Topic Questions Option (A) Option (B) A data warehouse is which of the Contains numerous naming DM following? Can be updated by end users conventions and formats. A star schema has what type of relationship DM between a dimension and fact table? Many-to-many One-to-one DM Fact tables are which of the following? Completely demoralized Partially demoralized A snowflake schema is which of the DM following types of tables? Fact Dimension A goal of data mining includes which of the To explain some observed event DM following? or condition To confirm that data exists OLAP databases are called decision support DM 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 Ralph Kimball believes that portions of data can be Inmon believes that portions of combined based on relevance of data can be combined based on data and can be used for relevance of data and can be DM Choose two reporting used for reporting In which type of SCD(Slowly changing DM 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 First load data into fact tables First load data into dimension Sequence of jobs to load data in to then dimension tables, then tables, then fact tables, then DM warehouse Aggregates if any Aggregates if any DM Snowflaking means Normalizing the data Denormalizing the data Drill Across generally use the following OLAP 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 In 4 step dimensional process, declaring DM gain of business process is First Step Second They areStep either same or one is DM Dimensions are Confirmed when They are different 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 DM be best for this table? bitmap unique A data warehouse is valuable A data warehouse is useful to all only if the organisation has an organisations that currently use interest in analysing historical DM Which of the following statements is true? OLTP's data. the act of using software to analyse highly consolidated data, often to view the changes the act of exporting data into a DM Analytical processing is over time. spreadsheet for analysis The fact table of a data The fact table of a data warehouse is the main store of warehouse is the main store of descriptions of the transactions all of the recorded transactions DM Which of the following statements is true? stored in a DWH over time. Which of the following is associated with a DM data warehouse A relation A flat file A data warehouse automatically makes a copy of The more data a data warehouse every transaction recorded in DM Which of the following statements is true? has, the better it is an OLTP system must import data from transactional systems whenever significant changes occur in the takes regular copies of DM A data warehouse transactional data. transaction data The level of detail of the data The number of fact tables in a descriptions held in a data DM Granularity refers to data warehouse warehouse The level of detail of data that is The data that describes the DM Dimensionality refers to held in the fact table transactions in the fact table. The main organisational justification for implementing a data warehouse is to lagre scale transaction Cheaper ways of handling DM provide processing transactions OLAP OLTP stands for On Line Transaction Processing On Line Terminal Protocol must be in normalised form to DM Data in a data warehouse in a flat file format at least 3NF DM A data warehouse needs to be time varient Subject orientated the act of analysing each the act of processing individual transaction to verify that it is DM Transaction processing is transactions valid On Line Abstraction OLAP OLAP stands for On Line Analytical Protocol Processing What is a formal way to express data relationships to a database management DM system? Attributes Entity identifier What is a technique for documenting the relationships between entities in a database DM environment? Attributes Entity identifier What indicates having the potential to contain more than one value for an attribute DM at any given time? Constraint Single-valued 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, DM one, or more instances of entity A? One-to-many relationship One-to-one relationship a low level of granularity mean less DM detail. all tables in the DM data warehouse should be indexed. TRUE FALSE Fact tables are often referred to as the DM measures of business performance. TRUE FALSE The level of granularity you choose for the time dimension has no significant impact on DM the size of your database. TRUE FALSE There is no need to include a time DM dimension in the data warehouse. TRUE FALSE One difference between the design of online transaction processing (OLTP) and online analytical processing (OLAP) systems is that the OLTP system design is OLAP optimized for getting data into the database. The gathering of input OLAP except information Processing input information Which tool is used to help an organization DM build and use business intelligence? Data warehouse Data mining tools DM What does the data dictionary identify? Field names Field types Which of the following is a data DM manipulation tool? File generators Query by example tool When gathering business information requirements. TRUE FALSE Surrogate keys are generated on tables in the data warehouse after the table is DM populated. TRUE FALSE . TRUE FALSE One method of managing the history in dimension tables is to drop the dimension DM and rebuild the table from scratch. TRUE FALSE Cardinality is defined as the number of DM relationships existing between entities. TRUE FALSE It is not important to include metadata when DM designing a data warehouse. you