Exam 1 Terms

Question 1

Datasets that are too large and complex for businesses’ existing systems to handle utilizing their traditional capabilities to capture, store, manage, and analyze these datasets.

Answer 1

Big Data

Question 2

A data approach that attempts to assign each unit in a population into a few categories potentially to help with predications.

Answer 2

Classification

Question 3

A data approach that attempts to divide individuals (like customers ) into groups (or clusters) in a useful way.

Answer 3

Clustering

Question 4

A data approach that attempts to discover associations between individuals based on transactions involving them.

Answer 4

Co-occurrence grouping

Question 5

The process of evaluating data with the purpose of drawing conclusions to address business questions.

Answer 5

Data Analytics

Question 6

Centralized repository of descriptions for all of the data attributes of the dataset.

Answer 6

Data dictionary

Question 7

A data approach that attempts to reduce the amount of information that needs to be considered to focus on the most critical items.

Answer 7

Data reduction

Question 8

A data approach that attempts to predict a relationship between two data items.

Answer 8

Link Prediction

Question 9

A variable that predicts or explains another variable.

Answer 9

Predictor variable.

Question 10

A data approach that attempts to characterize the “typical” behavior of an individual, group, or population by generating summary statistics about the data.

Answer 10

Profiling

Question 11

A data approach that attempts to estimate or predict, for each unit, the numerical value of some variable using some type of statistical model.

Answer 11

Regression

Question 12

A variable that responds to, or is dependent on, another.

Answer 12

Response variable

Question 13

A data approach that attempts to identify similar individuals based on data known about them.

Answer 13

Similarity matching

Question 14

Data that are organized and reside in a fixed field with a record or a file.

Answer 14

Structured data

Question 15

Data that do not adhere to a predefined data model in a tabular format.

Answer 15

Unstructured data

Question 16

A system that records, processes, reports, and communicates the results of business transactions to provide financial and nonfinancial information for decision- making purposes.

Answer 16

Accounting information system

Question 17

A special case of primary key that exists in linking tables. (made up of two primary keys in the table that it is linking)

Answer 17

Composite primary key

Question 18

An information system for managing all interactions between the company and its current and potential customers.

Answer 18

Customer Relationship Management system (CRM)

Question 19

Centralized repository of descriptions for all of the data attributes of the dataset.

Answer 19

Data dictionary

Question 20

A method for obtaining data if you do not have access to obtain the data directly yourself.

Answer 20

Data request form

Question 21

Attributes that exist in relational databases that are neither primary nor foreign keys. Provide business information.

Answer 21

Descriptive attributes

Question 22

A category of business management software that integrates applications from throughout the business into one system.

Answer 22

Enterprise Resource Planning system (ERP)

Question 23

The extract, transform, and load process that is integral to mastering the data.

Answer 23

ETL

Question 24

A means of storing data in one place, such as in an Excel spreadsheet, as opposed to storing the data in multiple tables, such as in a relational database.

Answer 24

Flat line

Question 25

An attribute that exists in a relational databases in order to carry out the relationship between two tables. Does not serve as the "Unique Identifier" for each table.

Answer 25

Foreign Key

Question 26

An information system for managing all interactions between the company and its current and potential employees.

Answer 26

Human Resource Management system HRM

Question 27

The second step in the IMPACT cycle; it involves identifying and obtaining the data needed for solving the data analysis problem, as well as cleaning and preparing the data for analysis.

Answer 27

Mastering the data

Question 28

An attribute that is required to exist in each table of a relational database and serves as the "unique identifier" for each record in a table.

Answer 28

Primary key

Question 29

A means of storing data in order to ensure that the data are complete, not redundant, and to help enforce business rules. (Communication and integrations of business processes)

Answer 29

Relational Database

Question 30

An information system that helps manage all the company's interactions with suppliers.

Answer 30

Supply Chain Management system (SCM)

Question 31

The opposite of the null hypothesis, or a potential result that the analyst may expect.

Answer 31

Alternative hypothesis

Question 32

The principle that in any large, randomly produced set of natural numbers, there is an expected distribution of the first, or leading, digit with 1 being the most common.

Answer 32

Benford's Law

Question 33

A data approach similar to regression, but used to test for cause and effect relationships between multiple variables.

Answer 33

Causal modelling

Question 34

A data approach that attempts to assign each unit in a population into a few categories potentially to help with predictions.

Answer 34

Classification

Question 35

A data approach that attempts to discover associations between individuals based on transactions involving them.

Answer 35

Co-occurrence grouping

Question 36

A data approach that attempts to reduce the amount of information that needs to be considered to focus on the most critical items.

Answer 36

Data reduction

Question 37

Technique used to mark the split between one class and another.

