What is ER Diagram 2008-03-13 00:15:00 ER - Stands for entitity relationship diagrams. It is the first step in the design of data model which will later lead to a physical database design of possible a OLTP or OLAP databaseorThe Entity-Relationship (ER) model was originally proposed by Peter in 1976 [Chen76] as a way to unify the network and relational database views. Simply stated the ER model is a conceptual data model that views the real world as entities and relationships. A basic component of the model is the Entity-Relationship diagram which is used to visually represents data objects. Since Chen wrote his paper the model has been extended and today it is commonly used for database design For the database designer, the utility of the ER model is: it maps well to the relational model. The constructs used in the ER model ca Read more:Diagram
What are Data Marts 2008-03-13 00:14:22 Data Mart is a segment of a data warehouse that can provide data for reporting and analysis on a section, unit, department or operation in the company, e.g. sales, payroll, production. Data marts are sometimes complete individual data warehouses which are usually smaller than the corporate data warehouse.orA data mart is a focused subset of a data warehouse that deals with a single area(like different department) of data and is organized for quick analysis
What is a Data Warehousing? 2008-03-13 00:13:37 Data Warehouse is a repository of integrated information, available for queries and analysis. Data and information are extracted from heterogeneous sources as they are generated....This makes it muchorData Warehouse is a repository of integrated information, available for queries and analysis. Data and information are extracted from heterogeneous sources as they are generated....This makes it much easier and more efficient to run queries over data that originally came from different sources. Typical relational databases are designed for on-line transactional processing (OLTP) and do not meet the requirements for effective on-line analytical processing (OLAP). As a result, data warehouses are designed differently than traditional relational databases.
What is the difference between the File and RandomAccessFile classes 2008-03-13 00:12:44 The File class encapsulates the files and directories of the local file system. TheRandomAccessFile class provides the methods needed to directly access data containedin any part of a file.orThe File class encapsulates the files and directories of the local file system. TheRandomAccessFile class provides the methods needed to directly access data containedin any part of a file. Read more:difference
What an I/O filter 2008-03-13 00:11:46 An I/O filter is an object that reads from one stream and writes to another, usuallyaltering the data in some way as it is passed from one stream to another.
What is the difference between OLAP and OLTP? 2008-03-13 00:10:26 OLAP stands for online analytical processing . In this we have access to live data. This process contain historical information to analyze. Data needs to be integrated.We can create reports that are multi-dimensional, supported by time-based analysis and ideal for applications with unpredictable, ad hoc query requirments.OLTP stands for online transaction processing. OLTP databases are fully normalized and are designed to consistently store operational data, one transaction at a time.It performs day-to -day operations and not support historical data. Read more:difference
What is the data type of the surrogate key? 2008-03-13 00:09:53 Always numberandNumuric, because it generates Numuric values.or1.It is always integer.2.This is because we are generating a key and best performance comes only when keys are numeric. so they generate keys numerically only so that sorting is also quiet cheap for numbers compared to char,varchar..It Supposed to be Numeric Its Like Serial Numbers
“A dimension table is wide but the fact table is deep” Explain the statement in your own words. 2008-03-13 00:09:05 Probably they mean dimesion tables will generally have more coloumns where as fact tables will have more rows...orA dimension table contains a higher granular information so have less no of records and it needs to have all the necessary details (More columns) related to the grain of the table. On the other side, A fact table has the lowest level grain of a subject area. Lower grain cause more number of rows in the Fact table.orDimension table has got all the detail informations of their respective table ,for eg, customer dimension table will contain all the related info about customers whereas fact table contains the main data,which contains the surrogate keys of every dimensions along with other measures. Read more:statement
What is the difference between aggregate table and materliazed view? 2008-03-13 00:08:12 Aggregate tables are pre-computed totals in the form of hierarchical mutidimensional structure.,whereas materliazed view ,is an database object which caches the query result in a concrete table and updates it from the original database table from time to time .Aggregate tables are used to speed up the query computing whereas materialized view speed up the data retrieval . Read more:difference
briefly state different between data ware house & data mart? 2008-03-12 23:20:15 1) Dataware house is made up of many datamarts. DWH contain many subject areas. but data mart focuses on one subject area generally. e.g. If there will be DHW of bank then there can be one data mart for accounts, one for Loans etc. This is high level definitions.3) Metadata is data about data. e.g. if in data mart we are receving any file. then metadata will contain information like how many columns, file is fix width/elimted, ordering of fileds, dataypes of field etc.. Read more:different
how can you implement many to many relation in star schema model? 2008-03-12 23:19:51 Many-many relations can be implemented by using snow flake schema .With a max of n dimensions .orHiUpto my knowlege designers implementing this M-M relation asFirst break the schema to 1-M and M-1 relationsLet me correct if any thing is wrong Read more:model
Data Warehousing questions: 2008-03-12 22:39:39 1) What is source qualifier?2) Difference between DSS & OLTP?3) Explain grouped cross tab?4) Hierarchy of DWH?5) How many repositories can we create in Informatica?6) What is surrogate key?7) What is difference between Mapplet and reusable transformation?8) What is aggregate awareness?9) Explain reference cursor?10) What are parallel querys and query hints?11) DWH architecture?12) What are cursors?13) Advantages of de normalized data?14) What is operational data source (ODS)?15) What is meta data and system catalog?16) What is factless fact schema?17) What is confirmed dimension?18) What is the capacity of power cube?19) Difference between PowerPlay transformer and power play reports?20) What is IQD file?21) What is Cognos script editor?22) What is differ Read more:questions
what are the types of dimension tables 2008-03-12 22:38:33 Dimensions are of 3 types
mainly in case of slowly changing dimensions: Type 1 ->Doesnt maintain any history and is update only.Type 2-> Maintains full history.Insert row when certain attributes change else update row.The latest record is identified by a flag or date field which is called the MRI or Most Recent IndicatorType 3->Maintains partial history.History is maintained as columns and not rows.Hence it is predecided as to till how many levels of history you want to maintain.orthere are five types of dimensions:1. star schema2. snowflake schema3.parent-child schema4.virtual dimension5. mining model
Explain paradigm of Bill Inmon and Ralph Kimball. 2008-03-16 07:14:12 Bill Inmon's paradigm: Data warehouse is one part of the overallbusiness intelligence system. An enterprise has one data warehouse,and data marts source their information from the data warehouse. Inthe data warehouse, information is stored in 3rd normal form.Ralph
Kimball's paradigm: Data warehouse is the conglomerate of alldata marts within the enterprise. Information is always stored in thedimensional model.