should focus only on the requirements provided by the business DM groups. Which of the following uses a series of logically related two-dimensional tables or files to store information in the form of a DM database? Database Database management system All of the following terms describe OLAP. TRUE FALSE A high level of granularity means more detail. TRUE FALSE To improve performance. TRUE FALSE Designing a data warehouse in first normal DM form (1NF) is not recommended. TRUE FALSE Dimension tables are used to provide descriptions of the business subjects and descriptive information about each row in DM the fact table. shared information Aggregation provides OLAP with OLAP __________ multidimensional data pre-calculated data OLAP What is the acronym that defines OLAP? FHTMI FASMI __________ in OLAP allows you to define OLAP a subcube of the original space. dimensions measures select multiple cube OLAP When you nest in OLAP. TRUE FALSE Summary data cannot be combined with DM detailed fact data. TRUE FALSE Denormalization is the factor that increases DM the sparseness in a database. you _________ . Dicing Slicing What term in OLAP defines changing the dimensional orientation of the report from OLAP the cube data? Dicing Slicing The _________ in OLAP enable you to drill-up or drill-down to view different OLAP levels of detail about your data. TRUE FALSE When choosing a level of summarization. aggregations select multiple cube measures A process that transforms A process that loads information using a common set information into a data ETL Which of the following describes ETL? of enterprise definitions warehouse The common term for the A particular attribute of representation of DM What is data mining information multidimensional information . You do not need to be concerned with maintaining the history of changing data in DM the dimension tables. or summarizing part of the dimension and partially improving DM performance TRUE FALSE Table partitioning splits the storage of a DM table into smaller individual units. there are two approaches: summarizing the entire dimension. dicing slicing What is an item that matches a specific OLAP description or classification? Category Measure The cube structure in OLAP achieves the OLAP __________ functionality. TRUE FALSE Effective use of summaries is the best technique for improving performance in DM data warehouses. TRUE FALSE What are the actual data values that occupy the cells as defined by the dimensions OLAP selected? Nesting Aggregation The term that defines filtering data in an OLAP OLAP cube is ___________ . TRUE FALSE One of the goals of a DBMS is to increase data redundancy thereby making it less DM vulnerable to hackers. and application programs data repository A(n) ____ is a generalized class of people. relational model hierarchical model A primary key is a field or set of fields that DM uniquely identifies a record. A collection of related data fields is called a DM ____. byte record interface between the database DM A DBMS is a(n) ____. Which of the three values. distributed hierarchical The most popular database model currently DM in use is the ____. or things for which data is collected.Byte Numeric . What data DM type would you select Numeric . TRUE FALSE A Data Warehouse would most likely be DM part of a(n) ERP System Small MIS System to streamline a Transaction DM Data Mining would most likely be used 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 A RDBMS cannot store data without A Logical data type can store knowing the data type. places. TRUE. Numerical data can be stored DM following statements are true? UNKNOWN and FALSE in different formats A FLAT FILE database management A database design that only has A DBMS that can only have DM system is one table in it simple data tables in it Assume you are extending the design of The College Student Records System to include details on each classroom. DM stored. and maintained record entity Which attribute would make the best DM primary key? Social security number Last name The ____ data model follows a treelike DM structure. The college is never likely to have more than ten classrooms and definitely not ever going to have more than 25 classrooms.Single be exported to a word processor be based on an underlying data OLAP A report must for printing source (a table or a query) The layout of a report is independant of the OLAP number of records held in a table or query True FALSE produce output that is ready produce output that is ready for for publication on the Web OLAP A report is used to e-mailing (HTML) The rule that prohibits transitive DM dependencies is third normal form first normal form . Data transactional layer layer OLAP Staging Area comes under which layer? Data Storage layer Data Access layer What are Limitations of Traditional OLAP 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 A process that uses a variety of statistical and artificial intelligence frameworks to OLAP discover patterns and relationships in data Data Access Process Data Mining Process A category of data access solutions in which information is viewed through a web OLAP browser Data Access Process Data Mining Process Businesses today face Data Access is the ‘last mile’ OLAP What is importance of Data Access? challenges like that enables decision makers to . sname. kids >1. Data What are the three layers of Data Data staging layer. gender. The rule that requires that each non-key field (attribute) should be fully functionally DM dependent on the primary key is Third Normal Form First Normal Form The rule that specifies that