Mcts 70-448 Chap 9 Working With Ssas Data Mining

Front 1

What does the term data mining mean?

Back 1

Data mining enables you to deduce hidden knowledge by examining or training the data. The knowledge you find is expressing patterns and rules.

Front 2

What is the unit of examination called?

Back 2

Case, which can be interpreted as one apperance of an entity or a row in a table

Front 3

What does a Data model store?

Back 3

Information about the variables you use, the algorithms you implement on the data, and the paramaters of the selected algorithms, and (after training is complete) extracted knowledge

Front 4

What are the two main classes of techniques in data mining?

Back 4

Directed approach and undirected approach

Front 5

What are the four parts of the Data Mining Life Cycle?

Back 5

1. Identifying the business prblem
2. Using data mining techniques to transform the data into actionable information
3. Acting on the information
4. Measuring the results

Front 6

What are the four stages in the transform phase of the Data Mining Life Cycle?

Back 6

Prepre the data
Create the models
Examine and evaluate the models
Deploy selected model

Front 7

What are the two most important factors in the success of a data mining project?

Back 7

Data preparation and understanding

Front 8

What are four kinds of variables you can use to measure values?

Back 8

Categorical or nominal attributes
Ranks
Intervals
True numeric variables

Front 9

What is the difference between a simple or complex case?

Back 9

Complex cases have nested tables in one or more columns. These need to be glattened or normalize them into standard rowsets where you perform joins between parent and child tables

Front 10

What two kinds of data do you need to decide how to handle?

Back 10

Outliers and missing data

Front 11

What is the key to properly preparing the training set and the test set?

Back 11

Statistically split the data randomly (you can use Row Sampling and Percentage Sampling Transformations in SSIS)

Front 12

How do you verify that your data split is random?

Back 12

The first four moments (mean, standard deviation, skewness, and kurtosis)

Front 13

What is kurtosis?

Back 13

Kurtosis measures peakedness of probability distribution, showing whether the distribution is narrow and high around the center or lower close to the center

Front 14

What do you use to create your models?

Back 14

Analysis Services Project template in BIDS. You define the data source and DSV objects in the same way you create them for UDM dimensions and cube

Front 15

What is a data mining structure?

Back 15

A data structure that defines the domain from which you build your mining models, it specifies the source data through a DSV, the columns, and training models. Can contain multiple mining models

Front 16

How many models should you make?

Back 16

Multiple. Evaluate them all, see if they agree, and then deploy the one that works the best.

Front 17

What are the four options in the mining model for defining the use of columns?

Back 17

Input
Predictable
Input and predictable
Ignored

Front 18

What are the nine data mining algorithms included in SSAS?

Back 18

Association rules
Clustering
Decision trees
Linear regression
Logistic Regression
Naive Bayes
Nueral Network
Sequence Clustering
Time Series

Front 19

What do you need to use in order to anaylze texts such as articles in magazines?

Back 19

Text mining, which is not part of SSAS. Instead, use the two SSIS transformations for text mining: Term Extraction and Term Lookup

Front 20

Which algorithm do advanced e-mail SPAM filters use?

Back 20

Naive Bayes

Front 21

What is the Association Rules algorithm used for?

Back 21

Market based analysis. Used to find cross-selling opportunities

Front 22

What is the Clustering Algorithm used for?

Back 22

Groups cases from a dataset into clusters of similar charctersitcs. Used for grouping customers for a CRM applicaiton. Also for searching for anomalies in data, as in fruad detection

Front 23

What is the Decision Trees Algorithm used for?

Back 23

The most popular data mining algorithm. Easy to understand. Used to predict discrete and coninuous variables. A tree that predicts continous variables is a regression tree

Front 24

What is the Linear Regression algorithm?

Back 24

Predicts continuous variales using a single multiple linear regreasion formula. It is a regression tree with no splits.

Front 25

What is the Logistic Regression algorithm?

Back 25

A Logistic Regression algorithm is a Neural Network without any hidden layers.

Front 26

What is the Naive Bayes algorithm?

Back 26

Calculates probabilities for each possible state of the input attribute. Fast and a good starting point. Doesn't support continuous attributes

Front 27

What is the Neural Network algorithm?

Back 27

Serches for nonlinear functional dependencies. Harder to predict than linear lagorithms such as decision trees and not often used for business.

Front 28

What is the sequence clustering algorithm?

Back 28

Searches for clusters based on a model rather than simliarity of cases. Builds markov chains with combinations of all possible states and assigns probabilities of moving from one state to another. Used for analyzing web sites.

Front 29

What is the time series algorith?

Back 29

Created for forecasting continuous variables using ART Auto-Regression Trees and ARIMA Auto-Regressive Integrated Moving Average algorithms

Front 30

What three main tools are included in BIDS for creating mining models?

Back 30

Data Mining Wizard
Data Mining Desinger
Data Mining Viewers

Front 31

What three things do you do with the Data Mining Wizard?

Back 31

Define the DSV and the tables and columns from the DSV that you want to use
Add an initial model to the structure
Partition the data into training and test sets

Front 32

What five tasks can you perform in the Data Mining Designer?

Back 32

Modify the mining structure
add additonal mining models to the structure
Process the strcuture and browse the models using Data Ming Viewers
Check the accuracy of the models using a lift chart and other techniques
Create DMX prediction queries using you models

Front 33

What are the two discretization methods in SSAS 2008?

Back 33

EqualAreas and Clusters

Front 34

What are the different components that make up the SQL Server BI Suite?

