Data Warehousing - Essay Example

Introduction In the world today, many organizations are implementing advanced technologies that are aimed at improving the performance of the organizations. The importance of the technologies is to ensure that an organization achieves it goals and objectives within the stipulated period of time and in the appropriate manner. Data warehouses and business intelligence assists in transforming the raw data into information and knowledge that is essential for any decision making process. Part 1 Data warehousing refers to an area within a computer where data is stored in an organized and centralized way. It focuses on how well the data is stored for better analysis and reporting of information by the analysts. There are tools that are used to move the data into the storage area and the intelligence tools ensure there is efficiency in delivery of services to the customers. The high changing technology is important for an organization since it integrates data for easier analysis and data reporting. It also assists organizations to get more information about the business, assists companies to meet the business requirements, demands of the customer and eventually helps a company to be at a competitive advantage over their competitors ( SCN Education BV 2001). Most organizations gather their data from various sources such as; inventory management, online and sales services as the data has to go through the data Life cycle management so that it can be useful to the organization. The tools that are used in gathering the summarized data from various sources into the data warehouse are online analytical processing systems and the query tools. The tools are used in supporting adhoc analysis, inquiring and reporting of the data to the end-users without asking for assistance from the programmers while undertaking the required tasks in the appropriate manner (Witten & Frank 2000). Data warehousing Values. Data warehousing is easy to maintain and fast in generating reports. It is widely preferred because it doesn't require too much technical knowledge to control it hence any member of staff can use it comfortably. The data that runs through the server may take more transacting time than is required and to avoid such delays then organizations would rather use a server that takes acceptable time which is cheaper and uses separate servers and therefore a data warehouse becomes an important tool that would be used to solve such a problem. In business models it can be used to speed up the querying and reporting processes that are appropriate for the transaction process. For example the Star Scheme model is not very appropriate for the transaction process as it normally slows down the process. Another example is the bit-Mapped index model that may speed up the process of transaction but slows down the reporting and querying process therefore a data warehouse becomes appropriate because it doesn't not interfere with the process in any way. For organizations that need to manage and transact large volumes of data it is appropriate to use this database as it helps in capturing data from different multiple and external sources (McDonald et al. 2002). Challenges of warehousing Data warehousing is important to any business organization but it faces challenges which every organization should be made aware of. Data warehouses store very old and historical information that may not be very useful to the organization in the current business environment. The high technological changes and a very high competitive world are some of the things that could render such data obsolete .A company structure could also be continuously changing such that the data in the organizations database may not be useful and therefore the top management may loose interest in analyzing such data (McDonald et al. 2002). It could also be a very complicated process to a business because most organizations tend to institutionalize reports that are generated from these databases. If an organization does not have an organized and central way of dealing with the way it produces, transforms and loads data then the warehouse can easily become filled up with unnecessary information. Data warehousing is a major investment that an organization has invested in and the returns on this investment can take long before they are realized and most of the times organization may not even benefit from such an investment. Most of the organizations may just be storing data just for the sake of it and because data warehousing is a very complex system it therefore become very expensive for the business organization to maintain the system (McDonald et al. 2002). The process of producing, transforming and loading data so that it can be beneficial to its end user can be a very expensive affair. Cleaning up the data to the acceptable level of the user may be costly the organization in terms of time and the human resources required as most of the organizations may not have the relevant staff required and they have to keep on hiring professionals to do it for them ( Loshin 2003). Business Intelligence It refers to the skills, technologies, applications and the practices that are used in assisting a person in understanding the business environment in which to carry out their activities within the organizations. This process helps in ensuring that the competitive advantage of a business is increased through using intelligent data to enhance the decision making process within an organization. There are different kinds of stages that are followed in order to ensure that the operation is undertaken in the right manner: The stages include; data sourcing, data analysis, situation awareness, risk assessments and use of the decision support systems (Loshin 2003). Data sourcing stage is the stage that involves the extraction of information from different kinds of sources of data. The data may be in form of; memos, reports, electronic messages, photographs, images, sounds, formatted tables, web pages, and other related mediums. The facilities that are used to carry out this function involve; a scanner, digital cameras, database queries, web searches, computer file access systems and other relates sources of data (Loshin 2003). Data analysis is another stage followed in the business intelligence process that involves the synthesizing of knowledge