there should be no repeating fields and that fields should be DM atomic is third normal form second normal form The process of combining two tables in a DM relational database is known as a Join a Combine enable low level descriptions of DM The ER model is meant to data replace relational design DM The Entity Relation Model models Entities Relationships An ER model is concerned Which of the following statements best An ER model provides a view primarily with a physical decribes the function of an entity relation of the logic of the data and not implementation of the data and DM model? the physical implementation. OLAP A typical data warehouse consists of … Staging area Data Marts Data Modelling layer. that order) for all students who have more kids FROM studrec WHERE kids FROM studrec WHERE DM then 1 child. SNAME. gender. sname. Data Storage OLAP warehouse architecture? layer. SELECT init. kids <1. GENDER and KIDS (in SELECT init. Which of the following statements will list columns INIT. secondly with the logical view DM SQL stands for Sequential Question Language Structured Query Language Which of the following are elements of DM SQL? Data Query Language Data Definition Language Consider the table (STUDREC). Data Extract Accesses layer. Enterprise Data Warehouse OLAP What are different types of reporting? Transaction Systems Reporting Reporting In Transaction Systems Reporting. Reporting Tool has a native connectivity to OLAP ? Views Tables To provide consolidated and An enterprise data warehouse (EDW) is To combine data from multiple cleansed data to an array of OLAP designed to OLTP systems data marts OLAP Examples of Managed Query Tool Business Objects MS Query Multidimensional viewing Time Intelligence . Data Extraction – Cleanup. Data ETL Which are ETL Activities ? transformation.Time OLAP Which are the OLAP features ? Capabilities Series analysis Relatively standardized and simple queries returning OLAP OLAP system is Decision support relatively few records OLAP What is measure? Is not a number represents factual data Data is stored in Support for large databases OLAP What is ROLAP? multidimensional cubes with good performance SQL Which one is DDL command? Insert Update How many types of Normalization rules are SQL there? 4 5 SQL Which are pseudocolumns CURRVAL NEXTVAL Can you use select in FROM clause of SQL SQL select ? YES NO It allows you to associates a It allows you to associate a Describe the use of %ROWTYPE in variable with a single column variable with an entire table SQL PL/SQL ? type row SQL How many types of triggers are there? 9 10 What is the default ordering of an ORDER SQL BY clause in a SELECT statement? Descending Ascending All rows selected by either All rows selected by either SQL Union All returns query query and including duplicates ETL is the set of processes by ETL is the set of processes by which data is extracted from which data is extracted from various sources. Data Data Extraction. Data loading loading ETL Data Extraction Methods are Incremental Extraction Real Time Extraction ETL Which are the examples of ETL tools? Informatica PowerCenter Ab Initio It limits your ability to recover Format of Archived data because no database logging ETL What is Bulk Load? different from operational data occurs ETL Which one is not GUI based Scheduler ? Tool Specific Autosys . transformed various sources and loaded ETL What is ETL process? and loaded into target systems into target systems Closely integrated with High speed loading of target ETL What is Importance of ETL? RDBMS’s data warehouses Data Extraction. performs the access and perform a variety of extraction of data from the transformations unique to the source system and builds a What do you mean by Source alteration source. Data Warehouse is integarted of nonvolatile. time-variant data in support of management's collection of data in support of DW What is Data Warehouse ? decisions management's decisions Better business intelligence for DW What is the Need of Data Warehousing ? To store Operational Data end-users Which one is not Characteristic of Data DW Mart ? Restrictive. Logical model. Hybrid model . depending on business temporal view of the data at ETL stage in ETL ? requirements the time of extraction What are the different types of Commit ETL intervals? Target-based commit Source-based commit ETL Which is the first step of the ETL process ? Data Extraction – Cleanup Data Extraction Quick and relatively easy to write scripts for doing exports Does not usually require ETL Which is not pros of Batch Extraction ? and imports additional hardware Which tool does not support Change-Data- ETL Capture Feature ? Ascential Data Stage XE Informatica PowerCenter A data warehouse is a subject- oriented. integrated. non extensible Short life/tactical Which is the information need for recent DW data ? ODS OLTP What type of Data Structure Characteristic DW does Data Warehousing has ? Detailed Summarized What are Components of a Data Warehouse DW Architecture ? Data Cleansing tool ETL tool Clean up source data in-place Generate and maintain DW What is use of Data Cleaning Tools ? on the host centralized metadata DW What is the use of Data Mining Tools ? Slice and Dice What If analysis A known fact that can be recorded and that have implicit The data is perceived by the DM What is Database ? meaning user as tables A collection of concepts that Representation of a set of can be used to describe the business requirements in a structure of a database standard structured framework DM What is Data Model ? understood by the users Which Data Modelling approach suit for DM corporate data Warehouse ? Dimensional Approach Entity Relational Approach What are the different types of relationship DM notations ? IEX IDFIX Geared for performance and DM What is Physical Data Model ? Conceptual may consists of redundant data DM What are different types of Data Model ? Physical model. Can we have multiple foreign keys in a DM table ? TRUE FALSE . 