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PART I:(Marks 2 points each) Which of the following are un answered questions of ER modeling (2)Which table is importantRelationships between the tablesWhich table contain numeric dataAll of aboveWhich of the following are features of Dimensional ModelingSingle path between any two tablesAll relationships are 1:MSupports OLAP operationsKeys are usually system generatedAll of the aboveDimension tables are:NarrowFrequently changingLarge is sizewideNone of the aboveKimball’s data warehouse implementation approach consists of:Data TrackApplication TrackTechnology TrackAll of the aboveStar Schema results in:Simplified physical modelFewer tablesFewer joins resulting in higher performanceNeed for additionalspaceAll of the aboveWhich of the following is an atomic grainIndividual transactionDaily aggregatesMonthly aggregatedSnapshotsNone of the aboveWhich of the following is an example of grainEntry from cache registerBoarding pass to get on a flightSensor reading per minute for a sensorStudent enrolled in a courseAllof the aboveWhich statement is true for aggregationHides crucial factsDoes not work for repetitive queriesCan create weekly sales data from monthly salesA microscopic view of dataAll of the aboveWhich of the following is not a dimension. (2)ProductQuantity soldTimeAccount numberThe characteristics of data warehouse are:Idealenvironment for data analysisFluid, flexible and interactive100 % user drivenProvides the ability to discover complex, unpredictable questionsAll of the aboveData for Data warehouse can come from following resources:Production OLTP System Archived DataExternal dataApplication DataAll of the aboveWhat of following applies to fact tableContains foreign keys of dimension tablesA table without a numeric columnContains descriptive columnsAll of the aboveWhich of the following is not part of dimensional modelingSelection of software to useIdentify processDetermine grainIdentify numeric valuesNone of the aboveThe part of a type 1 Slowly changing dimension isCode of a city entered incorrectPayment MethodNo changes needed elsewhere in dimensionDimension referenced many times in fact tableAll of the aboveThe part of a Role playing dimension areCode of a city entered incorrectPayment MethodNo changes needed elsewhere in dimensionDimension referenced many times in fact tableAll of the above Metadata is:Catalog of dataData warehouse directoryData warehouse atlasTongs to handle dataAll of the aboveMetadata answers which of the following questions: (2)Which subject areas are most important for analysisThe purpose of the business unitHow old is data in warehouseHow can I browse and see what is availableAll of the aboveRequirement analysis document should includePurpose of data warehouseEnd user applications and how they analyze dataLocation of data sources and data structures usedBus MatrixAll of the aboveReasons of moving to data warehouse isProcessing huge amount of dataProviding interactive analysisLower costNone of the aboveAll of the aboveCharacteristics of a data warehouse include (2)Stores only current dataFacilitates analysis of large volumes of dataData extracted from a single sourceContains read intensive dataAll of the aboveIn data Warehouse data will be collected in terms of DimensionsHierarchiesFactsAll of the aboveThe numbers that users analyze are calledDimensionsHierarchiesFactsAll of the aboveWhat does a dimension table contain:HierarchiesForeign keysCategoriesPrimary keysAll of the aboveWhich type of relationship star schema contains between fact table and every dimension table1:11:MM:1M;NWhat is true about dimensional model:Easy to understandEfficient for queriesProcess Focusedall of the abovePART II:(Marks 1 points each)Fill in the blanks:___________________table contains giga / tera bytes of dataData grain means the level of details for a____________________________________ table contains records that describe facts________________ are system generated sequence numbers that do not have any builtin meanings___________________ contains the details of business events_________________ provides users with access to accurate, consolidated information from various internal and external resources.In bottom up design approach, data flows from _____________________ to the data mart tables.Kimball’s architecture consists of ______________________ and ________________________ .A ___________________________________ is an information delivery system________________________ contains the information about operational systems, ETL, process, data warehouse and predefined reports.The data warehouse queries process a lot of ___________________ data.Bus matrix is backbone of the _____________________________. It records dimensions and factsType 1 changes of slowly changing dimensions relate to ________________________in data.Metadata repository is like a general purpose ____________________ tool.Managers think in terms of __________________________________ for analysis.Dimension _________________ relate to drill-down analysisAggregates in fact table are ___________________ summaries.We use ___________________________ for designing tables for data warehouse and ER modeling for OLTP tables.Type 6 slowly changing dimension is a combination of type ____,______ and ___________________________ of the source table does not change in slowly changing dimension of type 6.There are three basic fact table grains: transactional,_____________________, accumulating snapshot.You should avoid _________________ schema because it is difficult for business users to understandDimension tables are usually ________________ and de-normalized.Multiple fact tables from multiple processes are combined into a single _________________ fact table if they can be expressed in same grainConsolidate fact table is a burden to the _______________processing(Key: OperationalDB, Dimension Definition, DW, ETL, Snow Flaking,Metadata, Back end, Product Key, Snow flake, front end, Presentation, PK of dimension table, OLAP, Galaxy Schema, Fact Table, Fact-less fact table, Data Design, Dimensional, BUS matrix, Star Schema, Wide, Rows in Fact table, Correction of errors, Directory, 1 2 3 4 5 6, Business Dimension, narrow, Pre Calculated, Hierarchies, Periodic, Consolidated, Technical Architecture, staging area, Data warehouse, dimensional modeling)part 3 Answer if true or falseLarge dimensions usually have multiple hierarchies T / FConformed dimensions are not absolutely necessary in a data warehouse T / FRequirement analysis of operational and data warehouse are very similar T / FCategories are attributes of business dimension. T / FIt is not always necessary to conduct pre-interview research T / FThe departmental users are very good source for information on data structures of operational system T / FThe data warehouse can be defined as the warehouse of data. T / FData warehouse helps in customized marketing T / FMost of organizations knowledge base contains unstructured data. T / FIt is most important to include unstructured data than structured data in data warehouse T / FNormally, data flows from data warehouse repository to data staging area. T / FTechnical architecture simply means the vendor tools T / FSometime the results of individual queries are held in temporary tables for repeated use. T / FMetadata is needed by IT for data warehouse administration T / FData warehouse in not a product, it is an environment. T / FEvery numeric attribute of production database is a fact in fact table T / FRequirement definition document is the basis for next phase T / FUnlike the requirements of operational system, the requirements of data ware house not very clear. T / FData warehouse is an ongoing process, each implementation project should have a cycle with a specific beginning and an end. T / FBusiness requirement gathering and technical architecture design can be done in parallel. T / FKimball’s life cycle is a more practical approach to design and implement data ware house T / FPriority grid is an effective tool for reaching consensus on a data warehouse starting single process for implementation. T / FApplication track coding can start in parallel with dimensional design part of data track….. T / F The questions drafted for interview by Lead should be more data oriented than IT oriented. T / F All facts in fact table should at the same grain or level of detail T / F
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