Mid-Term Study Flashcards

Pass the Mid-term

1
Q

Essential components of modern business decision making

A
  • Give business a competitive advantage
  • Greater Revenue
  • Improved efficiency/ lower production cost
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2
Q

Business analytics

A

Helps organizations make quicker and better decisions and take action with greater confidence

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3
Q

What makes Big Data possible

A

High level processors make big data possible

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4
Q

What is Big Data

A

a large data set commonly used by the larger companies while being larger than a gigabyte (terabyte)

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5
Q

Why do we need Business Analytics

A

Information: Data analytics provides information on every aspect of business

Bias: we have a capacity for taking in information and our shortcuts hold us back

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6
Q

People misunderstand randomness

A

Expect independent trials to not exhibit “streakiness”

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7
Q

Confirmation Bias

A

A bias where we place a greater weight on additional information that supports our bias

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8
Q

Business Analytics

A

Data analytics being applied to business decisions-creates foundation of information and insights for business managers

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9
Q

Descriptive Analytics

A

Serves as the foundation and answers the question “What Happened”
-uses current and historical data to find trends
-effective for communicating change over time

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10
Q

Diagnostic Analytics

A

Addresses “Why did this happen?” It helps determine root problems of/in trends

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11
Q

Predictive Analytics

A

“What might happen in the future?”
Utilizes past data to forecast scenarios, trends, and events and inform business strategies

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12
Q

Perspective Analytics

A

“What should we do next?”
Consider all relevant data to chart optimal path forward

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13
Q

If you don’t use data you will…

A

FALL BEHIND

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14
Q

Data Science

A

Focused on making sense of raw data using algorithms statistical methods, models, and computer programming

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15
Q

Examples of “actionable business decisions”

A
  • Open a new market
  • Hire additional salesperson
  • Invest in new products
  • Close down a factory
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16
Q

Ethics WHH

A
  • Who owns the data
  • How is data being shared
  • How is the data “monetized”
17
Q

5 Principles of Data Ethics

A
  1. Ownership
  2. Transparency
  3. Privacy
  4. Intention
  5. Outcomes
18
Q

Tools for Data Analytics

A
  • You
  • Creativity
  • The “GUT”
  • Communication skills