Date post: | 07-Feb-2016 |
Category: |
Documents |
Upload: | urs-gopinath |
View: | 173 times |
Download: | 4 times |
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