A data warehouse is constructed by integrating data from multiple heterogeneous sources. It supports analytical reporting, structured and/or ad hoc queries and decision making. This tutorial adopts a step-by-step approach to explain all the necessary concepts of data warehousing. Objective of Data warehouse Deployment Till the year , the architecture of the data warehouses was built to enable the existence of vendor's specific. In this course, you would be learning all the concepts and terminologies related to the Datawarehouse, such as the OLTP, OLAP, Dimensions, Facts and much.


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They must resolve such problems as naming conflicts and inconsistencies among units of measure. When they achieve this, they are said to be integrated.


Nonvolatile Nonvolatile means that, once entered into the warehouse, data should not change. This is logical because the purpose of a warehouse is to enable you to analyze what has occurred. Time Variant In order to discover trends in advanced data warehouse concepts, analysts need large amounts of data.

Data Warehousing Concepts

This is very much in contrast advanced data warehouse concepts online transaction processing OLTP systems, where performance requirements demand that historical data be moved to an archive.

A daily data load can be made an hourly data load The other option is to store the real-time data in an external real-time data cache outside the traditional data warehouse The RTDC real-time data cache can be a dedicated database server involved in loading, storing, and advanced data warehouse concepts the real-time data.

There is no risk of introducing scalability or performance problems on the existing data warehouse when using an RTDC Scalability Challenge The issue of scalability is the most difficult problem faced by organizations when deploying real-time data warehouse solutions.

The reports need to be confined to simple and quick single-pass queries The addition of more hardware to deal with the expandability problems is another solution.

More nodes can be added to a high-end database system or a stand-alone data warehouse box can be upgraded with faster processors and additional memory Query Tools A querying and reporting tool helps in executing regular reports, organize listings, and perform cross-tabular reporting and querying Significance of SQL SQL is the official database query language that is used to access and update the data involved within a relational data base management system or RDBMS The importance of SQL for querying an reporting is that the language has represented a mostly standard way of accessing different RDBMS products Each RDBMS product has a minor different SQL dialect but the basic syntax is same Technical Query Tools SQL forms the basis for the technical query tools.

Data Warehousing Tutorial

Many product-to-product matchups are available in data warehousing environments that offers tools provided by RDBMS vendors and other third-party vendors A series of query tools allows the users to type in and edit the SQL queries.

These tools are not designed for the end-users but for the developers involved in the coding and testing process User Query Tools User query tools offer visually-oriented, painting, environments that enables users to create screens for report-layouts, the data columns desired for the report, or the rows of data that the user wants to select Reporting Tools When the requirements of the end-users is complex user interaction or sophisticated formats, a tool with more reporting features is included The reporting tools provide data accessing, filtering, and simple formatting Reporting tools offer an environment that enables the users to create refined layouts that concentrate on formatting the data obtained from the database query Data warehousing Analytics Data warehousing analytics administers a framework of database, reports, and advanced data warehouse concepts objects that are created to interface with one or more Commerce Server runtime databases.

The data warehouse analytics system is incorporated with a SQL server database, an analysis services databases, a set of functionalities that a system administrator uses to import and maintain data Use of data warehouse analytics Using the SQL Server or SQL Server reporting services we can advanced data warehouse concepts reports.

Data can also be imported using the Import Wizard Types of data representation using analytics Logical Representation The logical representation consists of the following entities Classes: A class signifies a set of logically related information Data members: A data member represents an attribute of a class Keys: A key is an exclusive identifier for a class Relations: Integrated In Data Warehouse, integration means the establishment of a common unit of measure for all similar data from the dissimilar database.

The data also needs to be stored in the Datawarehouse in common and universally acceptable manner.


A data warehouse is developed by integrating data from varied sources like a mainframe, relational databases, flat files, etc.

Moreover, it must keep consistent naming conventions, format, and coding.

10 - Advanced Data Warehousing Concepts

This integration helps in effective analysis of data. Consistency in naming conventions, attribute measures, encoding structure etc.

Consider the following example: In the above example, there are three different application labeled A, B and C. Information stored in these applications are Gender, Date, and Balance. However, each application's data is stored different way.