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Business Analytics Exam 1 questions with right answers.
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Business Analytics Exam 1 questionswith right answers.
course objectives ANS - To gain an understanding of how managers use business analytics to formulate
& solve business problems to support managerial decision making
To become familiar with the processes needed to develop, report, and analyze business data
To give you the skills to solve complex business problems using analytical techniques and tools on
spreadsheets
What do we use each for?
Excel
Tableau
XLMiner
Solver ANS - Excel + Tableau- Data visualization
XLMiner - Data mining
Solver - Optimization
Analytics ANS - Process of transforming data into actions through analysis
That is, transforming data into useful knowledge to solve business problems
process may be initiated by the desire to address specific problems or the need to explore and learn
from existing data
why Is analytics important? ANS - Data is everywhere!!
Every sector
Every economy
Every organization
, The US alone faces a shortage of 1.5 Million analysts to analyze big data and make decisions based on
their findings
90% of the data in the world today has been created in the last ANS - 2 years
potential value from utilizing data ANS - could be more than $300 Billion in value every year
it is the core of enterprise, companies make more money when using data analytics
4 types of business analytics ANS - descriptive, diagnostic, predictive, prescriptive
descriptive analytics ANS - preliminary stage of data processing that creates a summary of historical
data to yield useful information and possibly prepare the data for further analysis.
(What happened?)
data visualization, dash boards
diagnostic analytics ANS - used for discovery or to determine why something happened. For example,
for a social media marketing campaign, you can use descriptive analytics to assess the number of posts,
mentions, followers, fans, page views, reviews, pins, etc. There can be thousands of online mentions
that can be distilled into a single view to see what worked in your past campaigns and what didn't
(why did it happen?) data modeling and trend lines
Prescriptive Analytics ANS - really valuable, but largely not used. Where big data analytics in general
sheds light on a subject, prescriptive analytics gives you a laser-like focus to answer specific questions
(how can we make it happen) optimization and simulation ( imitation of the operation of a real-world
process )
Predictive Analytics ANS - use big data to identify past patterns to predict the future. For example,
some companies are using predictive analytics for sales lead scoring. Some companies have gone one
step further use predictive analytics for the entire sales process, analyzing lead source, number of
communications, types of communications, social media, documents, CRM data, etc. Properly tuned
predictive analytics can be used to support sales, marketing, or for other types of complex forecasts.
(what will happen) data mining n predictive forecasting
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