Standard SRMU

8/16/2019 Standard SRMU

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Topic Questions Option (A) Option (B)

DM

A data warehouse is which of the

following? Can be updated by end users

Contains numerous naming

conventions and formats.

DM

A star schema has what type of relationship

between a dimension and fact table? Many-to-many One-to-one

DM Fact tables are which of the following? Completely demoralized Partially demoralized

DM

A snowflake schema is which of the

following types of tables? Fact Dimension

DM

A goal of data mining includes which of the

following?

To explain some observed event

or condition To confirm that data exists

DM

OLAP databases are called decision support

system ? TRUE FALSE

DM In Star Schema Dimension tables are Short and Fat Long and Thin

DM The data in Data Warehouse is generally Clean Data Dirty Data

DM Choose two

a p m a e eves t at

portions of data can becombined based on relevance of

data and can be used for

reporting

Inmon believes that portions ofdata can be combined based on

relevance of data and can be

used for reporting

DM

In which type of SCD(Slowly changing

dimensions) do we preserve history of data: Type One Type Two

ETL During ETL load we generally have Unsorted data for Aggregator Sorted data for Aggregator

DM

Sequence of jobs to load data in to

warehouse

First load data into fact tables

then dimension tables, then

Aggregates if any

First load data into dimension

tables, then fact tables, then

Aggregates if any

DM Snowflaking means Normalizing the data Denormalizing the data

OLAP

Drill Across generally use the following

join to generate report Self Join Inner Join

DM In general data in Data Warehousing is Normalized Denormalized

DM Consolidated data mart is First level data mart Second level data mart

DM

In 4 step dimensional process, declaring

gain of business process is First Step Second Step

DM Dimensions are Confirmed when They are different

subset of another

DM

You need to create an index on the SALES

table, which is 10 GB in size. You wantyour index to be spread across many

tablespaces, decreasing contention for

index lookup, and increasing scalability and

manageability.Which type of index would

be best for this table? bitmap unique

DM Which of the following statements is true?

A data warehouse is useful to all

organisations that currently use

OLTP's

A data warehouse is valuable

only if the organisation has an

interest in analysing historical

data.


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DM Analytical processing is

the act of using software to

analyse highly consolidated

data, often to view the changes

over time.

the act of exporting data into a

spreadsheet for analysis


The fact table of a data

warehouse is the main store of

descriptions of the transactions

stored in a DWH

The fact table of a data

warehouse is the main store of

all of the recorded transactions

over time.

DM

Which of the following is associated with a

data warehouse A relation A flat file


The more data a data warehouse

has, the better it is

A data warehouse

automatically makes a copy of

every transaction recorded in

an OLTP system

DM A data warehouse

must import data from

transactional systems whenever

significant changes occur in the

transactional data.

takes regular copies of

transaction data

DM Granularity refers to

The number of fact tables in a

data warehouse

The level of detail of the data

descriptions held in a data

warehouse

DM Dimensionality refers to

The level of detail of data that is

held in the fact table

The data that describes the

transactions in the fact table.

DM

The main organisational justification for

implementing a data warehouse is to

provide

lagre scale transaction

processing

Cheaper ways of handling

transactions

OLAP OLTP stands for On Line Transaction Processing On Line Terminal Protocol

DM Data in a data warehouse in a flat file format

must be in normalised form to

at least 3NF

DM A data warehouse needs to be time varient Subject orientated

DM Transaction processing is

the act of processing individual

transactions

the act of analysing each

transaction to verify that it is

valid

OLAP OLAP stands for On Line Analytical Protocol

On Line Abstraction

Processing

DM

What is a formal way to express data

relationships to a database management

system? Attributes Entity identifier

DM

What is a technique for documenting the

relationships between entities in a database

environment? Attributes Entity identifier

DM

What indicates having the potential to

contain more than one value for an attribute

at any given time? Constraint Single-valued

DM

Which relationship is between two entities

in which an instance of entity A can be

related to zero, one, or more instances of

entity B and entity B can be related to zero,

one, or more instances of entity A? One-to-many relationship One-to-one relationship


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DM

Which of the following uses a series of

logically related two-dimensional tables or

files to store information in the form of a

database? Database Database management system

OLAP

All of the following terms describe OLAP,

except

The gathering of input

information Processing input information

DMWhich tool is used to help an organization build and use business intelligence? Data warehouse Data mining tools

