Finals M1 Flashcards
Three Terms in Business Literature are often related to one another
Analytics
Business Analytics
Business Intelligence
Begins with a data set (a simple collection of data or a data file) or commonly with a database (a collection of data files that contain information on people, locations, and so on).
Business Analytics
A simple collection of data or a data file
data set
A collection of data files that contain information on people, locations, and so on.
database
As databases grow, they need to be stored somewhere.
True
Hardware and software used for data remote storage, retrieval, and computational functions
computer clouds
A collection of databases used for reporting and data analysis store data.
data warehousing
Database storage areas have become so large that a new term was devised to describe them.
True
Describes the collection of data sets that are so large and complex that software systems are hardly able to process them .
Big data
They define ________ as anything that is not big data.
little data
describes the smaller data segments or files that help individual businesses keep track of customers.
Little data
Using analytics as a means of sorting through data to find useful information, the application of analytics has found a new purpose.
True
Can be defined as a process that involves the use of statistical techniques (measures of central tendency, graphs, and so on), information system software (data mining, sorting routines), and operations research methodologies (linear programming) to explore, visualize, discover and communicate patterns or trends in data.
analytics
measures of central tendency, graphs, and so on
statistical techniques
information system softwares:
data mining, sorting routines
operations research methodologies aka?
linear programming
can be defined as a process that involves the use of statistical techniques, information system software , and operations research methodologies to explore, visualize, discover and communicate patterns or trends in data.
Analytics
Analytics is an older term commonly applied to all disciplines, not just business.
True
convert data into useful information.
analytics
Three types of analytics
descriptive , predictive , and prescriptive
The application of simple statistical techniques that describes what is contained in a data set or database.
Descriptive analytics
An application of advanced statistical, information software, or operations research methods to identify predictive variables and build predictive models to identify trends and relationships not readily observed in a descriptive analysis.
Predictive analytics
An application of decision science, management science, and operations research methodologies (applied mathematical techniques) to make best use of allocable resources.
Prescriptive analytics
To identify possible trends in large data sets or databases.
Descriptive analytics
To build predictive models designed to identify and predict future trends.
Predictive Analytics
To allocate resources optimally to take advantage of predicted trends for future opportunities.
Prescriptive Analytics
________________ statistics, including methodologies like:
measures of central tendency (mean, median, mode)
measures of dispersion (standard deviation)
charts
graphs
sorting methods
frequency distributions
probability distributions
sampling methods
Descriptive
____________statistics, uses:
Multiple regression
ANOVA
Information system methods like data mining and sorting.
Operations research methods like forecasting models.
Predictive
________________ statistics, uses operations research methodologies like linear programming and decision theory.
Presciptive
answers the questions what happened and why it happen
Descriptive analytics
What exactly is the problem?
How many, how often, where?
What happened?
Descriptive analytics
answers the question what will happen:
predictive analytics
What will happen next if…?
What if these trends continue?
What could happen…?
What actions are needed?
predictive analytics
Anticipates what will happen, when it happened, and also why it happened:
prescriptive analytics
How can we achieve the best outcome including the effects of variability?
How can we achieve the best outcome?
prescriptive analytics
____________ is focused on generating insightful information from data sources
analytics
____________________ goes the extra step to leverage analytics to create an improvement in measurable business
business analytics
the three types of analytics are applied sequentially (descriptive, then predictive, then prescriptive).
True
can be defined as a process beginning with business-related data collection and consisting of sequential application of descriptive, predictive, and prescriptive major analytic components, the outcome of which supports and demonstrates business decision-making and organizational performance.
BA
Policing/Security
Transportation
Fraud and Risk Detection
Manage Risk
Delivery Logistics
Web Provision
Proper Spending
Customer Interactions
City Planning
Healthcare
Travel
Energy Management
Internet/Web Search
Digital Advertisement
Where is Analytics Applied
____________ will translate the business challenges into operational measures that can be monitored over time, not only for analytics impact, but for the entire company.
Metrics
is a data point at a single point in time
Measurement
Metrics is Measurement with context
True
Measurement is Metrics with context
False
____________ means by which your company can measure progress and business analytics impact.
Objective
When is Analytics Not Practical?
When There’s No Data
When There’s No Precedent
When the Decision Maker Has Considerable Experience
When the Variables Can’t Be Measured
The Three Secret of Success
EUR
Establish business analytic culture
Understand analytic in play
Recognize the insights as a competitive advantage.
Challenges of Business Analytics
ECC
Environment
Competition
Customers
Predictive analytics methodologies
MR
A
DMDS
FM
Multiple regression
ANOVA
Information system methods like data mining and sorting.
Operations research methods like forecasting models.
Prescriptive analytics methodologies
Decision Theory
Linear Programming
