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Mod 1 - Data Analytics And Management Flashcards | StudBud
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Mod 1 - Data Analytics And Management
Mod 1 - Data Analytics And Management
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Mod one of Analytics Mod 1 - Data Analytics And Management
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Answers
1
Descriptive Analytics is also known as the
Phase 2.1 → Why did it happen?
Phase 2 → What Will happen? (future risks and Opportunities)
Phase 3 → What are the consequences of our decisions?
Phase 1 → What Happened? (Patterens, trends, relationships)
2
Prescriptive Analytics
historical data to highlight useful data to help make future decisions
the likelihood of future events or outcomes based on historical data.
who, what, where, when, how and why we are using analytics in our business.
predict future outcomes but also show the implications of all decisions.
3
The main parts of a Data Management Plan are
Data Quality
Data Storge
Data Integration
all are correct
4
Unstructured data
data
Unorginized data (emails, surveys, social media, etc.)
Orginized data
Excel
5
A CONS of
Predictive Analytics
Simulate Probability and good for Forecasting
Can keep up with rapid change
Challenges in the long-term (too much change!) and garbage data
Easy to use
6
Prescriptive Analytics is also known as the
Phase 2 → What Will happen? (future risks and Opportunities)
Phase 1 → What Happened? (Patterens, trends, relationships)
Phase 3 → What are the consequences of our decisions?
Phase 2.1 → Why did it happen?
7
Predictive Analytics
summarizes historical data to make future decisions
predict future outcomes but also show the implications of all decisions.
likelihood of future events or outcomes based on historical data
who, what, where, when, how and why we are using analytics in our business.
8
How is Dat management different from governance
Data Managmnet is the core rules surround how data is handled → leads to DG
DM is spine that connects all segments of the information lifecycle
Both are they same
Data Governace is identifying an organization's key entities
9
Three types of Analytics
1. Descriptive 2. Predictive 3. Prescriptive
1. Pictorial 2. Historical 3. Produce
1. Historical 2. Mindreading 3. Fortune telling
1. Diazepam 2. Prozac 3. Penicillin
10
What is information?
data + meaning
all of the above
Structured/orginized data
Processed infomation
11
A positive of using
Descriptive Analytics is
Easy to deploy into business operations and Forecasting
Simulate Probability
Requires a lot of historical data.
automate decisions
12
Knowledge
Learing the alphabet
Orginized data
Knowledge is what is understood, learned or being aware of.
I know things
13
How to choose the right analytic approach?
Ask Google, for it knows things
Do what ever the boss man tell you
Flip a coin and hope for the best
Know what question you are asking and what you want answered
14
6 parts of Data Quality
Predcivive, descriptive, analysation, governace, sales data, Chosen
All data is quality
Matching, Proofing, Cleasning, Parsing, Matching, enrchimnet
Clean, Complete, Calculable, Comprehesive, Credible, Chosen
15
A CON of using
Descriptive Analytics is
Garbage data in, garbage data out!
Requires a lot of historical data, and is a surface view only
Simulate Probability
Very complex
16
Data Quality techniques
Clean, Complete, Calculable, Comprehesive, Credible, Chosen
Predcivive, descriptive, analysation, governace, sales data, Chosen
Matching, Proofing, Cleasning, Parsing, Matching, enrchimnet
Interview the data
17
Why is a Data Governance Strategy Very Important?
Because it detemens who is touching the data
real-time data to help with real-time business decisions
All of the above
Will provide your organization with a “SINGLE SOURCE OF TRUTH
18
Prescriptive Analytic Examples
Identify areas of cost or profit in the business.
Automate some business decisions
Predict industry and business risks
At this point I know it's ALL OF THE ABOVE
19
Structured Data
80 - 90%
emails
databases or CRMS
Data is organized and contains a ‘structure’.
20
A positive of
Predictive Analytics
Challenges in the long-term (too much change!)
Simulate Probability and good for Forecasting
Easy to use
Can keep up with rapid change
21
What is data management?
Using excel despite knowing python is better
When AI's become your manager
is the process (or standard operating procedures),
is the art of managing data as a valuable resource
22
Opportunities in the Hospitality Industry
Mitigate Risks
Optimize Business Processes
all above
Increased ROI and Effectively manage compliance requirements.
23
Descriptive Analytics
identifies likelihood of future events outcomes based on historical data
Shows us how we can make it happen
summarizes historical data -highlight useful data to make future decisions
Uses historical data to make acurate discptions about movies
24
What is Data?
Numbers and letters
Random things
Symbols, characters and numbers stored by a computer that tells you nothing
25
Predictive Analytics is also known as the
Phase 3 → What are the consequences of our decisions?
Phase 2 → What Will happen? (future risks and Opportunities)
Phase 2.1 → Why did it happen?
Phase 1 → What Happened? (Patterens, trends, relationships)
26
Data management is the same as Data Governance
False
True
27
Info Example
Insights Intuition
Facts
Symbols Numbers Unstructured
Orginized data like Excel sheet
28
3 V’s in analytics?
Volume, Vectors, Various
Vroom, Vroom, Vroom
Volume Velocity Variety
Vectors, Vertex, Varity
29
How much Data is Unstructured
80-90%
I got 99.9% problems but data ain't one
70-85%
10-20%
30
Data Integration
the process of bringing data from disparate sources together
Make data go one place
Put the data in a box
Making sure your data is integrel
31
Data storage should be?
Owned by our google overlords
warehouses
Large, pricey, slow
Cheap, Flexible, Faster, Scalable
32
A CON of
Prescriptive Analytics
Very Complex and needs lots of data
Easy to use
Analysis how many prescriptive drugs you Take
Can show action we "should take" and autome decisions
33
A Positive of
Prescriptive Analytics
Very Complex and needs lots of data
Can show action we "should take" and autome decisions
Analysis how many prescriptive drugs you Take
Easy to use
34
What can structured data help with?
facilitates searching and finding patterns or significant conclusions.
It helps build data houses
It makes your Excel Doucmnets look nice
Bring balance to the force
35
Data Warehouses
All are right
All data in one place
Inflexible to new. data or changes to data collection
a central repository of information that can be analyzed
36
Data Governance
who, what, where, when, how and why we are using analytics in our business.
all of the above
Who controls and touches the data
37
Predictive Analytic Examples
Fraud Detection
All of the above
Trade Risks
Inventory Forecasting help
38
Knowledge Example
Emails from my boss
Unstructured Symbols Numbers
Insights Intuition trends & patterns
Orginized data like Excel sheet
39
How is Data governance different from management
Data Goverance is the data lifecyle of organization needs
Both are they same
Data Governace is identifying an organization's key entities
Data Goverance is the core rules surround how data is handled → leads to DM
40
Data Example
Insights Intuition
Back-end information
GATACA
Unstructured Symbols Numbers
41
Example of Descriptive Analytics
Financial Statment Analysis
All of the Above, baby!
Medical History
Previous Sales Results
42
What are some
Data Management Challenges in the Hospitality Industry
high-touch and low-tech
We are an industry of emotional decisions
all are challanges
Balance between profits and guest experience has usually been a trade-off
