Data warehouse

DWH Architecture

There are three types of Architectures proposed in warehouse and recently one additional architecture proposed called MDM.
  • Topdown
  • Bottomup
  • Hybrid
  • MDM
Top-Down Approch
According to the W.H Inmon first we need to load the Data warehouse and later we will load the data marts. As the data mart data is dependent on Data warehouse we call these marts as dependent data marts.
         The data flow in the topdown OLAP environment begins with data extraction from the operational data sources. The data is loaded into the staging area and validated and consolidated for ensuring a level of accuracy and the transferred to the Operational Data Store (ODS). The ODS stage is sometimes skipped if it is a replication of the operational databases. Data is also loaded in to the parallel process to avoid extracting it from the ODS. Detailed data is regularly extracted from the ODS and temporarily hosted in the staging are for aggregation, summarization and then extracted and loaded in to the Data Warehouse.
                   Once the data warehouse aggregation and summarization processes are complete, the data mart refresh cycles will extract the data from the data warehouse into the staging area nd perform  new set of transformations on them. This will help organize the data in particular structures required by data marts. Then the data marts can be loaded with the data and the OLAP environment becomes available to the users.
Bootom-Up Approch
According to the Ralph Kimbell first we need to load the data mart with available data later we will load data warehouse. As the data marts loaded first we call them as independent data marts.
                In the bottom up approach data marts are first created to provide reporting and analytical capabilities for specific business processes. The single data mart often models a specific business area such as "Sales" or "Production". These data marts can eventually be integrated  to create a comprehensive data warehouse. The integration data marts is manged through the implementation of "data warehouse bus architecture". The data warehouse bus architecture primarily an implementation of  "the bus", a collection of conformed dimensions and facts, which are dimensions that are shared between facts two or more data marts.  
               The dta flow in the bottom up approach starts with extraction of dt from operational databases in to the staging area where it is processed and consolidated and then loaded into the ODS. The data in the ODS is appended to or replaced by the fresh data being loaded. After the ODS is refreshed the current data is once again extracted into the staging area and processed into the data mart structure.The data from the data mart, then is extracted to the staging are aggregated, summarized and so on and loaded into the Data Warehouse and made available to the end user for analysis.   
Data Waarehouse in a hybrid solution is kept on third norml form to eliminate data redundency. A normal data relational database however is not efficient for business intelligence reports where dimensional modelling is prevalent small data marts can shop for data from the consolidated warehouse and use the filtered, specific data for the fact tables and dimensions required.The Data warehouse effectively provides a single source of information from which the data marts can read from creating high flexible solution from BI point of view. The hybrid architecture allows a Data warehouse to be replaced with master data management solution when operational , non static information could reside.
Master Data Management(MDM)   
MDM has the objective of providing processes for collecting, aggregating, matching, cnsolidting, quality assuring, persisting and distributing such data through out an organization to ensure consistency and control in the ongoing maintenance and application use of this information. The term recalls the concept of a master file from an earlier computing era. MDM is similar to, and some would say the same as, virtual or federated data base management.  

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