Importance of Online Transaction Processing - Essay Example

OLTP and OLAP OLTP (Online Transaction Processing) refers to the system whereby business transactions or applications are managed online, i.e, wherethe nature of processing is such that the user’s request receives an immediate response. Bernstein defines an online transaction as the “execution of a program that performs an administrative function by accessing a shared database, usually on behalf of an online user.(Bernstein, 1997:3). A processing system to manage transactions must be the kind of system that can efficiently “handle high volume, avoid errors due to concurrent operation, avoid producing partial results, grow incrementally, avoid downtime and never lose results.” (Bernstein, 1997:3). Some examples of Online Transaction Processing applications include electronic reservations, electronic transfer of funds, inventory control, telephone switching and centralized command and control services. Online Transaction Processing is used by a variety of industries, such as banking, airlines, mail order retailing, marketing and manufacturing. Examples include electronic banking, processing of orders online, airline reservations, employee time clock systems, etrading in stocks, shares and bonds and various ecommerce applications are all examples of an online transaction processing environment. OLTP is generally used in processing large scale volumes of transactions. Transaction monitoring software that deals with the online processing of transactions on a mass scale represents a combination of several applications, such as operating systems, database systems, operations programming languages and communication systems. Bernstein and Newcomer (1997) have pointed out that the software environment that is the prime driver of online transaction processing applications are based on Transaction Processing monitoring products and some of the examples he cites and elaborates upon are ACMS, CICS, Encina, IMS, Pathway/TS, Top End, or TUXEDO. The most commonly used software is IBM’s CICS. Based upon measurements of usage in terms of number of licenses, customers and the revenue it garners, CICS appears to have the largest market share of any transaction processing software application. (Bernstein and Newcomer, 1997:127). The CICS system was first developed in 1968 and is now able to run on several different platforms and operating systems, using the appropriate “process and memory abstractions” available on each system. (Bernstein, 1997: 127). Online Transaction Processing applications are targeted towards achieving maximum speeds in access and processing of data. Hence, basic data about customers are stored, such as name, age, gender, address, goods purchased, price, order number, etc. Such data may also not be retained for a very long period of time because of the costs of storage and the need to ensure that the most current data is available to be pulled up very quickly. The use of OLTP modules and the application of such software applications are most likely to be useful to lower level employees working in employees and ordinary consumers. Front line personnel who deal with customers directly are likely to find OLTP tools useful in responding quickly and efficiently to customer enquiries or concerns. It may also be useful for traders and investors and financial advisors who will be able to advise their clients on buying and selling of their stocks based upon the information they are able to quickly pull up using OLTP modules to gain fast and easy access to the most current data. Banking clerks and organizational sales people will also be benefited through OLTP modules because they are able to assist customers quickly and promptly by providing data on goods and services, balances in their account, charges associated with individual transactions, etc. OLTP transactions in general provide a more superficial level of information as compared to OLAP modules, which are discussed further below. These modules ensure fast access to data but they do not offer correlations or links between the data. Hence, such data is useful for individual transactions, or in enabling administrative personnel working in organizations to provide customers with the information they require in connection with specific transactions, such as a purchase or an enquiry. Hence, in general, OLTP tools may not be used by higher level staff in the organization such as managers and Directors; they are likely to relegate the functions requiring processing of individual transactions to the lower level employees or knowledge workers. The kind of knowledge workers who will be dealing with OLTP tools may thus be characterized as the knowledge workers with general skills rather than those who are highly skilled. These may not necessarily be the kind of employees who would command a high salary or be irreplaceable within an organization due to their ability to think through and discover solutions to complex problems. Rather, these are the kind of employees whose jobs can be transformed into routine standardized tasks that can be outsourced. OLTP tools allow organizations to ensure that many organizational functions pertaining to customer queries and sale transactions are carried out automatically and electronically. As opposed to Online Transaction Processing, Online Analytical Processing comprises the process of providing fast responses to technical queries rather than performing general transactions. Since data is a vital requirement in almost every organization, operational managers and employees are constantly engaged in the process of collection, manipulation and analysis of data in order to aid the decision making process on organizational goals and performance objectives.