A Data warehouse is a repository of an organization’s electronically stored data. Data warehouses are designed to manage and store the data whereas the Business Intelligence (BI) focuses on the usage of data to facilitate reporting and analysis. The purpose of a data warehouse is to house standardized, structured,
![041902_schraml_2[1]](/wp-content/uploads/2011/07/041902_schraml_21-150x150.gif)
There are three types of slowly changing dimensions: Type 1, Type 2, and Type 3. Each of these types tries to help the designer of the star schema eliminate paradox from their dimensional model (just as the three interpretations of the Schrödinger’s Cat thought experiment tries to eliminate the paradox of the living dead).
![199807_012_2[1]](/wp-content/uploads/2011/07/199807_012_21-150x150.gif)
An operational data store (or “ODS”) is a database designed to integrate data from multiple sources for additional operations on the data. The data is then passed back to operational systems for further operations and to the data warehouse for reporting. Because the data originates from multiple sources, the
![dwh+components[1]](/wp-content/uploads/2011/06/dwh+components1-150x150.png)
Operational Source Systems are the systems of record that capture the transactions of the business. The source systems are usually different than the data warehouse because presumably we have little to no control over the content and format of the data in these operational legacy systems.
![Database_2[1]](/wp-content/uploads/2011/09/Database_21-150x150.png)
Data Access Tools are end user oriented tools that allow users to build structured query language (SQL) queries by pointing and clicking on the list of table and fields in the data warehouse.
Recent advancement in information technology has brought about new and innovative software applications that have more standardized languages, format, and
![h-00100020000_image002[1]](/wp-content/uploads/2011/05/h-00100020000_image0021-150x150.gif)
The reporting, analysis, and interpretation of business data is of central importance to a company in guaranteeing its competitive edge, optimizing processes, and enabling it to react quickly and in line with the market.
![mistry[1]](/wp-content/uploads/2011/09/mistry1-150x150.png)
This video is just amazing! This makes me want to figure out how he did all this. Pranav Mistry demos several tools that help the physical world interact with the world of data — including a deep look at his SixthSense device and a new
![right_fisher[1]](/wp-content/uploads/2011/09/right_fisher1-150x124.jpg)
Data life cycle management (DLM) is a policy-based approach to managing the flow of an information system’s data throughout its life cycle: from creation and initial storage to the
![Allosphere18_w479[1]](/wp-content/uploads/2011/09/Allosphere18_w4791-150x150.jpg)
Amazing video found on TED.com about the AlloSphere. JoAnn Kuchera-Morin demos the AlloSphere, a new way to see, hear and interpret scientific data. Dive into the brain, feel electron spin, hear the music of the elements
![erdexample[1]](/wp-content/uploads/2011/09/erdexample1-150x150.gif)
What is ER Modeling?
ER modeling itself defines the methodology used in the analysis and design of information-based systems. Database designers often use this methodology to gather requirements and define the architecture of the database systems. The output of this
Top Posts
-
