Topic Questions Option (A) Option (B)

DM Can be updated by end users

DM Many-to-many One-to-one

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

DM Fact Dimension

DM To confirm that data exists

DM 1 0

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

DM Type One Type Two

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

DM

DM Snowflaking means Normalizing the data Denormalizing the data

OLAP 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 First Step Second Step

DM Dimensions are Confirmed when They are different

DM bitmap unique

A data warehouse is which of the following?

Contains numerous naming conventions and formats.

A star schema has what type of relationship between a dimension and fact table?

A snowflake schema is which of the following types of tables?

A goal of data mining includes which of the following?

To explain some observed event or condition

OLAP databases are called decision support system ?

Ralph Kimball believes that portions of data can be combined based on relevance of data and can be used for reporting

Inmon believes that portions of data can be combined based on relevance of data and can be used for reporting

In which type of SCD(Slowly changing dimensions) do we preserve history of data:

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

Drill Across generally use the following join to generate report

In 4 step dimensional process, declaring gain of business process is

They are either same or one is subset of another

You need to create an index on the SALES table, which is 10 GB in size. You want your 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?

DM Which of the following statements is true?

DM Analytical processing is

DM Which of the following statements is true?

DM A relation A flat file

DM Which of the following statements is true?

DM A data warehouse

DM Granularity refers to

DM Dimensionality refers to

DM

OLAP OLTP stands for On Line Terminal Protocol

DM Data in a data warehouse in a flat file format

DM A data warehouse needs to be time varient Subject orientated

DM Transaction processing is

OLAP OLAP stands for On Line Analytical Protocol

DM Attributes Entity identifier

DM Attributes Entity identifier

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.

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.

Which of the following is associated with a data warehouse

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

must import data from transactional systems whenever significant changes occur in the transactional data.

takes regular copies of transaction data

The number of fact tables in a data warehouse

The level of detail of the data descriptions held in a data warehouse

The level of detail of data that is held in the fact table

The data that describes the transactions in the fact table.

The main organisational justification for implementing a data warehouse is to provide

lagre scale transaction processing

Cheaper ways of handling transactions

On Line Transaction Processing

must be in normalised form to at least 3NF

the act of processing individual transactions

the act of analysing each transaction to verify that it is valid

On Line Abstraction Processing

What is a formal way to express data relationships to a database management system?

What is a technique for documenting the relationships between entities in a database environment?

DM Constraint Single-valued

DM One-to-many relationship One-to-one relationship

DM Database Database management system

OLAP Processing input information

DM Data warehouse Data mining tools

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

DM File generators Query by example tool

DM 1 0

OLAP 1 0

DM 1 0

DM 1 0

DM 1 0

DM 1 0

DM 1 0

DM 1 0

DM 1 0

DM 1 0

What indicates having the potential to contain more than one value for an attribute at any given time?

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?

Which of the following uses a series of logically related two-dimensional tables or files to store information in the form of a database?

All of the following terms describe OLAP, except

The gathering of input information

Which tool is used to help an organization build and use business intelligence?

Which of the following is a data manipulation tool?

When gathering business information requirements, you should focus only on the requirements provided by the business groups.

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.

Designing a data warehouse in first normal form (1NF) is not recommended.

Cardinality is defined as the number of relationships existing between entities.

It is not important to include metadata when designing a data warehouse.

There is no need to include a time dimension in the data warehouse.

The level of granularity you choose for the time dimension has no significant impact on the size of your database.

Surrogate keys are generated on tables in the data warehouse after the table is populated.

To improve performance, all tables in the data warehouse should be indexed.

Fact tables are often referred to as the measures of business performance.

DM 1 0

DM 1 0

DM 1 0

DM 1 0

DM 1 0

DM 1 0

DM 1 0

DM 1 0

DM 1 0

OLAP Nesting Aggregation

OLAP dicing slicing

OLAP Category Measure

OLAP shared information

OLAP multidimensional data pre-calculated data

OLAP What is the acronym that defines OLAP? FHTMI FASMI

OLAP Dicing Slicing

OLAP Dicing Slicing

Dimension tables are used to provide descriptions of the business subjects and descriptive information about each row in the fact table.

A high level of granularity means more detail; a low level of granularity mean less detail.

One method of managing the history in dimension tables is to drop the dimension and rebuild the table from scratch.

You do not need to be concerned with maintaining the history of changing data in the dimension tables.

Effective use of summaries is the best technique for improving performance in data warehouses.

Summary data cannot be combined with detailed fact data.

When choosing a level of summarization, there are two approaches: summarizing the entire dimension, or summarizing part of the dimension and partially improving performance

Table partitioning splits the storage of a table into smaller individual units.

Denormalization is the factor that increases the sparseness in a database.

What are the actual data values that occupy the cells as defined by the dimensions selected?

The term that defines filtering data in an OLAP cube is ___________ .

