Social Science Business Business Management
Business Analytics & Data Management
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Chapter 1 Quiz CIS 348 Quizzes 1-4 business analytics chapter 1 BUS 312
36 terms 40 terms 49 terms 37 terms
Trin4710 Preview Avery_Kyle3 Preview gracemargueritte Preview Ale
Business Value all items, events, interactions that determine a company's financial health
Business Process a coordinated, standardized set of activities conducted by both people and
equipment to accomplish a specific business task
Business Analyst a data specialist who curates and uses data to help an organization make effective
business decisions
Data Overload vast amount of data prevents business analysts from properly synthesizing data
Analytics Mindset willingness and ability to specify which business questions need to be addressed,
find and extract pertinent data that might address those questions, analyze those
data, and then report the results to decision-makers.
-Understand the questions that their business and its decision-makers are asking
-Understand the nature and quality of the business's data
Data raw numbers and facts that have little meaning on their own
Information is data that are organized in a way that is meaningful to the user in a giver context
Information value chain is composed of the events and processes going all the way from the collection of
data to the compilation of information to the ultimate business decision
Data & Context → Information → Knowledge → Decision
, SOAR Analytics model 1. Specify the question
2. Obtain the data
-Relevant data: directly or closely connected to the question at hand
-Reliable data: reflect the facts or truth with little or no bias
-Data Integrity: refers to the combined accuracy, validity, and consistency of data
stored and used over time
3. Analyze the data
Analytics
-Ascendency model
-Descriptive Analytics (what happened)
-Diagnostics analytics (why did it happen and what are the causes)
-Predictive analytics (Will it happen?)
-Prescriptive analytics (What should we do?)
-Adaptive/Autonomous analytics (How can we learn?)
4. Report the results
-Data Visualization: graphic representation of data
-Exploratory Visualizations: is a graphical representation that is useful for
uncovering patterns and useful insights in the data, generally as a part of
descriptive or diagnostic analytics
-Explanatory Visualizations: graphical representation that is useful in
communicating the findings of the analysis to stakeholders
Types of Visualizations and their Purposes Comparison of Values → Column Chart
Composition of Values → Pie chart
Distribution of Values → Histogram
Trends of values over time → Line Graph
Relationships between values → Scatterplot
Centralized Relational Databases 1. Tables: are data organized into a set of columns and rows
2. Fields (attributes): are the columns that contain descriptive characteristics about
the observations in the table
3. Records: are the rows, with each observation corresponding to a unique
instance of what is being described in the table
4. Primary Key: any field that functions as a unique identifier in a table
5. Foreign Key: creates relationships between two tables so that database users
can look up details of the observation based on the primary key/foreign key
relationship
Big Data data sets that are too large and complex for businesses' centralized systems to
capture, store, manage, and analyze
Characterized by the four V's:
1. Volume: sheer amount of data
2. Variety: different forms of data
3. Velocity: the speed that the data is being generated or the rate that the data is
being analyzed
4. Veracity: the underlying truthfulness, accuracy, and trustworthiness
Structured Data highly organized data that fits neatly
Unstructured Data data without internal organization
Semi-structured Data has elements of both structured & unstructured
Business Analytics & Data Management
Save
Students also studied
Chapter 1 Quiz CIS 348 Quizzes 1-4 business analytics chapter 1 BUS 312
36 terms 40 terms 49 terms 37 terms
Trin4710 Preview Avery_Kyle3 Preview gracemargueritte Preview Ale
Business Value all items, events, interactions that determine a company's financial health
Business Process a coordinated, standardized set of activities conducted by both people and
equipment to accomplish a specific business task
Business Analyst a data specialist who curates and uses data to help an organization make effective
business decisions
Data Overload vast amount of data prevents business analysts from properly synthesizing data
Analytics Mindset willingness and ability to specify which business questions need to be addressed,
find and extract pertinent data that might address those questions, analyze those
data, and then report the results to decision-makers.
-Understand the questions that their business and its decision-makers are asking
-Understand the nature and quality of the business's data
Data raw numbers and facts that have little meaning on their own
Information is data that are organized in a way that is meaningful to the user in a giver context
Information value chain is composed of the events and processes going all the way from the collection of
data to the compilation of information to the ultimate business decision
Data & Context → Information → Knowledge → Decision
, SOAR Analytics model 1. Specify the question
2. Obtain the data
-Relevant data: directly or closely connected to the question at hand
-Reliable data: reflect the facts or truth with little or no bias
-Data Integrity: refers to the combined accuracy, validity, and consistency of data
stored and used over time
3. Analyze the data
Analytics
-Ascendency model
-Descriptive Analytics (what happened)
-Diagnostics analytics (why did it happen and what are the causes)
-Predictive analytics (Will it happen?)
-Prescriptive analytics (What should we do?)
-Adaptive/Autonomous analytics (How can we learn?)
4. Report the results
-Data Visualization: graphic representation of data
-Exploratory Visualizations: is a graphical representation that is useful for
uncovering patterns and useful insights in the data, generally as a part of
descriptive or diagnostic analytics
-Explanatory Visualizations: graphical representation that is useful in
communicating the findings of the analysis to stakeholders
Types of Visualizations and their Purposes Comparison of Values → Column Chart
Composition of Values → Pie chart
Distribution of Values → Histogram
Trends of values over time → Line Graph
Relationships between values → Scatterplot
Centralized Relational Databases 1. Tables: are data organized into a set of columns and rows
2. Fields (attributes): are the columns that contain descriptive characteristics about
the observations in the table
3. Records: are the rows, with each observation corresponding to a unique
instance of what is being described in the table
4. Primary Key: any field that functions as a unique identifier in a table
5. Foreign Key: creates relationships between two tables so that database users
can look up details of the observation based on the primary key/foreign key
relationship
Big Data data sets that are too large and complex for businesses' centralized systems to
capture, store, manage, and analyze
Characterized by the four V's:
1. Volume: sheer amount of data
2. Variety: different forms of data
3. Velocity: the speed that the data is being generated or the rate that the data is
being analyzed
4. Veracity: the underlying truthfulness, accuracy, and trustworthiness
Structured Data highly organized data that fits neatly
Unstructured Data data without internal organization
Semi-structured Data has elements of both structured & unstructured