Back 34

SSAS cubes
SSAS data mining
SSRS
SSIS

Front 35

What are three ways to prepare training sets and test sets?

Back 35

The Data Mining Wizard and Data Mining Designer in BIDS to specify the percentage of the holdout data for the test set
Use the TABLESAMPLE option of the T-SQL SELECT statement
Use the SSIS Row Sampling Transfromation and Percentage Sampling Transformation

Front 36

What are the five supported content types for columns?

Back 36

Discrete
Continuous
Discretized
Ordered
Cyclical

Front 37

What are the three key column types?

Back 37

Primary
Key Sequence
Key Time

Front 38

What algorithm did Microsoft develop for clickstream analysis?

Back 38

Sequence Clustering

Front 39

What is your case table and case-level columns when you mine an OLAP cube?

Back 39

A dimension is the case table and any measure group or fact table connected with the selected dimension can be used as a case-level column

Front 40

Why can't you use a mining model as a dimension in the same cube in which you used it as the source for the model?

Back 40

You would get a circular reference an never stop processing

Front 41

Which algorithm would you use to find the best way to arrange products on shelves in a retail store?

Back 41

Associtation rules

Front 42

What does a lift chart show?

Back 42

The compares the performance of models when predicting a value
Or shows the quality of global predictions

Front 43

What does a classification matrix show?

Back 43

Compares te actual valuses compared to the predicted values

Front 44

What are the five settings you can define for cross-validation?

Back 44

Fold Count (how many partitions created in training data)
Max Cases
Target Attribute
Target State
Target Threshold (minimum accuracy needed for a prediction to be counted as correct)

Front 45

On a real data mining project, which two tasks will take most of the time?

Back 45

Data preparation and then validation of predictive models

Front 46

What are the three measures that give you information about the quality of the rules that the Association Rules algorithm finds?

Back 46

Support (How many times items were found together)
Probability (build direction A-->B not B-->A)
Importance (Score of the rule, how coorelated they are)

Front 47

What two paramaters can be used to control the creation o historical models?

Back 47

HISTORICAL_MODEL_COUNT (number of model built)
HISTORICAL_MODEL_GAP (Number of time slices between historical models)

Front 48

What are the two kins od DMX statements?

Back 48

DDL Data Definition Language
DML Data Manipulation Language

Front 49

What are eight DMX DDL statements?

Back 49

Create mining strucutre
Alter mining structure
Create mining model
Export
Import
Select into
Drop Mining Model
Drop Mining Structure

Front 50

What are four DMX DDL statements?

Back 50

Insert into (which trains the model)
Select
Update
Delete

Front 51

Do dataset tables support nested tables?

Back 51

No

Front 52

What are the three types of charts you can use to evaluate predictive models?

Back 52

Lift chart for global statistics
Lift chart for a single value
Profit chart

Front 53

How do you evaluate a Time Series model?

Back 53

You can make historical predictions to evaluate a time series model

Front 54

How do you evaluate a clustering model?

Back 54

You should evaluate clustering models from a business perspective

Front 55

Using DMX, can you add a mining model to an existing structure so that you can share the structure with other models?

Back 55

You can use the ALTER MINING STRUCTURE dmx statement to add a mining model to an existing structure so it can be shared with other models

Front 56

Can you use DMX to drill through to the ample cases you used for trianing a mining model?

Back 56

Yes, you can use the dmx SELECT FROM <model>.CASES syntax to drill through to the sample cases you used to train a mining model

Front 57

What are the four SSAS general data mining properties?

Back 57

AllowSessionMiningModels
AllowAdHocOpenRowsetQueries
AllowedProvidersInOpenRowset
MaxConcurrentPredictionQueries

Front 58

If you want to let applications use the SSAS data mining features, which data mining property do you need to set as "true"?

Back 58

AllowSessionMiningModels

Front 59

What are your four options for impersonating information in a data source?

Back 59

Use a specific username and password
Use the service acount
Use the credentials of the current user
Inherit (Impersonates current users)

Front 60

What permission must a user have to connect to an SSAS database through SSMS or BIDS?

Back 60

Read Definition permission for a complete SSAS database

Front 61

What is a data mining structure?

Back 61

A blueprint of the database schema that is shared by all mining models inside the structure

Front 62

What is the defaul CacheMode property and what does it allow?

Back 62

The default CacheMode property is set to KeepTrainingCases which caches the data mining model training data to allow the user to issue drill-through queries to see the source data. You can set it to ClearAfterProcessing to avoid keeping large data volumes in the cache

Front 63

What is another phrase for training the model?

Back 63

Model processing

Front 64

What are the four steps to processing a mining structure?

Back 64

Save changes in BIDS
On the Mining Structure tab click the Process the Mining Structure button
In the process dialog box select the desired processing option, then click run
Watch the process prgress dialog box

Front 65

Can you use SQL server logins for SSAS authentication?

Back 65

No. SSAS supports Windows authentication only

Front 66

Do end users need the Process permission on a mining structure?

Back 66

No

Front 67

As an administrator, how would you prevent usage of the clustering data mining algorithm?

Back 67

Use the Analysis Services Properties dialog box in SSMS

Front 68

What processing option deletes the training data in a mining structure without affecting its mining models?

Back 68

Use the Process Clear Structure option to pruge the structure data without affecting the models inside the structure

Front 69

Can an SSRS report use a mining model as its source?

Back 69

Yes

Front 70

How do you brows mining models?

Back 70

The DMX language. You can also use the Prediction Query Builder in SSMS and BIDS to create prediction DMX queries