Summary: Data warehousing tools are the tools that support data warehouse functions in different stages. These are basically software applications needed for the ETL (Extract, Transform, Load) process. These tools extract and transform data from operational systems and then help load that data into the data warehouse that further assists managers or users of an organization in the business decision-making process. The ETL process involves very complex activities. In order to facilitate the ETL process it is important to employ the right data warehouse tools. Read more…
The basic idea behind having a warehouse is to capture information from different parts of a business process and gather them all in a centralized database. We can define data warehouse as the collection of data and how it is used by the individuals of the company whom it supports. There is an immense amount of intelligence to be gained by your business by thoroughly analyzing the data that your customers provide. It helps you to make wise business decisions that will have an impact on your business for years to come. Read more…
If you are about to undertake your first data warehouse project, you need to be very watchful and careful about a few things. Of course, you want your data warehouse project to be successful and fruitful! The foremost step you should take up towards implementing a project is to look for the right data warehousing vendors. Well, the market is full of a wide variety of data warehousing vendors. But to start with, what are data warehousing vendors? Read more…
Data Warehouses are the subject-oriented, integrated, time-variant, non-volatile collections of data of enterprises used to support analytical decision-making. The data stored in a warehouse comes from different operational systems inside an enterprise as well as from external sources. Data Warehouses are separated from operational systems, however they are fed by operational systems with varied source data. Read more…
Data warehousing is an important part of an organization as it helps in the smooth operations of the different departments. It is a must-have in every small and big organization. The architecture of a data warehouse defines its success. The article below talks about data warehouse architecture, its construction and implementation. Read more…
Many BI vendors, particularly front-end solution-vendors, try to convince you that you do not need a data warehouse as a building or feeding mechanism for their front-end tool. This is a very bad advice and it will cost you dearly in the long run. Read more…
There are two prevalent approaches to the development of Datawarehouse Architectures:
- Data Warehouse (DWH) bus architecture (introduced by Ralph Kimball)
According to this approach the DWH is developed in phases. Each phase includes the development of a set of dimensional models which are linked together via conformed dimensions, thus forming a virtual bus architecture. Therefore, according to this approach, at the core of the DWH resides a denormalised dimensional data model, which handles data at the atomic level. Read more…
In part 1 of this article series, we described the staging area and the ETL process of a data warehouse architecture. In the present and following article we shall describe the presentation area of the data warehouse. The term presentation is used to denote the fact that this is the area, where data are presented to its Customers (the business analysts). There is no globally acceptable standard on the development of the data warehouse presentation area. Two major approaches have prevailed: the dimensional datawarehouse approach (proposed by R. Kimball) the corporate information factory (CIF) approach (proposed by B. Inmon) Kimball approach According to the Kimball approach, the presentation area is made of a number of dimensional data structures, called star schemas. A star schema is a relational data structure which involves the following: Read more…
This tutorial covers OLAP solutions used by Data warehouses and understanding Data Warehouse design. The enterprise needs to ask itself certain fundamental questions before actually launching on the process of designing the data warehouse. It must begin with a conviction that a data warehouse would really help its business and the return on investment will make it worth it. Read more…
In parts 2 & 3 of this article series, we described the data warehouse architecture according to the Kimball and the Inmon approach. In the present article we shall describe the main differences between the two approaches and their common points. The two approaches have the following common points: Read more…
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