The key thing that all OLAP products have in common is multidimensionality, but that is not the only requirement for an OLAP product.
An OLAP application is targeted to deliver most responses to users within about five seconds, with the simplest analyses taking no more than en second and very few taking more than 20 seconds. Impatient users often assume that a process has failed if results are not received with 30 seconds, and they are apt to implement the CB finger salute’ or Cite*Strict+Diet’ unless the system warns them that the report will take longer. Even if they have been warned that it will take significantly longer, users are likely to get distracted and lose their chain of thought, so the quality of analysis suffers.
This speed is not easy to achieve with large amounts of data, particularly if Oromo. Fly and ad hoc calculations are required. A wide variety of techniques are used to achieve this goal, including specialized forms of data storage, extensive pre-calculations and specific hardware requirements, but a lot of products are yet fully optimized, so we expect this to be an area to developing technology. In particular, the SAP Business Warehouse is a full pre-calculation approach that fails as the databases simply get too.
Likewise, doing everything on-the-fly is much too slow with large databases, even if the most expensive server is used, Slow query response is consistently the most often-cited technical problem with OLAP products. OLAP is used for mainly for analysis. This means that the system copes faith any business logic and statistical analysis that is relevant for the application and the user, and keep it easy enough for the target user. This analysis is done in the application’s own engine or in a linked external product such as a spreadsheet.
All the required analysis functionality can be provided in an intuitive manner for the target users. This could include specific features like time series analysis, cost allocations, currency translation, goal seeking, ad hoc multidimensional tutorial changes, non-procedural modeling, exception alerting, data mining and Other application dependent features. The OLAP system implements all the security requirements for confidentiality. Not all applications need users to write data back, but for the growing number that does, an OLAP system handles multiple updates in a secure manner.
Multidimensional data is a key requirement. If one had to pick a one-‘. Ford definition of OLAP, this is it The OLAP system provides a multidimensional conceptual view of the data, including full support for hierarchies and multiple hierarchies, certainly the most logical way o analyze your business or Organization. Information is gathered based on business needs, wherever it is and however much is relevant for the application. The sure capacity of various applications in terms Of how much inputted data, differs greatly the largest OLAP applications can hold at least a thousand times as much data as the smallest.
Many considerations are made here, including data duplication, memory requirements, disk space utilization, performance, integration with data warehouses and the like. DATA WAREHOUSE AND DATA Most data in OLAP applications originates in other systems. However, in some applications (such as planning and budgeting), the data might be captured directly by the OLAP application. When the data comes from other applications, it is usually necessary for the active data to be stored in a separate, duplicated, tort for the OLAP application.
This may be retorted to as a data warehouse or, more commonly today, as a data mart. The most common uses for a data warehouse include performance, multi-data stores, data cleansing, data adjusting, timing, and historical analysis, Data warehouses are often large, but are nevertheless used for unpredictable interactive analysis. This requires hat the data be accessed very rapidly, which usually dictates that it be kept in a separate, optimized structure which can be accessed without damaging the response from the operational systems.
Most data marts multiple feeder systems from other sourced data, possibly including external sources and even desktop applications. The process Of merging these multiple data feeds can be very complex, because the underlying systems probably use different coding systems and may also hue different periodicities. For example, in a multinational company like Whet, it is rare for departments in different entries to use the same coding system for suppliers and customers, and they may well also use different ERR systems.
It is common for transaction systems to be full of erroneous data, which needs to be Decreased’ before it is ready to be analyzed. Apart from the small percentage of accidentally MIS-coded data, there could be examples of optional fields that have not been completed. For example, many companies would like to analyze their business in terms of their customers’ vertical markets. This requires that each customer (or even each sale) e assigned an industry code; however, this takes a certain amount of effort on the part those entering the data, for which they get little return, so they are likely, at the very least, to cut corners.
There may even be deliberate distortion of the data it sales people are rewarded more for some sales than others: they will certainly respond to this direct temptation by Calculating’ (ii distorting) the data to their own advantage if they think they can get away with Data marts are often used for adjusting data before it can be used for analysis, In order that this an be done without affecting the transaction systems, the data needs to be kept separate The data in stored in these warehouses more often than not comes from sources and it is very likely that they are updated on different cycles.
At any one time, therefore, the data may be at different stages of update. For example, the month-end updates may be complete in one system, but not in another and a third system may be updated on a weekly cycle. In order that the analysis is based on consistent data, the data needs to be staged, within a data warehouse. THREE-TIER ARCHITECTURE
A tier is a level of access or processing data from applications to databases. The three-tier architecture is used when an effective distributed client}server design is needed that provides increased performance, flexibility, maintainability, risibility, and scalability, While hiding the complexity Of distributed processing from the user.
These characteristics have made three layer architectures a popular choice for Internet applications and net-centric information systems. The first tier represents the end user interface (Web or application). The middle tier provides ODBC like process management services (such as process placement, process enactment, process monitoring, and process resounding) that are shared by multiple applications.
The third tier provides database management functionality and is dedicated to data and file services that can be optimized without using any proprietary database management system languages, The data management component ensures that the data is consistent throughout the distributed environment through the use of features such as data locking, consistency, and replication, It should be noted that connectivity between tiers could be dynamically changed depending upon the user’s request or data and services, ASP Abbreviated as ASP, a specification for a dynamically created Web page with a _ASP extension that utilizes Active scripting usually V Script or Script code. When a browser requests an ASP, the Web server generates a page with HTML code and sends it back to the browser. So ASPs are similar to CGI scripts, but they enable Visual Basic programmers to work with familiar tools. ASP is a server-side scripting environment. It was introduced by Microsoft in 1996 and is comprised of built-in objects, server-side scripts, ADO capability (access to databases), and
Active components Which allow web developers to build dynamic web sites such as search engines, e-commerce sites, auction houses, guardhouses, web portals, and more. Server-side is comparable to it’s cousin – “client. Side”. The web browser is the “client” in this case and the web server is obviously the “server”. ASP has certain built. In ‘objects’ that can be used to store and retrieve variables, get information from user submitted forms, get information about the server itself and, of course, write HTML based on this information. ASP also allows you to run objects on the server which provide access to ODBC compliant databases wrought Active Data Objects or custom components which provide any function or seer. ‘ice that be programmed in Windows.
Generally though, ASP can be used to create highly interactive and dynamic web pages that don’t require a lot of client-side programming. The client-side scripts control things within your web browser. However, immediately before you access an ASP enabled web page, an ASP script builds the script on a server, That web page does not really exist. You might expect there to be an HTML document (i. E. Web page) on the web server which was sent to your web browser. UT that’s not the case at all. What actually happens when you requested the page is far more interesting. The requested web page is an ASP file which was placed on the web server, but the file is not a web page… It is a script which is designed to build a eve page.
The ASP pages are built in mere milliseconds before it was sent to the web browser _ The advantage of this is that the ASP page can instruct the server to build the HTML code customized just for the web surfer depending on Whether or not their using a Microsoft or Netscape eve browser, or depending on their I. P. Address, r depending on Whether or not they have ever visited the website before! Therefore, it is possible to build truly dynamic web pages. For instance, an ASP script can read information from a database and display it in a web page – and the page contents would then be determined by the records in the database, which were retrieved by the script. In that case, it’s possible for a single ASP file to have millions of different “faces”, if the database has that many records. The most common use of ASP is database connection.