What is the difference between data warehousing and business 2008-03-16 07:13:41 Data warehousing deals with all aspects of managing the development,implementation and operation of a data warehouse or data martincluding meta data management, data acquisition, data cleansing,data transformation, storage management, data distribution, dataarchiving, operational reporting, analytical reporting, securitymanagement, backup/recovery planning, etc. Business intelligence, onthe other hand, is a set of software tools that enable an organizationto analyze measurable aspects of their business such as salesperformance, profitability, operational efficiency, effectiveness ofmarketing campaigns, market penetration among certain customergroups, cost trends, anomalies and exceptions, etc. Typically, the term“business intelligence” is used to encompass OLAP, data visualization,data Read more:difference
What is active data warehousing? 2008-03-16 07:13:18 An active data warehouse provides information that enables decisionmakerswithin an organization to manage customer relationshipsnimbly, efficiently and proactively.
What is junk dimension? 2008-03-16 07:12:35 A number of very small dimensions might be lumped together to forma single dimension, a junk dimension - the attributes are not closelyrelated. Grouping of Random flags and text Attributes in a dimensionand moving them to a separate sub dimension is known as junkdimension.
What is a Cube and Linked Cube with reference to data 2008-03-16 07:12:12 What is a Cube and Linked Cube with reference
to datawarehouse?Ans:Cubes are logical representation of multidimensional data.The edge ofthe cube contains dimension members and the body of the cubecontains data values. The linking in cube ensures that the data in thecubes remain consistent.
What is the difference between OLAP and data warehouse? 2008-03-16 07:11:42 Datawarehouse is the place where the data is stored for analyzingwhere as OLAP is the process of analyzing the data,managingaggregations, partitioning information into cubes for in depthvisualization. Read more:difference
What is Data Mart? 2008-03-16 07:11:09 A data mart (DM) is a specialized version of a data warehouse (DW).Like data warehouses, data marts contain a snapshot of operationaldata that helps business people to strategize based on analyses of pasttrends and experiences. The key difference is that the creation of adata mart is predicated on a specific, predefined need for a certaingrouping and configuration of select data. A data mart configurationemphasizes easy access to relevant information (Reference : Wiki).Data Marts are designed to help manager make strategic decisionsabout their business.
What is surrogate key? 2008-03-16 07:10:49 Surrogate key is a substitution for the natural primary key. It is just aunique identifier or number for each row that can be used for theprimary key to the table. The only requirement for a surrogate primarykey is that it is unique for each row in the table. It is useful becausethe natural primary key can change and this makes updates moredifficult.Surrogated keys are always integer or numeric.
Why is Data Modeling Important? 2008-03-16 07:10:29 Data modeling is probably the most labor intensive and timeconsuming part of the development process. The goal of the datamodel is to make sure that the all data objects required by thedatabase are completely and accurately represented. Because the datamodel uses easily understood notations and natural language , it canbe reviewed and verified as correct by the end-users.In computer science, data modeling is the process of creating a datamodel by applying a data model theory to create a data modelinstance. A data model theory is a formal data model description.When data modelling, we are structuring and organizing data. Thesedata structures are then typically implemented in a databasemanagement system. In addition to defining and organizing the data,data modeling will impose (implicitly or Read more:Modeling
What is degenerate dimension table? 2008-03-16 07:09:52 If a table contains the values, which are neither dimension normeasures is called degenerate dimensions.
What is Difference between ER Modeling and Dimensional 2008-03-16 07:09:33 What is Difference between ER Modeling
and DimensionalModeling?Ans:ER modeling is used for normalizing the OLTP database design.Dimensional modeling is used for de-normalizing the ROLAP/MOLAPdesign.
Differences between star and snowflake schema? 2008-03-16 07:09:06 Star schema - A single fact table with N number of Dimension, alldimensions will be linked directly with a fact table. This schema is denormalizedand results in simple join and less complex query as wellas faster results.Snow schema - Any dimensions with extended dimensions are know assnowflake schema, dimensions maybe interlinked or may have one tomany relationship with other tables. This schema is normalized andresults in complex join and very complex query as well as slowerresults.
What Snow Flake Schema? 2008-03-16 07:08:38 Snowflake Schema, each dimension has a primary dimension table, to which one or more additional dimensions can join. The primarydimension table is the only table that can join to the fact table. Read more:Flake
What is a Star Schema? 2008-03-16 07:08:13 Star schema is a type of organizing the tables such that we canretrieve the result from the database quickly in the warehouseenvironment.
What is BUS Schema? 2008-03-16 07:07:52 BUS Schema is composed of a master suite of confirmed dimensionand standardized definition if facts.
Recommend Site To A Friend