that is useful for carrying out different tasks within an organization. The functions undertaken within this stage involves making estimates about current trends,intergrating and summarizing disparate information and validating of the different kinds of models in order to understand and make predictions of all missing information or the future trends within an organization. The analysis tools used within this system involves; probability theory that involves classification, clustering and using the Bayesian networks, statistical methods that involves the regression process and the operations research systems such as queuing and scheduling of information within an organization and finally using the artificial intelligence network that involves neural networks and fuzzy logic processes ( Loshin 2003). The situation awareness system involves the process of filtering all the irrelevant information and later on setting out information in the context of business and environment in which to carry out the activities. An analyst is supposed to identify the key factors that can enable a person to meet the basic needs and to summarize relevant data through using the market forces and government policy to ensure that the activity is carried out in the appropriate manner. This stage helps in ensuring that business context is understood in order to enhance proper decision making process within an organization. Decision support stage refers to the stage where there is provision of important take over's, market changes and staff performance so as to ensure preventive steps that may be taken to avoid problems from occurring within an organization. The process also involves analyzing and making business decisions and satisfying the needs of the customers as well as boosting the morale of the customers in order to ensure that the goals and objectives are carried out in the appropriate manner (Ian & Frank 2005). Data mining It refers to the process of ensuring data is stored in the appropriate manner through using electronic means and ensures the search process that is either automated and augmented by the computer is set up appropriately. This process helps in ensuring that data collected is stored the database in the right manner. It also ensures that data is in form that the customers can understand through preparing patterns that the customers can derive an economic advantage from through carrying out activities of the organization in the right manner. The importances of the patterns are that they assist in predicting new information that may be used within an organization. For example by using data mining techniques a company is able to predict what would happen to them if their customers are wooed by their competitors (Ian & Frank 2005). Techniques for data warehousing and mining There are many techniques that are available in data warehousing and mining but the major one include Kimball Bus Architecture and the Corporate Information factory. In the Kimball approach the raw data is transformed within the staging area. At this stage we have the data being derived from the sources .We also have the area of presentation that holds the data in a very standard way. A dimensional structure may also be created and the data is henceforth populated and it therefore becomes independent of other departments in the system. The Corporate Information factory allows data to be transformed and coordinated right from the source. The technique allows the system to hold data for each and every specific warehouse and later on allowing the data to be used for mining. While this data is designed for specific areas the summary of the data could be used in a very dimensional way (Khan 2003). The issues of data warehousing and data mining that are used for ensuring a business achieves business intelligence involves: The data warehousing component consists of infrastructural components that assist a person in achieving the goals and objectives that that they have set for themselves in order to enhance the growth and development of an organization. These components help in ensuring that decision making process takes place in the appropriate manner. It is therefore correct to say that data warehousing ensures business intelligence takes place in the appropriate manner. On the other hand business intelligence is composed of information that is derived from data mining analysis techniques thus there is a need to ensure that the data mining, data warehousing and business intelligence are incorporated together in order to enhance better delivery of services to the customers (Witten & Frank 2000). In case a data warehouse is not effective then it means that data cannot be effectively extracted that can enhance proper decision making process .Currently business are required to make decisions based on data that has been supplied to the customers at the appropriate time and place. Business intelligence within an organization can be achieved through studying the customers' attitude towards a product and identifying the business trends in order to achieve the goals and objectives of an organization (Witten & Frank 2000). Data mining refers to the business intelligence technologies that are used by analysts in ensuring that raw data is processed into more meaningful form that can enable an organization to predict on the future trend and outcome that may occur to an organization. It also assists in solving problems that may be eminent within an organization. The technique can be used to determine the number of items that may be sold within a specified period of time. Data mining techniques can be used to influence the building of models aimed at influencing the effectiveness of artificial intelligence within an organization. Data mining and data warehousing are interrelated in that the data warehousing ensures that data that is to be processes is in the right format and manner in order to enhance decision making that is beneficial for an organization (Ian & Frank 2005). Part 2 A narrative of SAP Business Information Warehouse for performing Business Intelligence The Systems Application and Products Data Processing (SAP) Business Information Warehouse helps an organization in achieving its goals and objectives through using data warehousing functions, business intelligence platforms and ensuring that there is a suite of business