lookup table in data warehouse

are the definitions of these things, such as time, department, and dimension tables. The fact table contains the data to be queried and the dimension ID. In terms of concept, it is a bit obscure. Any technology serves applications, which can be easily understood in combination with applications. Take banking as an example. The database is the data platform of th

the first to implement a data warehouse. The following lists the steps that need to be taken into account in the data warehouse implementation process. Some of them may have never been realized, while others may have been used in the implementation process, but you may have more insights if you think about it again.

. The following lists the steps that need to be taken into account in the data warehouse implementation process. Some of them may have never been realized, while others may have been used in the implementation process, but you may have more insights if you think about it again. Open-minded, constantly trying new ways to find a feasible data

warehouse modeling tools and performance tools appear, and the personal experience and quality of designers will play an important role. The implementation of data Warehouse technology at present in the actual application of data warehouse technology mainly includes the fol

server|sql| data Partitioned views join horizontal partitioned data from a group of members so that the data looks like it comes from the same table. SQL Server 2000 distinguishes between local partitioned views and distributed partitioned views. In the local partitioned view, all related tables and views reside on the

. 3) consider how the data in the data warehouse is distributed across servers when the data volume rapidly increases to the point where the data in a single server cannot be stored, by topic, geographical location, or time? These policies have a significant impact on the

: This SQL requires grouping of query results, that is, the same product names are grouped together, and then the inventory quantity per group is calculated.2. Query for product names that exist in all warehousesSql: Select name from PWhere not exists(SELECT * FROM WWhere not exists(SELECT * FROM Lwhere P.productid=l.productid and W.warehouseid=l.warehouseid)) Analysis: This query is more difficult than the first, the main research on the SQL not exists understanding a

interrelationships across the enterprise. Based on this enterprise model, the business people who do not understand the database technology and SQL statements can also know the data in the Data Warehouse. Multidimensional Data Model: This is an important part of the enterprise conceptual model, which tells the busines

of aggregation of data in a data warehouse depends on many design factors, such as the speed requirements of OLAP queries and the granularity required for analysis. For example, if you aggregate sales details into a daily summary instead of an hourly rollup, OLAP queries will run faster, but you can do this only if you don't need to analyze sales per hour. Orga

development" and "bottom-up" mode is that it uses a unified data model of the global Data Warehouse to guide the construction of various departments ' data marts, which can resolve the inconsistency of data between data marts and

called the second paradigm, and so on. Therefore, Paradigms at all levels are backward compatible.　　What is star mode?　　　　The star schema is a multidimensional data relationship that consists of a Fact Table and a set of dimension tables.. Each dimension table has a dimension as the primary key. All these dimensions are combined into the primary key of the fact