ACC 490 Final Exam

what does SPARKS stand for?

stakeholders

what does SPARKS stand for?

purpose

what does SPARKS stand for?

alternatives

what does SPARKS stand for?

risks

what does SPARKS stand for?

knowledge

what does SPARKS stand for?

self-reflection

define descriptive analytics.

what happened

define diagnostic analytics.

why did something happen

define predictive analysis

what will happen

define prescriptive analytics.

what should we do

what are common descriptive analytics techniques?

dashboards, averages, percentages, frequency analysis, and visualizations

what are common predictive analytics techniques?

forecasting, regression, and machine learning

what is a data analytics mindset?

using critical thinking, curiosity, and data-driven decision making

what are important data analytic skills?

critical thinking, technology skills, communication, accounting knowledge, and visualization skills

what are examples of data analysis risks?

incorrect data, bias, wrong methods, missing data, and calculation errors

what is a relational database?

a collection of related tables that store data

what is a primary key?

a unique identifier for each record in a table

what is a foreign key?

a primary key from another table used to create relationships

what is a record in a database?

a row in a table

what is an attribute in a database?

a column or field describing characteristics of data

what is the difference between null and zero?

null mean missing/unknown and zero is a numeric value

what visualization is best for trends over time?

line chart

what visualization is best for relationships between variables?

scatterplot

what visualization is best for showing composition?

pie chart

what visualization is best for distributions?

histogram or boxplot

what visualization is best for comparisons?

bar chart or column chart

how can descriptive statistics help us understand the characteristics of data?

summarizes and describes data using measures such as mean, median, mode, range, variance, and standard deviation

what measures are used to describe a data set’s shape and distribution?

skewness, kurtosis, histograms, and boxplots

what are good data analysis questions?

clear, concise, measurable, and focused on one issue

what is categorical data?

data grouped into labels or categories

what is ordinal data?

ranked categorical data

what is interval data?

numeric data without a true zero

what is ratio data?

numeric data with a meaningful zero

which data types are commonly used for predictive analysis?

interval and ratio

what type of analysis can be performed for descriptive analytics?

summaries, dashboards, averages, and visualization

what type of analysis can be performed for diagnostic analytics?

comparisons, drill-down analysis, trend analysis, and root-cause analysis

what type of analysis can be performed for predictive analytics?

forecasting, regression analysis, probability models, and machine learning

what type of analysis can be performed for prescriptive analytics?

optimization models, simulations, decision trees, and recommendation systems

what is data preparation?

profiling, cleaning, restructuring, and integrating data before analysis

what are the three parts of data profiling?

investigating quality, investigating structure, and deciding and informing

what is dirty data?

inaccurate or incomplete data

what is a flat table?

a table where each column contains one variable and each row is one record

what is a composite column?

a column containing multiple characteristics in one field

what is a crosstab table?

a table where values appear in column headers

what is the recommended analytical data model structure?

star schema

what are the two table types in a star schema?

fact tables and dimension tables

what is a fact table?

a table containing quantitative transaction data

what is a dimension table?

a table providing descriptive context for analysis

what does ETL stand for?

extract. transform, load

what happens during the extract step of ETL?

data is pulled from source systems

what happens during the transform step of ETL?

data is cleaned and restructured

what happens during the load step of ETL?

data is stored in the analytical platform

what is information modeling?

transforming data into useful information using algorithms

what is a calculated column?

a formula applied to each row in a table

what is a measure?

an aggregate calculation used in reports and analysis

give an example of a calculated column.

revenue = price x quantity

give an example of a measure.

total revenue

what is data exploration?

looking for patterns, outliers, and insights in data

what are insights in data analytics?

observations that may significantly impact decisions

what are the eight foundational data relationships?

nominal comparison, distribution, deviation, ranking, part-to-whole, correlation, time series, and geospatial

what chart is commonly used for correlation?

scatterplot

what chart is commonly used for part-to-whole relationships?

pie chart

what chart is commonly used for time series relationships?

line chart

what is a pareto chart?

a chart combining bars and a cumulative percentage line

what is data analysis interpretation?

evauluating analysis results to understand their meaning

what is data exploration?

analyzing data to determine if more analysis is needed

what is analysis risk?

risk caused by using incorrect methods or calculations

what is data risk?

risk caused by incomplete, inaccurate, or outdated data

what is bias risk?

risk caused by personal data-related biases

what is confirmation bias?

looking for information that supports existing beliefs

what is “what you see is all there is” bias?

assuming limited information tells the whole story

what should you ask when evaluating analysis methods?

was the correct method used?

what should you ask when evaluating data?

is the data reasonable and complete?

what should you ask when evaluating results?

do the results answer the original question and make sense?