star schema in data warehouse

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Comparison of the characteristics of nine large data warehouse schemes

enough, a change in data warehouse design often leads to the reconstruction of the database. In addition, the current level of integration between Oracle 8i and Express is not high enough, Oracle 8i and express need to replicate metadata, if Oracle Discoverer (or Bo) need to access the rollup data, It is difficult to maintain the summary

SQL Server Data Warehouse concepts and building process

deposits and withdrawals for this month at the fastest speed in the shortest time, if this type of query is placed on the original database, it will lose the meaning of the Data Warehouse. The ultra-large amount of data makes it impossible to query, at this time, you need to convert the meaningful data for this query

The construction and analysis of SQL Server Data Warehouse

, if this query on the original database to do, you will lose the significance of data warehousing, large-scale data so you can not query down, At this point you will have to the query meaningful data into the data warehouse, this is the

Use partitions in SQL Server 2000 Data Warehouse

The partition view joins the horizontal partition data from a group of Members to make the data look like it is from the same table. SQL Server 2000 distinguishes the local partition view from the distributed partition view. In the local partition view, all related tables and views reside on the same instance of SQL Server. In the distributed partition view, at least one table in the relevant table resides

SQL Server Data Warehouse Construction and Analysis

step because I do not have a standardized original database or standardized business requirements. I just used the STAR MODEL AND snowflake model to create several typical data warehouse tables. The table relationships are as follows: WindowFactFor fact tables,Time,Address,DetailTime Dimension, address dimension, detailed address dimension,DetailAgainAddr

Introduction to the DB2 data warehouse OLAP Service

the basis for providing data warehouse solutions to customers. OLAP data market When talking about the data market, many people may immediately think about multidimensional or OLAP analysis. According to the definition, the data market is a subset of the

Comparative analysis---Relational model and multidimensional model of Data Warehouse database design method

Label:There are two kinds of database design models widely used in Data warehouse: Relational type and multidimensional type. It is generally believed that the relational model in the design method of Data Warehouse is "Inmon" method and multidimensional model is "Kimball" method. First look at the relational model, wh

AWS pushes the data warehouse service Redshift price only for TeradataIBMOracle

, and HP. The share price of Teradata, a leading data warehouse service company, fell by 3.7% to $59.27 on Wednesday due to the hidden concerns of competition from AWS. Background (Baidu encyclopedia ): William H. the definition proposed by Inmon in the book "Building the Data Warehouse" published in 1991 is widely acc

The basic architecture of the Data Warehouse

documents that may be generated outside the site and other types of data that are useful for company decisions. data storage: The source data is exported through the daily tasks of ETL, and is converted into the Data warehouse in the form of attributes. The

Data Warehouse-New optimization features for SQL Server 2008

Label:In the absence of a real data warehouse database, all data warehouses are now just a relational database created based on the dimension model, but the Data Warehouse database itself has some differences, such as the unique features of an OLTP database, such as the most

Data Warehouse-New optimization features for SQL Server 2008

Tags: Data Warehouse optimizationin the absence of a real data warehouse database, now all data warehouses are just a relational database created based on the dimension model, but the Data War

Use Hive to build a data warehouse

systems that may have existed for decades with systems that were only implemented a few months ago? This is still before big data and Hadoop. By adding unstructured, Data, NoSQL, and Hadoop to a combination, you will soon get a huge data integration project. The simplest way to describe a data

Software function Comparison of nine large data warehouse development

flexible enough, a change in data warehouse design often leads to the reconstruction of the database. In addition, the current level of integration between Oracle 8i and Express is not high enough, Oracle 8i and express need to replicate metadata, if Oracle Discoverer (or Bo) need to access the rollup data, It is difficult to maintain the summary

Two major schools of Data Warehouse theory (_bi.old)

constructs dimension Data Warehouse in the form of star model or snowflake model, in which data mart is closely combined with dimension Data Warehouse, and data mart is a logical subje

Three major issues to be avoided in deploying a data Warehouse system

technical requirements of the Data Warehouse project. In addition to identifying hasty business problems and requirements for data Warehouse devices, the performer should look at the data-related business rules in the Data

Open-source MySQL efficient data warehouse solution: Infobright details _ MySQL

avoid the problem of maintaining indexes and indexes expanding with data. Data in each column is compressed and stored in blocks. Each Knowledge Grid node records the statistical information in the block, instead of indexing, to accelerate search. Quick response to complex aggregate queries: suitable for complex analytical SQL queries, such as SUM, COUNT, AVG, and GROUP InfobrightValue Save design co

Open-source MySQL efficient data warehouse solution: Infobright details, mysqlinfobright

the block, instead of indexing, to accelerate search. Quick response to complex aggregate queries: Suitable for complex analytical SQL queries, such as SUM, COUNT, AVG, and GROUP InfobrightValue Save design costs. No complex data warehouse model design requirements (such as star model and snowflake model), no materialized view,

9 Characteristics comparison of large Data Warehouse

Express is not high enough, Oracle 8i and express need to replicate metadata, if Oracle Discoverer (or Bo) need to access the rollup data, It is difficult to maintain the summary data in both Oracle and Express. Notably, the Oracle 9i, which has just come out, is an important feature of OLAP and data mining. Sybasesybase provides a

Correct understanding of four types of data warehouse modeling methods of SQL Server

SQL ServerCategory 4Data warehouse modelingMethods are mainly divided into the following four types. The first type is the three-paradigm modeling of relational databases. We usually use the three-paradigm modeling method to build various types of operational database systems. The second category is the three-paradigm data warehouse modeling promoted by inmon,

Data Warehouse scalability of SQL Server 2008 new features (i)

Backup compression Star Association performance faster parallel query on partitioned tables grouping SETS Resource Monitor Data compression alignment partitioned indexed view Integration Services Lookup Performance Pipeline Performance Analysis Services Backup MDX query performance: Block compute query and write back perform

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