Summarize Information with Data Wareouse

The term “data warehouse” means a data store as opposed to the classic data base that is intended to summarize the data in a DBMS, transforming them into meaningful information for those responsible decision-making in the company.
Normally in a classical database it is possible to query and intelligent views on the data, but this is not always possible due to the nature of the data base, in fact, many large organizations have multiple databases that you divide the work and are also implemented with different technologies. The task of a system based on data warehouse is to provide support to business decisions that you have to take, in these cases the person responsible does not affect the individual orders or the individual movements of material, rather than, for example, the material sold in a given country and at a given time. In the past to indicate software systems with these characteristics you used the term DSS ( Decision Support System ), which today has become the most common term ( OLAP On-Line Analytical Processing ), often opposed to OLTP ( On Line Transaction precessing ). In the first case we have a software that allows the user to interact with the database with very complex analytical queries, while in the second case we have operations on small data sets, these are the classic enterprise software with database behind. A data warehouse is then a system to provide aggregate data relevant to the development of the enterprise decision-making, even if these are needed for heavy queries that would normally require a lot of time.
A data warehouse is implemented on the basis of the classical relational DBMS, but for which construction techniques that are used in classical systems would be considered wrong. For example, instead of applying the techniques of normalization of tables, it tends to perform the reverse operation, by decreasing the number of them, without even worrying about data redundancy. The construction of a data warehouse is based on the existing archives in the organization, the first step is to understand the information that is necessary to extract the leadership to undertake certain corporate actions. You can then go to the definition of the structure of the data warehouse, using standard Entity-Relationship diagrams. You will have to take particular care in defining the tables and indexes, especially the most frequent queries must have acceptable processing time. Once the stage of creating the structure that is to receive the data warehouse, you have to go to populate the tables with the transfer of data from the original database. A very important aspect is to define the update frequency of the data, in fact, some companies just a week, while in other cases it may be required more frequently. Last aspect is to create the user interface, which will have to be simple and intuitive, allowing you to query the data based on various factors such as, sales by product, by sector or geographical area.
In RGPSoft we always try to insert an intermediate approach to data warehousing, it is possible to see one of our free management software in action, with extraction of data to be popular in an Excel spreadsheet, a tool which we thought was the best way to analyze the data. The program that I recommend you try it Calus 2012, a simple but powerful application in Access to the warehouse is completely free and open source to download your copy you can visit our website.