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 Does not matter if we load either into dimension tables. reporting. then fact of fact. dimensions. or tables 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 When Step they can be compared Fourth Step B mathematically None of these B partitioned reverse Key C A data warehouse is valuable to thiose organisations that need to A data warehouse is necessary keep an audit trail of their to all those organisations that activities are using relational OLTP's B . Answer Option (C) Option (D) 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 Ralph Kimball believes that DW and should be used for is built and should be used for reporting. g.B. recording the act of analysing transactions and storing individual on a regular basis (e. warehouseing analysis D takes regular copies of transaction data and stores it in a has to work on live transactional way that is optimised for query data to provide up to date and and reporting vaild results C The level of detail of the data The number of dimensions in a stored in a data warehouse. monthly) summaries) A A fact table describes the granularity of data held in a A fact table describes the DWH transactions stored in a DWH B A hierachical and/or network structure A star schema D Adding data for the sake of it may well degrade the A data warehouse is a relatively effectiveness of data straighttforward thing to set up.the act of using a relational database to produce reports the act of sumarising data on a giving data summaries on a regular basis (e.g. month end regular basis (e. monthly) 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 .g.D the act of processing. data warehouse C The level of detail that is held in The number of dimension tables the Data Warehouse that exist in a star schema B Storing large volumes of data Decision support D On Line Terminal Processing On Line Transaction Protocol A must be in normalised form to at can be normalised but often isn't least 2NF C Capable of integrating data from a wide variety of sources non-volatile A.C. 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 . 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 Usesofathe above variety of techniques to D find patterns and relationships in large volumes of information The process of analyzing data to and infer rules from them that extract information not offered predict future behavior and by the raw data alone guide decision making C . 6.7.D A DBMS that contains records A DBMS that can only have one that have a large number of table in it fields in them C Numeric . C Initials + Family Name + Date Car Registration number of Birth C Consists of Rows and Columns Cannot be empty B Some DBMS's can use DATE A Character (Text) data type can data types contain 0.Integer Numeric .8 and 9 B.2.3.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 from to help transform data into different sources so that they useful information that can be can be stored in a single Data used by a DSS Warehouse.1.4.5.C.Long integer A Be redefined each time it is used be password protected B A produce output that is formatted produce output formatted for for display on a computer screen print D second normal form None of the Above A . B. gender. gender. Relationships and Processes Entities and Relationships D An ER model is concerned An ER model is entirely primarily with a logical view of concerned with modelling the the data and secondly with the physical implemetation physical implementation A Structured Question Language Sequential Query Language B Data Modification Language Data Manipulation Language A.D SELECT init. sname. Data Accesses layer. kids >1. D Analytical environment All of the above A Data Extraction layer. SELECT init sname. kids FROM studrec WHERE kids FROM studrec WHERE kids >'1'. Data Storage layer None C Data Extract layer None D SQL does not have a natural 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 .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 enable detailed descriptions of the data data query processing C Entities. Data loading – Cleanup.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 Compilation intensive data 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 All rows selected by the first both queries query but not the seconds B 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 . Data transformation. Data Extraction Data Extraction. built.performs final formatting of data to produce load-ready files for the target table. 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 . updated (if applicable). identifies and segregates rows to be inserted final stage. files from Stage 4 to build applies remaining technical meta aggregation tables needed to data tagging. and processes data improve query performance into the RDBMS against the warehouse A Only A Both A and B D Data transformation Data loading B Not event driven--does not facilitate notification or change Almost all applications provide in another application at the time utilities for exporting and of a change in first application 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.ready vs. 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. uses the load. A .