DM What does the data dictionary identify? Field names Field types

DM

Which of the following is a data

manipulation tool? File generators Query by example tool

DM

en gat er ng us ness n ormat on

requirements, you should focus only on the

requirements provided by the business

groups. TRUE FALSE

OLAP

One difference between the design of

online transaction processing (OLTP) and

online analytical processing (OLAP)

systems is that the OLTP system design is

optimized for getting data into the database. TRUE FALSE

DM

Designing a data warehouse in first normal

form (1NF) is not recommended. TRUE FALSE

DM

Cardinality is defined as the number of

relationships existing between entities. TRUE FALSE

DM

It is not important to include metadata when

designing a data warehouse. TRUE FALSE

DM

There is no need to include a time

dimension in the data warehouse. TRUE FALSE

DM

The level of granularity you choose for the

time dimension has no significant impact onthe size of your database. TRUE FALSE

DM

Surrogate keys are generated on tables in

the data warehouse after the table is

populated. TRUE FALSE

DM

To improve performance, all tables in the

data warehouse should be indexed. TRUE FALSE

DM

Fact tables are often referred to as the

measures of business performance. TRUE FALSE

DM

Dimension tables are used to provide

descriptions of the business subjects and

descriptive information about each row in

the fact table. TRUE FALSE

DM

A high level of granularity means more

detail; a low level of granularity mean less

detail. TRUE FALSE

DM

One method of managing the history in

dimension tables is to drop the dimension

and rebuild the table from scratch. TRUE FALSE


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DM

You do not need to be concerned with

maintaining the history of changing data in

the dimension tables. TRUE FALSE

DM

Effective use of summaries is the best

technique for improving performance in

data warehouses. TRUE FALSE

DM

Summary data cannot be combined with

detailed fact data. TRUE FALSE

DM

When choosing a level of summarization,

there are two approaches: summarizing the

entire dimension, or summarizing part of

the dimension and partially improving

performance TRUE FALSE

DM

Table partitioning splits the storage of a

table into smaller individual units. TRUE FALSE

DM

Denormalization is the factor that increases

the sparseness in a database. TRUE FALSE

OLAP

What are the actual data values that occupy

the cells as defined by the dimensions

selected? Nesting Aggregation

OLAP

The term that defines filtering data in an

OLAP cube is ___________ . dicing slicing

OLAP

What is an item that matches a specific

description or classification? Category Measure

OLAP

The cube structure in OLAP achieves the

__________ functionality. shared information

OLAP

Aggregation provides OLAP with

__________ multidimensional data pre-calculated data

OLAP What is the acronym that defines OLAP? FHTMI FASMI

OLAP

__________ in OLAP allows you to define

a subcube of the original space. Dicing Slicing

OLAP

What term in OLAP defines changing the

dimensional orientation of the report from

the cube data? Dicing Slicing

OLAP

The _________ in OLAP enable you to

drill-up or drill-down to view different

levels of detail about your data. dimensions measures

OLAP When you nest in OLAP, you _________ .select multiple cubeaggregations select multiple cube measures

ETL Which of the following describes ETL?

A process that transforms

information using a common set

of enterprise definitions

A process that loads

information into a data

warehouse

DM What is data mining

A particular attribute of

information

The common term for the

representation of

multidimensional information


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DM

co ec on o re a e a a e s s ca e a

____. byte record

DM A DBMS is a(n) ____.

interface between the database

and application programs data repository

DM

A(n) ____ is a generalized class of people,

places, or things for which data is collected,

stored, and maintained record entity

DM

Which attribute would make the best

primary key? Social security number Last name

DM

The ____ data model follows a treelike

structure. distributed hierarchical

DM

The most popular database model currently

in use is the ____. relational model hierarchical model

DM

A primary key is a field or set of fields that

uniquely identifies a record. TRUE FALSE

DM

One of the goals of a DBMS is to increase

data redundancy thereby making it less

vulnerable to hackers. TRUE FALSE

DM

A Data Warehouse would most likely be

part of a(n) ERP System Small MIS System

DM Data Mining would most likely be used

to streamline a Transaction

Processing System to model data in a DBMS

DM Which of the following is a valid key field A Book Title House number + Street Name

DM A Table Can only store data of one type Consists of Alphanumeric data

DM

A RDBMS cannot store data without

knowing the data type. Which of the

following statements are true?

