Glossary Terms - Module 1 Flashcards

1
Q

Analytical skills

A

Qualities and characteristics associated with using facts to solve problems

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2
Q

Analytical thinking

A

The process of identifying and defining a problem, then solving it by using data in an organized, step-by-step manner

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3
Q

Context

A

The condition in which something exists or happens

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4
Q

Data

A

A collection of facts

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5
Q

Data analysis

A

The collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making

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6
Q

Data analyst

A

Someone who collects, transforms, and organizes data in order to draw conclusions, make predictions, and drive informed decision-making

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7
Q

Data analytics

A

The science of data

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8
Q

Data design

A

How information is organized

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9
Q

Data-drive decision-making

A

Using facts to guide business strategy

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10
Q

Data ecosystem

A

The various elements that interact with one another in order to produce, manage, store, organize, analyze, and share data

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11
Q

Data science

A

A field of study that uses raw data to create new ways of modeling and understanding the unknown

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12
Q

Data strategy

A

The management of the people, processes, and tools used in data analysis

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13
Q

Data visualization

A

The graphical representation of data

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14
Q

Dataset

A

A collection of data that can be manipulated or analyzed as one unit

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15
Q

Gap analysis

A

A method for examining and evaluation the current state of a process in order to identify opportunities for improvement in the future

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16
Q

Root cause

A

The reason why a problem occurs

17
Q

Technical mindset

A

The ability to break things down into smaller steps or pieces and work with them in an orderly and logical way

18
Q

Visualization

A

(Refer to data visualization)

19
Q

What are the five parts of Analytical Thinking?

A
  1. Visualization
  2. Strategy
  3. Problem orientation
  4. Correlation
  5. Big picture and detail-oriented thinking
20
Q

What are the five core Analytical Skills?

A
  1. Curiosity
  2. Understanding context
  3. Having technical mindset
  4. Data design
  5. Data strategy