What is an item that matches a specific description or classification?

The cube structure in OLAP achieves the __________ functionality.

Aggregation provides OLAP with __________

__________ in OLAP allows you to define a subcube of the original space.

What term in OLAP defines changing the dimensional orientation of the report from the cube data?

OLAP dimensions measures

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

ETL Which of the following describes ETL?

DM What is data mining

DM byte record

DM A DBMS is a(n) ____. data repository

DM record entity

DM Social security number Last name

DM distributed hierarchical

DM relational model hierarchical model

DM 1 0

DM 1 0

DM ERP System Small MIS System

DM Data Mining would most likely be used 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

DM

DM

The _________ in OLAP enable you to drill-up or drill-down to view different levels of detail about your data.

select multiple cube aggregations

A process that transforms information using a common set of enterprise definitions

A process that loads information into a data warehouse

A particular attribute of information

The common term for the representation of multidimensional information

A collection of related data fields is called a ____.

interface between the database and application programs

A(n) ____ is a generalized class of people, places, or things for which data is collected, stored, and maintained

Which attribute would make the best primary key?

The ____ data model follows a treelike structure.

The most popular database model currently in use is the ____.

A primary key is a field or set of fields that uniquely identifies a record.

One of the goals of a DBMS is to increase data redundancy thereby making it less vulnerable to hackers.

A Data Warehouse would most likely be part of a(n)

to streamline a Transaction Processing System

Consists of Alphanumeric data

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

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 Numeric - Byte Numeric - Single

OLAP A report must

OLAP True 0

OLAP A report is used to

DM third normal form first normal form

DM Third Normal Form First Normal Form

DM third normal form second normal form

DM a Join a Combine

DM The ER model is meant to replace relational design

DM The Entity Relation Model models Entities Relationships

DM

DM SQL stands for Sequential Question Language Structured Query Language

DM Data Query Language Data Definition Language

DM

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

OLAP

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

be exported to a word processor for printing

be based on an underlying data source (a table or a query)

The layout of a report is independant of the number of records held in a table or query

produce output that is ready for e-mailing

produce output that is ready for publication on the Web (HTML)

The rule that prohibits transitive dependencies is

The rule that requires that each non-key field (attribute) should be fully functionally dependent on the primary key is

The rule that specifies that there should be no repeating fields and that fields should be atomic is

The process of combining two tables in a relational database is known as

enable low level descriptions of data

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

Which of the following are elements of SQL?

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;

SELECT init, sname, gender, kids FROM studrec WHERE kids >1;

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 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 Data Access Process Data Mining Process

OLAP Data Access Process Data Mining Process

OLAP What is importance of Data Access?

OLAP What are different types of reporting? Transaction Systems Reporting

OLAP Views Tables

OLAP

OLAP Examples of Managed Query Tool Business Objects MS Query

OLAP Which are the OLAP features ?

OLAP OLAP system is Decision support

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

OLAP What is ROLAP?

SQL Which one is DDL command? Insert Update

SQL 4 5

SQL Which are pseudocolumns CURRVAL NEXTVAL

SQL YES NO

SQL

SQL How many types of triggers are there? 9 10

SQL Descending Ascending

SQL Union All returns

What are Limitations of Traditional techniques ?

A process that uses a variety of statistical and artificial intelligence frameworks to discover patterns and relationships in data

A category of data access solutions in which information is viewed through a web browser

Businesses today face challenges like

Data Access is the ‘last mile’ that enables decision makers to

Enterprise Data Warehouse Reporting

In Transaction Systems Reporting, Reporting Tool has a native connectivity to ?

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

Multidimensional viewing Capabilities

Time Intelligence - Time Series analysis

Relatively standardized and simple queries returning relatively few records

Data is stored in multidimensional cubes

Support for large databases with good performance

How many types of Normalization rules are there?

Can you use select in FROM clause of SQL select ?

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

What is the default ordering of an ORDER BY clause in a SELECT statement?

All rows selected by either query

All rows selected by either query and including duplicates

ETL What is ETL process?

ETL What is Importance of ETL?

ETL Which are ETL Activities ?

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?

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

ETL

ETL 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 ?

ETL Ascential Data Stage XE Informatica PowerCenter

DW What is Data Warehouse ?

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

DW Restrictive, non extensible Short life/tactical

DW ODS OLTP

DW Detailed Summarized

DW Data Cleansing tool ETL tool

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

Closely integrated with RDBMS’s

High speed loading of target data warehouses

Data Extraction, Data transformation, Data loading

Data Extraction, Data Extraction – Cleanup, Data loading

Format of Archived data different from operational data

It limits your ability to recover because no database logging occurs

What do you mean by Source alteration stage in ETL ?

perform a variety of transformations unique to the source, depending on business requirements

performs the access and extraction of data from the source system and builds a temporal view of the data at the time of extraction

What are the different types of Commit intervals?