Answer 37

Decision boundaries

Question 38

An information system that supports decision-making activity within a business by combining data and expertise to solve problems and perform calculations.

Answer 38

Decision support system

Question 39

Tool used to divide data into smaller groups.

Answer 39

Decision tree

Question 40

Procedures that summarize existing data to determine what has happened in the past.

Answer 40

Descriptive analytics

Question 41

Procedures that explore the current data to determine why something has happened the way it has, typically comparing the data to a benchmark.

Answer 41

Diagnostic analyics

Question 42

An interactive report showing the most important metrics to help users understand how a company or an organization is performing.

Answer 42

Digital Dashboard

Question 43

A numerical value (1 or 0) to represent categorical data in statistical analysis. 1= something, 0= nothing

Answer 43

Dummy variable

Question 44

Used in addition to statistical significance in statistical testing. Demonstrates the magnitude of the difference between groups.

Answer 44

Effect size

Question 45

A measure of variability. Divided into four parts.

Answer 45

Interquartile range (IRQ)

Question 46

A modeling error when the derived model too closely fits a limited set of data points.

Answer 46

Overfitting

Question 47

Procedures used to generate a model that can be used to determine what is likely to happen in the future.

Answer 47

Predictive analytics

Question 48

Procedures that work to identify the best possible options given constraints or changing conditions.

Answer 48

Prescriptive analytics

Question 49

A data approach that attempts to identify similar individuals based on data known about them.

Answer 49

Similarity matching

Question 50

Describe the location, spread, shape, and dependence of a set of observations.

Answer 50

Summary Statistics

Question 51

Approach used to learn more about the basic relationships between independent and dependent variables that are hypothesized to exist.

Answer 51

Supervised approach

Question 52

A discriminating classifier that is defined by a separating hyperplane that works first to find the widest margin.

Answer 52

Support Vector Machines

Question 53

A set of data used to assess the degree and strength of a predicted relationship established by the analysis of training data.

Answer 53

Test data

Question 54

A predictive analytics technique used to predict future values based on past values of the same variable.

Answer 54

Time series analysis

Question 55

Existing data that have been manually evaluated and assigned a class, which assists in classifying the test data.

Answer 55

Training data

Question 56

A modeling error when the derived model poorly fits a limited set of data points.

Answer 56

Underfitting

Question 57

Approach used for data exploration looking for potential patterns of interest.

Answer 57

Unsupervised approach

Question 58

A global standard for exchanging financial reporting information that uses XML.

Answer 58

XBRL

Question 59

One way to categorize quantitative data, as opposed to discrete data. Height, or weight.

Answer 59

Continuous data

Question 60

Made when the aim of your project is to declare or present your findings to an audience. Charts made after the data analysis has been completed.

Answer 60

Declarative visualizations

Question 61

One way to categorize quantitative data, as opposed to continuous data. Whole numbers, like points in a basket ball game.

Answer 61

Discrete data

Question 62

Made when the lines between steps "P" (perform test plan), "A" (address and refine results), and "C" (communicate results) are not as clearly divided as they are in a declarative visualization.

Answer 62

Exploratory visualization

Question 63

The third most sophisticated type of data on the scale of nominal, ordinal, interval, and ratio. A quantitative data. No meaningful 0.

Answer 63

Interval data

Question 64

The least sophisticated type of data on the scale of nominal, ordinal, interval and ration. You can only count, group, or take a proportion. Ex: Hair color, gender, and ethic groups.

Answer 64

Nominal data

Question 65

A type of distribution in which the median, mean, and mode are all equal, so half of all the observations fall below the mean and the other half fall above the mean.

Answer 65

Normal distribution

Question 66

The second most sophisticated type of data on the scale of nominal, ordinal, interval and ratio. Can be counted and categorized like nominal data. Gold, silver, and bronze medals. Includes ranking.

Answer 66

Ordinal data

Question 67

The primary statistic used with quantitative data. Calculated by counting the number of items from a group, then dividing that number by the total.

Answer 67

Proportion

Question 68

Categorical data. All you can do with these data is count and group, and some cases, you can rank.

Answer 68

Qualitative data

Question 69

More complex than qualitative data. Can be further defined in 2 ways: interval and ratio. Can have mean, median, STD dev.

Answer 69

Quantitative data

Question 70

The most sophisticated type of data on the scale of nominal, ordinal, interval, and ratio. Can be counted, grouped, and the differences between each data point are meaningful like interval data.

Answer 70

Ratio data

Question 71

A special case of the normal distribution used for standardizing data.

Answer 71

Standard normal distribution

Question 72

The method used for comparing two datasets that follow the normal distribution. By using a formula, every normal distribution can be transformed into the standard normal distribution.

Answer 72

Standardization