options. i.e. company TOTAL sales (just one
number) vs all sales invoices
●● Structured / Quantitative Data
, Answer: Data follows pre-defined formats.
i.e. multiple choice answers, addresses, names, stock tickers
●● Unstructured / Qualitative Data
Answer: Data doesn't follow pre-defined formats. Usually gets
structured by a "theme analysis"
i.e. blocks of freeform text, audio, video
●● Continuous Data
Answer: Data that can take any value (within a set range)
i.e. 3.14159, -189,115.2
a thermometer reads 66.5 degrees
●● Interval Data (data measuring levels)
Answer: data is ordered at equal intervals apart and "0" doesn't mean
absence of data, just another data point
a type of continuous data
i.e. date, time, degrees
MAKING FINAL PAPER FULL QUESTIONS
AND ANSWERS BUNDLED SOLUTION
●● Weighted Index
Answer: assign a weight to allow for significant differences in the index.
●● Reasons for including analytics in decision-making
Answer: decrease cost of data storage
increase processing power
●● Descriptive Analytics
Answer: using current and past data for strictly descriptive purposes.
i.e. car price data shows a 2% increase over the prior year
a manager wants to know why sales spiked during the prior quarter
●● Simple indexing
Answer: Common analytic measure to improve performance. Compares
current data with data during a base period.
,(Price / Price during "Base Period") x 100
i.e. Big Mac was 1.60 in 1968 which is base period. what is index for
2014 if price was 4.80 then?
(4..60) * 100 = 300 (means price is 3x greater than base period)
Used to identify price fluctuations of supplies, materials, products, etc.
●● Predictive / Inferential Analytics
Answer: using current and past data to predict/estimate future.
i.e. based on the past 10 years of data for car prices, we predict an
increase of 1.5% over the upcoming year.
●● Prescriptive Analytics
Answer: using past data to PREDICT or ESTIMATE future in order to
optimize operations
includes experimental design and optimization to aid in DECISION-
MAKING. MANAGERIAL DECISIONS.
,i.e. based on past data, sales prices for electric cars could increase by 5%
if we increased charging stations by 7%
●● Big data
Answer: Data so big that it's difficult to process using traditional
methods.
Stored in a Data Warehouse.
Mined to identify patterns and trends
Primary purpose is to encourage buying behavior.
Enables products to be more tailored to customer base.
Improves decision-making.
Supports development of next generation products/services.
watch for keywords in test options. i.e. company TOTAL sales (just one
number) vs all sales invoices
●● Structured / Quantitative Data
, Answer: Data follows pre-defined formats.
i.e. multiple choice answers, addresses, names, stock tickers
●● Unstructured / Qualitative Data
Answer: Data doesn't follow pre-defined formats. Usually gets
structured by a "theme analysis"
i.e. blocks of freeform text, audio, video
●● Continuous Data
Answer: Data that can take any value (within a set range)
i.e. 3.14159, -189,115.2
a thermometer reads 66.5 degrees
●● Interval Data (data measuring levels)
Answer: data is ordered at equal intervals apart and "0" doesn't mean
absence of data, just another data point
a type of continuous data
i.e. date, time, degrees
