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Business Analytics with Excel > 2 Week > Flashcards

2 Week Flashcards

1
Q

Analytics with Ba

A
  1. Recognize a problem
  2. Define the problem
  3. Structure the problem
  4. Analyze the problem
  5. Interpret results
  6. Implement the solution
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2
Q

Realizing the problem

A

Findinf sing of issues

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3
Q

Define the problem

A

clearly define the problem, what is part and what is not?

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4
Q

Structure the problem

A

stating goals and objectives, charactherizing the possible decisions

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5
Q

Analyze the problem

A

Analytics plays a major role, involves experimentation and modelling process.

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6
Q

Interpret reults and make decision

A

What do the results found by the model mean for the application?

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7
Q

implement the solution

A

Translate the results of the model back to the real world

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8
Q

data

A
  • Raw facts
  • No context
  • Just numbes and text
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9
Q

Information

A
  • Data with context
  • Processed data
  • Value added to data
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10
Q

Knowledge

A
  • Knowing what information is required

* Knowing what the information means

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11
Q

Data source (internal)

A
  • Annual reports
  • Accounting Audits
  • Financial profitability
  • Operation managment performance
  • Human resource measurements
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12
Q

Data source(External)

A

*Economic trends
*Marketing research
*

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13
Q

New development

A
  • Web behavour
  • Social Media
  • IOT
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14
Q

Big Data

A

refer to massive amounts of business data from a wide variety of sources, much of wich is avalaible in real time, and much of which is uncertain or unpredictable. IBM calls the caractheristics volumen, variety,

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15
Q

Database

A

A collection of related tables containing records on peoplem places or things (extract with SQL)

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16
Q

Data set

A

A collection of data (often a single “spread sheet” or data mining table)

17
Q

Discrete (Type of data)

A

derived from counting something (Ex. Is the deliver in time?)

18
Q

Continous (Type of data)

A

based on a continous scale of measurement (any metrics involving money, lenght, time)

19
Q

Measurment scales (Categorical (nominal data))

A

sorted into categories according to specified characteristics [Equality: IAre the colors the same?]

20
Q

Measurment scales(Ordinal data)

A

can be ordered and ranked according to relationship to another [sort: Is this value larger or better?]

21
Q

Measurment scales (Interval data)

A

there is order and the differences between the values is meaningful [Temperatu]

22
Q

Measurment scales (ratio data)

A

has all the properties of an internval variable [prices]

23
Q

Reliability

A

data accurate and consistent

24
Q

validity

A

data measures what is supose to be measured

25
Q

Experiment

A

Method for testing differen assumptions by trial and error under conditions constructed and controlled. Independed variables are allow to change and the effects are analyzed

26
Q

“Test and learn approach”

A

take action with one group then take action with another group and check

  1. Focus on individuals and think short term (immidate response )
  2. Keep it simple
  3. start with prof-of concept test
  4. when results come in, slice the data
  5. try out-of-the-box thinking
  6. Measure everything that matter.
  7. Look for natural experiments
27
Q

Tools

A

data base queries and analysis:

  • spreadsheets
  • Data manipulation
  • Data visualization
  • Dashboard to report KPM
28
Q

Descriptive analytics

A
  • Data source & types
  • Data wharehouse
  • Ghapical represatation
  • Data visualiztion
  • Analytics using SW
29
Q

Predictive analysys

A
  • Simple linear regression
  • Multiple regrassion model
  • Non-linear refression
  • Time series forecasting
  • Simulation models
30
Q

Model

A

an abstraction or represatin of a real system

*Capture most importan featured

31
Q

Predcitve (Category) ANOMALY

A

something out of the common

32
Q

Predcitve (Category) ASSOCIATION LEARNING

A

classification and cluster

33
Q

prescriptive analysis

A
  • Optimization model
  • Simulation model
  • Decision analysis
  • spreadsheet models

Business Analytics with Excel (3 decks)

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