w12d2 - Olap Data mining

Question 1

Main characteristics of an Olap application

Answer 1

• Fast (Deliver to the user in about 5 seconds)
• Analysis (copes with business logic, and relevant statistical analysis)
• shared (system implements all security requirements for confidentiality)
• Multidimentional (system must provide multidimentional views of the data, including full support for hierarchies an multiple hierarchies)
• information (all needed data and derived information is available)

Question 2

OLAP is used to ________
of _______
and of _______

Answer 2

produce reports
what is (especially trends)
what might be (by extrapolating and forecasting)

Question 3

normalization and other database design techniques focus on _______
Whereas reports usually _______

Answer 3

designing single records

combine multiple records

Question 4

A traditional report takes ______
that describes data in _______
The third dimension can be described by

Answer 4

a grid structure
up to 3 dimensions
The contents of cells at different {x,y} coordinates

Question 5

Dimensions provide \_\_\_\_\_\_\_\_\_
come from \_\_\_\_\_\_\_\_\_\_\_\_\_
may or may not have \_\_\_\_\_\_\_\_\_
may have \_\_\_\_\_\_\_\_\_
may share \_\_\_\_\_\_\_\_

Answer 5

Different ways of looking at a set of data
Different attributes of data
Particular ordering
Their own subdimensions
Data with other dimensions

Question 6

Temporal dimension includes
Events occur at
Activities occur over

Answer 6

activities and events

• a specific time only
• a range of times (Starting and ending event)

Question 7

Temporal dimension

Answer 7

Ordered linearly in terms of time from the start of an organization or activity up to the present and beyond to the future

Question 8

Temporal dimension includes a wide range of

Answer 8

granularities (often different records)

Question 9

Customer dimension often composed of

Answer 9

a number of discrete customers without a required ordering principle

Question 10

Customer dimension can be ordered based on

Answer 10

name, number, other dimensions

Question 11

Use of coding within customer-numbers may also provide additional dimensions such as

Answer 11

customer type dimension

vendor dimension

Question 12

location dimension is actually _________
Location may be limited to ________
Location is usually ordered relative to _____

Answer 12

multidimentional
a grouping of addresses based on some characteristic
other locations

Question 13

financial dimension generally contains ______
And is ordered _______

Measures for financial dimension

Answer 13

numeric information
linearly

exact $ values, being within some range, some # of sales slips

Question 14

Sub-dimensions

Answer 14

involve choices between different types of measures

Question 15

Different attributes are from different sub dimensions if

Answer 15

Neither attribute is an instance of the other attribute

Question 16

Granularities

Answer 16

Involve choices between different units for a given type of measure within a dimension

Question 17

Different attributes are of different granularities if ________
While normalization avoids ____________
It may not deal ______________

Answer 17

• one attribute can be converted with or without loss of some exactness into the other attribute
• multiple granularities of numeric values
• other types of granularites

Question 18

Olaps start with data in a ________

And progressivley reduces it by _______

Answer 18

data warehouse
slicing(removing whole columns)
Dicing(removing records based on attribute values or ranges of attribute values)
Consolidating (combining data by using finer granularities)
Drilling-down (examining more detailed granularities)
Processing (adding or replacing attributes based on the results of performing various computations on the data)

Question 19

Olap should allow users to easily work with the data by

Answer 19

Extracting copies of the data warehouse
Identifying dimensions in the data
selecting and working with dimension, subdimensions, and granularities,
Slicing, dicing, consolidating, drilling-down and processing data
Save the results form multiple stages for further processing
producing reports

Question 20

Data mining goes beyond \_\_\_\_\_\_\_\_
To \_\_\_\_\_\_\_\_
It operates on \_\_\_\_\_\_\_\_\_\_
It looks for \_\_\_\_\_\_\_\_\_\_
And suggests

Answer 20

Answering user questions
Identifying questions that users should consider
Data warehouses with good metadata
Trends and correlations across dimensions,
Models and visualizations that can be explored by the user

Question 21

Data mining techniques

Answer 21

Predictive modelling
Database segmentation
Link Analysis
Deviation Detection

Question 22

Predictive modelling

Answer 22

Classification - identifying groups based on common properties
Value Prediction - Extrapolating trends based on historical data

Question 23

Database segmentation

Answer 23

clustering based on multiple properties

Question 24

Link analysis

Answer 24

establishing associations between linked reports

Question 25

Deviation detection

Answer 25

Identifying records that deviate from the norm

Question 26

To be successful with olap and data mining

Answer 26

We need more than just tools

We need to know some things about the data

Question 27

Actual database contains

Answer 27

user data
data records in tables
metadata linked to individual data records in other tables
Data types and schemas including data types, constraints, relationships, permissions

Question 28

User programs typically

Answer 28

only interact with user data

leave data schema interations to the dba and dbms

Question 29

olap and data mining programs need to interact with

Answer 29

the actual data warehouse that contains user data
- data records in tables
- metadata linked to individual data records in other tables
Meta information that describes the attributes of the database in terms of data definitions, dimensions, granularities, transformations and other allowable types of processing