(www.databeacon.com). According to Pareek (2006), online analytical processing is a category of business intelligence, geared towards providing fast responses to multi dimensional queries and may include end uses such as data mining and relational reporting. Online Analytical processing is used by businesses in data mining operations to collect data and conduct analysis in areas such as preparation of business reports in sales and marketing, budgeting and forecasting as well as preparation of financial statements, management reporting as well as in business process management. This kind of processing allows users to mine data from multiple data sources that may not necessarily be compatible with each other and to combine and/or dissociate them at will.(Mailvaganam, 2007). Earlier OLAP software tools comprised applications such as Hyperion, Cognos, BusinessObjects and MicroStrategy, but several database vendors currently offer them with OLAP modules included, such as Analysis Services with Microsoft’s SQL Server 2000 and Express and Darwin with the Oracle database, while IBM offers the DB2 system that can handle OLAP applications. (Mailvaganam, 2007). Data storage is very important under OLAP systems, because long term data is mined and used as a basis on which to develop reports. The manner in which data is set up and data models prepared is different from OLTP systems, by using the star design, where data is aggregated into cubes that are interlinked, and thus used as the basis for networking of data from each unit. (Mailvaganam, 2007). OLAP tools are most useful for use by non-IT personnel such as operational managers, because they are able to examine large volumes of data from the perspective of how it applies to their organizational needs and in formulating decisions based upon this data.(www.databeacon.com). OLAP enquiries allow for complex, multi dimensional queries to be implemented rapidly within a short time span. As a result it is useful for sales and marketing managers in generating reports and projecting future sales and or/demand, or alternatively to prepare reports reflecting consumer trends, etc. This is also a useful tool for researchers, who are specifically involved in the business of data analysis, because it enables them to mine relevant data and to interlink it in order to examine and detect trends and patterns existing in the data. OLAP tools are this used by a different category of knowledge worker. These are the highly skilled individuals who need to think through their job, by developing solutions to specific problems. While OLTP tools are used by lower level knowledge workers who are not necessarily required to synthesize the data that is available to them from the OLTP databases or to detect underlying patterns in the data or derive conclusions from such data. But this is not the case with OLTP tools. Managers and higher level employees do not generate data merely to cater to the needs of an individual transaction and such data is not limited or restricted only to short term data. Rather, knowledge workers making use of OLAP tools are required to make use of data and to compile and assemble it. They are higher level employees who must use the longer term data as a basis to detect trends and patterns existing in the data. They are required to apply the data to their own organizations and generate projections and reports based upon conclusions they make on the basis of the data. Hence, OLAP tools are likely to be used only by highly skilled knowledge workers, for example, managers, writers, researchers and financial analysis for example. While OLTP tools may be used by a trader to provide basic information to a customer on the values at which stocks are trading in the market, OLAP tools will likely be used by a financial analyst, who would analyze past and current financial data available on the value of certain stocks, combined with information about the organization in question to generate a report forecasting the likely trends in the prices of that stock, based upon economic and other conditions existent in the pasta nd likely to exist in the future. This, there is an important distinction between those who use OLTP and OLAP tools. The former are lower level knowledge workers, mostly administrative staff, while the latter are likely to be skilled personnel who are placed much higher in the organization and paid much higher salaries. OLTP tools may be used by knowledge workers merely as a source of data, which is often transmitted in the same form in which it is received. OLAP tools, on the other hand, are likely to be used by knowledge workers with a much higher level of skills who are also required to use the data they acquire, think about it and process it further for the generation of reports. As a result, data is not presented in the form it is received, the final form the data may take would be processing into reports or analyses that also reflect the input of the knowledge worker and the conclusions they are able to draw from such data. Researchers for example, may make use of trends and patterns detected in the data to substantiate or refute existing theoretical models, while sales and marketing managers may process such data further to generate sales and marketing projections, which will form the basis for organizational decision making. Bibliography * Bernstein, Philip A and Newcomer, Eric, 1997. “Principles of Transaction Processing for the systems Professional”, Morgan Kaufman * Databeacon, 2004. “Why OLAP – An overview of online analytical Processing”, Retrieved October 20, 2008 from: http://www.databeacon.com/pdf/OLAP_White_Paper_2.0.pdf * Mailvaganam, Hari, 2007. “Slice, Dice and drill!” Data Warehousing Review, Retrieved October 20, 2008 from: http://www.dwreview.com/OLAP/Introduction_OLAP.html * Pareek, Deepak, 2006. “Business intelligence for telecommunications”, CRC Press. Read More