intelligence tools that can perform activities that are presented within an organization. It also assists in incorporating all data that has been extracted from the data warehouses so as to carry out analysis and interpretation of an organizations data in order to ensure that the decision making process takes place in the right and appropriate manner and within the time limits. It also assists in the integration, transformation, consolidation, clean up and the storage of data that may be required within an organization (McDonald et al. 2002). The main objective of business intelligence is to convert the data stored in an organization into information that can be useful to the organisation.It makes no sense for organizations to continue storing data which is not useful to it. Therefore the business intelligence tools are made to assist in converting the data into what is useful to the organization .The various stages followed in the business intelligence process ensures that the organization achieves its goals and objectives within the stipulated period of time. The implementation o f the Systems Application and Products Data Processing (SAP) tools together with the business intelligence tools assists an organization in achieving its goals and objectives thus enhancing decision making process to take place within a stipulated period of time (Loshin 2003). The features of Systems Application and Products Data Processing (SAP) The Systems Application and Products Data Processing (SAP) business information warehouse consists of the online analytical processing that enables an analyst to format the operative and historical data in the appropriate manner. Online analytical processing is a technological innovation that ensures that multi-dimensional analysis is undertaken as per the business perspectives. The architecture of the Systems Application and Products Data Processing (SAP) business information warehouse involves information modeling techniques, accessing, analyzing of personal and customer information as well as data management and scalability of data. It also assists in ensuring that the theoretical enterprise management is in order so as to meet the customers and individuals needs in the right manner (Martinez, Keogh, & Keogh 2005). The Business Explorer is a facility that is used in the Systems Application and Products Data Processing (SAP) that assists the customers in utilizing the multidimensional data access interface with ease. It also helps in building a personal catalog where the customers can report on the queries and reports that may require further clarification that may be displayed in data.SAP WB server consists of the OLAP and the metadata repository that enhance saving of time and money for building a data warehouse for storage of data that can be extremely expensive to maintain (Martinez, Keogh, & Keogh 2005). The advantages of using the Systems Application and Products data processing (SAP) business information warehouse The Systems Application and Products Data Processing (SAP) Business intelligence warehouse helps in ensuring that the business intelligence solutions are effectively implemented as compared to the data warehouse solutions. It also reduces the load time of data thus ensuring there is provision of data at the appropriate time on a timely basis so as to reduce the maintenance and overhead cost of running the operations of an organization. It is also used in improving a wide range of powerful reporting and analytical features that ensure that the exploration and interpretation of data takes place in the right manner (Martinez, Keogh, & Keogh 2005). The system is positioned in a manner that it can adapt to changes that may occur within the organization so as to ensure business processes and information technologies are performed in the right manner. An analyst can use the system in making decisions that are aimed at ensuring that growth and development within an organization takes place effectively (McDonald et al. 2002). The limitation of using Systems Application and Products Data Processing (SAP) Business Warehouse There may be redundancy while moving or storing of data since there are large volumes of data that should be sorted out in order to arrive at the right data that should be processed within a specified period of time. It also consists of underlying star schema that is attached to each cube that is limited to 16 dimensional out of which they are reserved for purposes of carrying out transactions within an organization. It is also costly to implement and to maintain the technologies used to run the operations of the organization since large amount of capital is needed to fulfill that obligation (McDonald et al. 2002). Conclusion It has been noted that organizations achieve their goals and objectives through using advanced technologies because they assist in ensuring that a firm achieves its goals and objectives within the stipulated period of time. Data warehouses are useful facilities that are used within the organization for storing data that may be used in future for enhancing decision making process to take place .Organization should also implement the data mining techniques so as to ensure predictions are made about the activities that should be undertaken within a stipulated period of time. The business information warehouse should be implemented within an organization so as to satisfy and define the kind of information that should be utilized within a specified period of time. It is important that organizations should store data in their warehouses if it is going to help the organizations make proper business decisions instead of cluttering the databases with unwanted information . References Ian H W, Frank E 2005, Data mining: practical machine learning tools and Techniques edition 2, revised, Morgan Kaufmann, New York. Hall, 2008, Accounting information systems, Cengage Learning EMEA, United States of America. 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Roze, CM, Isermann, R& Hashmi N 2003, SAP BW Certification: A Business Information Warehouse Study Guide, John Wiley and Sons, United States of America. SCN Education BV 2001, Data warehousing: the ultimate guide to building corporate Business intelligence, Birkhuser, United States of America. Witten, I H & Frank, E 2000, Data mining, Morgan-Kaufmann, New York. Read More