A Logical data type can store

three values, TRUE,

UNKNOWN and FALSE

Numerical data can be stored

in different formats

DM

A FLAT FILE database management

system is

A database design that only has

one table in it

A DBMS that can only have

simple data tables in it

DM

Assume you are extending the design of

The College Student Records System to

include details on each classroom. The

college is never likely to have more than ten

classrooms and definitely not ever going to

have more than 25 classrooms. What data

type would you select Numeric - Byte Numeric - Single

OLAP A report must

be exported to a word processor

for printing

be based on an underlying data

source (a table or a query)

OLAP

The layout of a report is independant of the

number of records held in a table or query True FALSE

OLAP A report is used to

produce output that is ready for

e-mailing

produce output that is ready

for publication on the Web

(HTML)

DM

The rule that prohibits transitive

dependencies is third normal form first normal form


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DM

The rule that requires that each non-key

field (attribute) should be fully functionally

dependent on the primary key is Third Normal Form First Normal Form

DM

The rule that specifies that there should be

no repeating fields and that fields should be

atomic is third normal form second normal form

DMThe process of combining two tables in arelational database is known as a Join a Combine

DM The ER model is meant to

enable low level descriptions of

data replace relational design

DM The Entity Relation Model models Entities Relationships

DM

Which of the following statements best

decribes the function of an entity relation

model?

An ER model provides a view

of the logic of the data and not

the physical implementation.

An ER model is concerned

primarily with a physical

implementation of the data and

secondly with the logical view

DM SQL stands for Sequential Question Language Structured Query Language

DM

Which of the following are elements of

SQL? Data Query Language Data Definition Language

DM

Consider the table (STUDREC). Which of

the following statements will list columns

INIT, SNAME, GENDER and KIDS (in

that order) for all students who have more

then 1 child.

SELECT init, sname, gender,

kids FROM studrec WHERE

kids 1;

OLAP A typical data warehouse consists of … Staging area Data Marts

OLAP

What are the three layers of Data

warehouse architecture?

Data staging layer, Data Extract

layer, Data transactional layer

Data Modelling layer, Data

Accesses layer, Data Storage

layer

OLAP Staging Area comes under which layer? Data Storage layer Data Access layer

OLAP

What are Limitations of Traditional

techniques ? Extensive programming Redundant reporting

OLAP Different categories of Data Access are? Web Access Data Mining

OLAP OLAP stands for Online Access Processing Online Analytic Processing

OLAP

A process that uses a variety of statisticaland artificial intelligence frameworks to

discover patterns and relationships in data Data Access Process Data Mining Process

OLAP

A category of data access solutions in

which information is viewed through a web

browser Data Access Process Data Mining Process

OLAP What is importance of Data Access?

Businesses today face

challenges like

Data Access is the ‘last mile’

that enables decision makers to


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OLAP What are different types of reporting? Transaction Systems Reporting

Enterprise Data Warehouse

Reporting

OLAP

In Transaction Systems Reporting,

Reporting Tool has a native connectivity to

? Views Tables

OLAP

An enterprise data warehouse (EDW) is

designed to

To combine data from multiple

OLTP systems

To provide consolidated and

cleansed data to an array of

data marts

OLAP Examples of Managed Query Tool Business Objects MS Query

OLAP Which are the OLAP features ?

Multidimensional viewing

Capabilities

Time Intelligence - Time

Series analysis

OLAP OLAP system is Decision support

Relatively standardized and

simple queries returning

relatively few records

OLAP What is measure? Is not a number represents factual data

OLAP What is ROLAP?

Data is stored in

multidimensional cubes

Support for large databases

with good performance

SQL Which one is DDL command? Insert Update

SQL

How many types of Normalization rules are

there? 4 5

SQL Which are pseudocolumns CURRVAL NEXTVAL

SQL

Can you use select in FROM clause of SQL

select ? YES NO

SQL

Describe the use of %ROWTYPE in

PL/SQL ?

It allows you to associates a

variable with a single column

type

It allows you to associate a

variable with an entire table

row

SQL How many types of triggers are there? 9 10

SQL

What is the default ordering of an ORDER

BY clause in a SELECT statement? Descending Ascending

SQL Union All returns

All rows selected by either

query

All rows selected by either

query and including duplicates

ETL What is ETL process?

ETL is the set of processes by

which data is extracted from

various sources, transformed

and loaded into target systems

ETL is the set of processes by

which data is extracted from

various sources and loaded

into target systems

ETL What is Importance of ETL?

Closely integrated with

RDBMS’s

High speed loading of target

data warehouses

ETL Which are ETL Activities ?

Data Extraction, Data

transformation, Data loading


Extraction – Cleanup, Data

loading

ETL Data Extraction Methods are Incremental Extraction Real Time Extraction

ETL Which are the examples of ETL tools? Informatica PowerCenter Ab Initio

ETL What is Bulk Load?

