Understanding Big Data and its Impact on Business Flashcards Preview

Information Technology Management - C954 > Understanding Big Data and its Impact on Business > Flashcards

Flashcards in Understanding Big Data and its Impact on Business Deck (28)
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1
Q

distributed computing

A

Processes and manages algorithms across many machines in a computing environment.

2
Q

data mining

A

The process of analyzing data to extract information not offered by the raw data alone.

3
Q

data profiling

A

The process of collecting statistics and information about data in an existing source.

4
Q

data replication

A

The process of sharing information to ensure consistency between multiple data sources.

5
Q

recommendation engine

A

A data-mining algorithm that analyzes a customer’s purchases and actions on a website and then uses the data to recommend complementary products.

6
Q

estimation analysis

A

Determine values for an unknown continuous variable behavior or estimated future value.

7
Q

market basket analysis

A

Evaluates such items as websites and checkout scanner information to detect customers’ buying behavior and predict future behavior by identifying affinities among customers’ choices of products and services.

8
Q

affinity grouping analysis

A

Reveals the relationship between variables along with the nature and frequency of the relationships.

9
Q

cluster analysis

A

A technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible.

10
Q

classification analysis

A

The process of organizing data into categories or groups for its most effective and efficient use.

11
Q

data mining tools

A

A variety of techniques to find patterns and relationships in large volumes of information that predict future behavior and guide decision making.

12
Q

prediction

A

A statement about what will happen or might happen in the future, for example, predicting future sales or employee turnover.

13
Q

cube

A

The common term for the representation of multidimensional information.

14
Q

algorithm

A

A mathematical formula placed in software that performs an analysis on a data set.

15
Q

anomoly detection

A

The process of identifying rare or unexpected items or events in a data set that do not conform to other items in the data set.

16
Q

outlier

A

A data value that is numerically distant from most of the other data points in a set of data.

17
Q

fast data

A

The application of big data analytics to smaller data sets in near-real or real-time in order to solve a problem or create business value.

18
Q

data scientist

A

Extracts knowledge from data by performing statistical analysis, data mining, and advanced analytics on big data to identify trends, market changes, and other relevant information.

19
Q

infographics (information graphics)

A

Present the results of data analysis, displaying the patterns, relationships, and trends in a graphical format.

20
Q

data artist

A

A business analytics specialist who uses visual tools to help people understand complex data.

21
Q

analysis paralysis

A

Occurs when the user goes into an emotional state of over-analysis (or over-thinking) a situation so that a decision or action is never taken, in effect paralyzing the outcome.

22
Q

data visualization tools

A

Moves beyond Excel graphs and charts into sophisticated analysis techniques such as controls, instruments, maps, time-series graphs, and more.

23
Q

data visualization

A

Describes technologies that allow users to “see” or visualize data to transform information into a business perspective.

24
Q

business intelligence dashboard

A

Tracks corporate metrics such as critical success factors and key performance indicators and includes advanced capabilities such as interactive controls, allowing users to manipulate data for analysis.

25
Q

optimization model

A

A statistical process that finds the way to make a design, system, or decision as effective as possible, for example, finding the values of controllable variables that determine maximal productivity or minimal waste.

26
Q

forecasting model

A

Predictions based on time-series information allowing users to manipulate the time series for forecasting activities.

27
Q

regression model

A

Includes many techniques for modeling and analyzing several variables when the focus is on the relationship between a dependent variable and one or more independent variables.

28
Q

time-series information

A

Time-stamped information collected at a particular frequency.