Quick and relatively easy to write scripts for doing exports and imports

Does not usually require additional hardware

Which tool does not support Change-Data-Capture Feature ?

Data Warehouse is integarted of data in support of management's decisions

A data warehouse is a subject-oriented, integrated, nonvolatile, time-variant collection of data in support of management's decisions

Better business intelligence for end-users

Which one is not Characteristic of Data Mart ?

Which is the information need for recent data ?

What type of Data Structure Characteristic does Data Warehousing has ?

What are Components of a Data Warehouse Architecture ?

DW What is use of Data Cleaning Tools ?

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

DM What is Database ?

DM What is Data Model ?

DM Dimensional Approach Entity Relational Approach

DM IEX IDFIX

DM What is Physical Data Model ? Conceptual

DM What are different types of Data Model ? Hybrid model

DM 1 0

Clean up source data in-place on the host

Generate and maintain centralized metadata

A known fact that can be recorded and that have implicit meaning

The data is perceived by the user as tables

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

Which Data Modelling approach suit for corporate data Warehouse ?

What are the different types of relationship notations ?

Geared for performance and may consists of redundant data

Physical model, Logical model,

Can we have multiple foreign keys in a table ?

Option (C) Option (D)

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 create a new data warehouse A

A

Long and Fat Short and thin A

Clean and Dirty Data None of above A

B and D

Type Three None of above B

None of the Above B

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

None of these B

partitioned reverse Key C

Answers

Organized around important subject areas.

To analyze data for expected relationships

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.

Does not matter if we use Sorted or Unsorted data for Aggregation

First Aggregates then load data into dimension tables, then fact tables

Does not matter if we load either of fact, dimensions, or aggregates

When they can be compared mathematically

B

A

B

A star schema D

D

C

C

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 C

non-volatile A,B,C,D

D

On Line Abstraction Protocol On Line Analytical Processing D

Data model Entity-relationship diagram C

Data model Entity-relationship diagram D

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

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 fact table describes the granularity of data held in a DWH

A fact table describes the transactions stored in a DWH

A hierachical and/or network structure

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

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

The level of detail of the data stored in a data warehouse.

The number of dimensions in a data warehouse

The level of detail that is held in the Data Warehouse

The number of dimension tables that exist in a star schema

must be in normalised form to at least 2NF

Capable of integrating data from a wide variety of sources

the act of analysing transactions on a regular basis (e.g. monthly)

the act of processing, recording and storing individual transactions in a database

All of the above None of the above D

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

Data warehouse None of the above D

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

Updating existing information to reflect to the gathered and processed information

A

A

B

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

All of the above D

C

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

C

Car Registration number C

Consists of Rows and Columns Cannot be empty B

B,C,D

C

A process that extracts information from internal and external databases

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

Uses a variety of techniques to find patterns and relationships in large volumes of information and infer rules from them that predict future behavior and guide decision making

to help transform data into useful information that can be used by a DSS

to help transform data from different sources so that they can be stored in a single Data Warehouse.

Initials + Family Name + Date of Birth

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 9

A DBMS that can only have one table in it

A DBMS that contains records that have a large number of fields in them

Numeric - Integer Numeric - Long integer A

be password protected B

A

D

second normal form None of the Above A

Second Normal Form None of the Above C

first normal form None of the Above C

a Relate a Construc A

C

Entities and Relationships D

A

Structured Question Language Sequential Query Language B

Data Modification Language Data Manipulation Language A,B,D

D

Analytical environment All of the above A

None C

Be redefined each time it is used

produce output that is formatted for display on a computer screen

produce output formatted for print

be close to a users perception of the data

enable detailed descriptions of data query processing

Entities, Relationships and Processes

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

SELECT init, sname, gender, kids FROM studrec WHERE kids >'1';

SELECT init sname, gender, kids FROM studrec WHERE kids >1;

Data Extraction layer, Data Accesses layer, Data Storage layer

Data Extract layer None D

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

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

B

Drop Select C

6 7 B

ROWID All of the above D

A

Both A and C B

11 12 D

B

B

SQL does not have a natural way of providing flexible view reorganizations that will transpose the data

Good to access pre-aggregated data

Compilation intensive architecture

It allows you to associate a variable with an entire table column

All distinct rows selected by both queries

All rows selected by the first query but not the seconds

Both A and B None A

Both A and B Only A C

Data Extraction, 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

A

Only A Both A and B D

Data transformation Data loading B

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 C

Data Modelling tool All of the above D

Data Extraction, Data transformation, Data Extraction – Cleanup, Data loading

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 data into the RDBMS

final stage, uses the load- ready files from Stage 4 to build aggregation tables needed to improve query performance against the warehouse

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

Detailed and lightly summarized

All of the above A

Dill Down Static Reports B

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

A

Automatic generation of data extract programs

It is designed, built, and populated with data for a specific purpose