Format of Archived data

different from operational data

It limits your ability to recover

because no database logging

occurs

ETL Which one is not GUI based Scheduler ? Tool Specific Autosys


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ETLWhat do you mean by Source alterationstage in ETL ?

perform a variety of

transformations unique to the

source, depending on businessrequirements

performs the access and

extraction of data from the

source system and builds a

temporal view of the data atthe time of extraction

ETL

What are the different types of Commit

intervals? Target-based commit Source-based commit

ETL Which is the first step of the ETL process ? Data Extraction – Cleanup Data Extraction

ETL Which is not pros of Batch Extraction ?

Quick and relatively easy to

write scripts for doing exports

and imports

Does not usually require

additional hardware

ETL

Which tool does not support Change-Data-

Capture Feature ? Ascential Data Stage XE Informatica PowerCenter

DW What is Data Warehouse ?

Data Warehouse is integarted of

data in support of management's

decisions

ata ware ouse s a su ect-

oriented, integrated,

nonvolatile, time-variant

collection of data in support of

management's decisions

DW What is the Need of Data Warehousing ? To store Operational Data

Better business intelligence for

end-users

DW

Which one is not Characteristic of Data

Mart ? Restrictive, non extensible Short life/tactical

DW

Which is the information need for recent

data ? ODS OLTP

DW

What type of Data Structure Characteristic

does Data Warehousing has ? Detailed Summarized

DW

What are Components of a Data Warehouse

Architecture ? Data Cleansing tool ETL tool

DW What is use of Data Cleaning Tools ?

Clean up source data in-place

on the host

Generate and maintain

centralized metadata

DW What is the use of Data Mining Tools ? Slice and Dice What If analysis

DM What is Database ?

A known fact that can be

recorded and that have implicit

meaning

The data is perceived by the

user as tables

DM What is Data Model ?

A collection of concepts that

can be used to describe the

structure of a database

Representation of a set of

business requirements in a

standard structured framework

understood by the users

DM

Which Data Modelling approach suit for

corporate data Warehouse ? Dimensional Approach Entity Relational Approach

DM

What are the different types of relationship

notations ? IEX IDFIX

DM What is Physical Data Model ? Conceptual

Geared for performance and

may consists of redundant data

DM What are different types of Data Model ? Physical model, Logical model, Hybrid model


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DM

an we ave mu p e ore gn eys n a

table ? TRUE FALSE


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Option (C) Option (D)

Answer

s

Organized around important

subject areas. Contains only current data. C

One-to-many All of the above B

Completely normalized Partially normalized C

Helper All of the above D

To analyze data for expected

relationships To create a new data warehouse A

A

Long and Fat Short and thin A

Clean and Dirty Data None of above A

Inmon believes that DW is built

and should be used for

reporting.

Ralph Kimball believes that DW

is built and should be used for

reporting. B and D

Type Three None of above B

Does not matter if we use Sorted

or Unsorted data for

Aggregation None of the Above B

First Aggregates then load data

into dimension tables, then fact

tables

Does not matter if we load either

of fact, dimensions, or

aggregates B

None of Above A

Outer Join None of the Above C

None of Above C

All of these None of Above B

Third Step Fourth Step B

mathematically None of these B

partitioned reverse Key C

A data warehouse is valuable to

thiose organisations that need to

keep an audit trail of their

activities

A data warehouse is necessary

to all those organisations that

are using relational OLTP's B


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the act of using a relational

database to produce reports

giving data summaries on a

regular basis (e.g. monthly)

the act of sumarising data on a

regular basis (e.g. month end

summaries) A

A fact table describes the

granularity of data held in a

DWH

A fact table describes the

transactions stored in a DWH BA hierachical and/or network

structure A star schema D

A data warehouse is a relatively

straighttforward thing to set up.

Adding data for the sake of it

may well degrade the

effectiveness of data

warehouseing analysis D

takes regular copies of

transaction data and stores it in a

way that is optimised for query

and reporting

has to work on live transactional

data to provide up to date and

vaild results C

The level of detail of the data

stored in a data warehouse.

