What are Aggregate tables? Aggregate table contains the summary of existing warehouse data which is grouped to certain levels of dimensions.Retrieving the required data from the actual table, which have millions of records will take more time and also affects the server performance.To avoid this we can aggregate the table to certain required level and can use it.This tables reduces the load in the database server and increases the performance of the query and can retrieve the result very fastly.
What is Dimensional Modelling? Why is it important ? Dimensional Modelling is a design concept used by many data warehouse desginers to build thier datawarehouse. In this design model all the data is stored in two types of tables - Facts table and Dimension table. Fact table contains the facts/measurements of the business and the dimension table contains the context of measuremnets ie, the dimensions on which the facts are calculated.
Why is Data Modeling Important? Data modeling is probably the most labor intensive and time consuming part of the development process. Why bother especially if you are pressed for time? A common response by practitioners who write on the subject is that you should no more build a database without a model than you should build a house without blueprints.
The goal of the data model is to make sure that the all data objects required by the database are completely and accurately represented. Because the data model uses easily understood notations and natural language , it can be reviewed and verified as correct by the end-users.
The data model is also detailed enough to be used by the database developers to use as a “blueprint” for building the physical database. The information contained in the data model will be used to define the relational tables, primary and foreign keys, stored procedures, and triggers. A poorly designed database will require more time in the long-term. Without careful planning you may create a database that omits data required to create critical reports, produces results that are incorrect or inconsistent, and is unable to accommodate changes in the user’s requirements.
What is data mining? Data mining is a process of extracting hidden trends within a datawarehouse. For example an insurance dataware house can be used to mine data for the most high risk people to insure in a certain geographial area.
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