The number of dimensions in a

data warehouse C

The level of detail that is held in

the Data Warehouse

The number of dimension tables

that exist in a star schema B

Storing large volumes of data Decision support D

On Line Terminal Processing On Line Transaction Protocol A

can be normalised but often isn't

must be in normalised form to at

least 2NF C

Capable of integrating data from

a wide variety of sources non-volatile A,B,C,D

the act of analysing transactions

on a regular basis (e.g. monthly)

the act of processing, recording

and storing individual

transactions in a database D

On Line Abstraction Protocol On Line Analytical Processing D

Data model Entity-relationship diagram C

Data model Entity-relationship diagram D

All of the above None of the above D

Many-to-many relationship Many-to-one relationship C


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Data warehouse None of the above D

Updating existing information to

reflect to the gathered and

processed information None of the above D

Database management systems All of the above D

Field formats All of the above D

Structure question language All of the above B

B

A

B

A

B

B

B

B

B

A

A

A

B


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B

A

B

A

A

A

Dimensions Measures D

rotating nesting B

Dimension Nest A

collection multidimensional D

nested data slow data retrieval B

ASFMI MASHF B

Rotating Nesting A

Rotating Nesting C

nesting aggregation A

select multiple cube dimensions select multiple cube slices C

A process that extracts

information from internal and

external databases All of the above D

The process of analyzing data to

extract information not offered

by the raw data alone

find patterns and relationships in

large volumes of information

and infer rules from them that

predict future behavior and

guide decision making C


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character bit B

knowledge base unique group of records A

attribute file B

First name Age A

network relational B

network model object model A

A

B

DBMS Expert system A

to help transform data into

useful information that can be

used by a DSS

to e p trans orm ata rom

different sources so that they

can be stored in a single Data

Warehouse. C

Car Registration number

Initials + Family Name + Date

of Birth C

Consists of Rows and Columns Cannot be empty B

Some DBMS's can use DATE

data types

A Character (Text) data type can

contain 0,1,2,3,4,5,6,7,8 and 9B,C,D

A DBMS that can only have one

table in it

A DBMS that contains records

that have a large number of

fields in them C

Numeric - Integer Numeric - Long integer A

Be redefined each time it is used be password protected B

A

produce output that is formatted

for display on a computer screen

produce output formatted for

print D

second normal form None of the Above A


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Second Normal Form None of the Above C

first normal form None of the Above C

a Relate a Construc A

be close to a users perception of

the data

enable detailed descriptions of

data query processing C

Entities, Relationships and

Processes Entities and Relationships D

An ER model is entirely

concerned with modelling the

physical implemetation

An ER model is concerned

primarily with a logical view of

the data and secondly with the

physical implementation A

Structured Question Language Sequential Query Language B

Data Modification Language Data Manipulation Language A,B,D

SELECT init, sname, gender,


kids >'1';

SELECT init sname, gender,


kids >1; D

Analytical environment All of the above A

Data Extraction layer, Data

Accesses layer, Data Storage

layer None C

Data Extract layer None D

oes not ave a natura way

of providing flexible view

reorganizations that will

transpose the data All of the above D

Both A and B None C

Both A and B None B

Web Access Process None B

Web Access Process Reporting C

Prompt, reliable data access All of the above D


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Both A and B None C

OLAP OLTP D

Both A and B None C

Microsoft Access All of the above A

Only A Both A and B D

Both A and B None A

description of subject Both B and C B

Good to access pre-aggregated

data

Compilation intensive

architecture B

Drop Select C

6 7 B

ROWID All of the above D

A

It allows you to associate a

variable with an entire table

column Both A and C B

11 12 D

B

All distinct rows selected by

both queries

All rows selected by the first

query but not the seconds B

Both A and B None A

Both A and B Only A C

Data Extraction, Data loading


transformation, Data Extraction

– Cleanup, Data loading D

Full Extraction All of the above D

Business Objects Both A and B D

Lengthy and Complex process All of the above B

CRON jobs All of the above C


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performs final formatting of data

to produce load-ready files for

the target table; identifies and

segregates rows to be inserted

vs. updated (if applicable);

applies remaining technical meta

data tagging; and processes datainto the RDBMS

final stage, uses the load- ready

files from Stage 4 to build

aggregation tables needed to

improve query performanceagainst the warehouse A

Only A Both A and B D

Data transformation Data loading B

Not event driven--does not

facilitate notification or change

in another application at the time

of a change in first application

Almost all applications provide

utilities for exporting and

importing C

Ab Initio All of the above B

Both A and B None B

Used by Operational users Both B and C B

Project Orientation Flexible, extensible D

OLAP All of the above A

Detailed and Summarized Detailed and lightly summarized C

Data Modelling tool All of the above D

Automatic generation of data

extract programs All of the above A

Dill Down Static Reports B

It is designed, built, and

populated with data for a

specific purpose All of the above C

Both A and B None A

Both A and B None B

IE Both B and C C

Both A and B None B

Conceptual model Both A and C D


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A


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Standard SRMU