WEEK 4 INDIVIDUAL PAPER
OLAP, DATA MARTS AND WAREHOUSES,
THREE-TIER ARCHITECTURE AND ASP
DBM405
OLAP, Data Marts and Warehouses, Three-Tier Architecture and ASP
OLAP
The term OLAP stands for ‘On-Line Analytical Processing’. OLAP is a technology used to process data a high performance level for analysis and shared in a multidimensional cube of information. 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 one 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 ‘3 finger salute’ or ‘Alt+Ctrl+Delete’ 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 on-the-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 of 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 with 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 structural changes, non-procedural modeling, exception alerting, data mining and other application dependent features.
The OLAP system implements all the security requirements for confidentiality.
ETL is a three-step process which stands for Extract-Transform-Load. This process comprises of: extracting the desired data from a source, transforming the extracted data into a specific format, and loading the transformed data into a destination such as a data warehouse (Haag & Cummings, 2013). After the ETL process is performed, data-mining tools can be used to turn this data into useful information. For the first three questions, the database would need to capture each checkout price, how many items are purchased, the individual price of each item, and if the item is discounted or full MSRP. This specific data will likely originate from a customer oriented database that will then flow into the data warehouse for full ETL. For YTD profits, the database would need to capture all purchases, sales, profits, and expenses from the current year. Sport T’s company data will originate from an in-company database which focuses on business expenses and profits. In solving customer satisfaction, the KPIs to consider would be survey questions and answers from responding customers as well as customer opinion on what can be improved. For customer surveys, we will ask
Smith, W., & Jewett, D. (2009). Tableau software and teradata database the visual approach to the active data warehouse. In Retrieved from http://www.tableausoftware.com/learn/whitepapers
...g system that supports the scalability of their data. The following is their input on their new proposal to create a new operational insight tool in order to provide a solution to their challenge:
KEDA was founded in 1992, mainly into manufacturing of Ceramics Machinery. The other major offerings by Keda involved stone processing, building materials processing and energy resource management. They had more than 2000 employees and a broad product offering by 2010. In this industry, managing infrastructure for inventory was of extreme importance because of the various, customizable offerings across multiple plants. It had become a world leader in building materials machinery by early 2000s. All the units including sales & marketing, logistics, production & inventory was acting separately. Thus for a sustainable business, it was highly important to move from decentralization to a centralized system. For this purpose
Companies have transformed technology from a supporting tool into a strategic weapon. ”(Davenport, 2006) In business research, technology has become an essential means that many organizations use in their daily operations. According to the article, Analytics is a major technological tool used. It is described as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.
Almost all commercial database systems available today are designed to provide a high level of performance to its users. Nonetheless, Database Performance Tuning for large volumes of data is an arduous task. Even minor changes can bring about a substantial impact (positive or negative) on the performance of the system (KOCH, 2014).
Now days, companies are searching for new ways of gathering data so that they can get useful data in order to make well informed decisions regarding the market they are operating in. Google analytics is considered one of the best tools offers extensive amount of data to business owners for free. However, the success of business is highly depended on how well they can arrange data and customize their collected data corresponded to their business priorities. Google analytics provides beneficial information for companies regardless of their extent of operation.
A data warehouse comprised of disparate data sources enables the “single version of truth” through shared data repositories and standards and also provides access to the data that will expand frequency and depth of data analysis. Due to these reasons, data warehouse is the foundation for business intelligence.
The last decade can be marked as a period of significant changes in the business world. Being accustomed to utilize computers as a powerful tool with its office applications such as Microsoft Word and Excel. In the 1990s office workers first faced the opportunity to share information using the Internet (McNurlin, 2009). However, the situation became even more different with the transition to the third millennium. With a further development of information technologies, the majority of big enterprises had to reconstitute their business processes and to make the transition to the Internet economy. Enterprise resource planning (ERP), supply-chain management (SCM), customer relationship management (CRM) software and the variety of other information systems became essential components of the new economy. It can be expected, that all these complex solutions were designed to bring great benefits for different sides of the corporate activity, in particular, decisions made by top-managers are expected to become nearer to the ideal, customer service is to be improved and collaboration more prolific. Nevertheless, to ensure the desired results it should be taken into account that the key concept of these reorganizations is an information or a data, dealing with which can be a serious issue, and wide utilizing of the data warehouses in contemporary organizations confirms this fact.
Analytics means using data and performing statistical analysis on it, applying quantitative and predictive models, in order to arrive at a certain decision. Analytics can be the first step in a process or can rather be an intermediate step as well. Analysis can be done using different set of tools that are available in the market or it can done manually using different concept and formulas. Business intelligence firms like Cognos, SAS and BusinessObjects have developed different tools that are readily available in market that assist in analysis and decision making. Analytics is used in order to find solutions to the problems and the solutions provided enables us to be successful and in the business world allow us to compete with our contenders.
Some faculties and departments are already using Oracle applications in their day-to-day operations. As time goes by, more and more information users will be working with an application based on Oracle database technology. If you get the opportunity to be a member of an application development team, you will become familiar with the workings of Oracle and relational databases. Other users may have to learn about this popular database management system through their own experience. This article is for our readers who, as of yet, have no access to Oracle databases but have a yearning for learning what they're all about.
Prior to the start of the Information Age in the late 20th century, businesses had to collect data from non-automated sources. Businesses then lacked the computing resources necessary to properly analyze the data, and as a result, companies often made business d...
Enterprise architecture can be used in a diverse number of ways. It can be used to describe a certain business practice in an organization and the aspects or elements of that specific business practice under description. The environment under which companies or business organizations operate in is always in constant change. This means that the managers should always introduce new enterprise solutions, which can directly contribute to the linkage to the measures of improvement of business practices.
What's e-business? It is the transformation of every business process through using the internet and associated technologies. In this transformation, each part of the business becomes a part of an intrinsic network, which enables employees, suppliers and customers of a given enterprise to conduct their tasks. People usually try to make a point in differing e-business from e-commence, but as I see, e-commerce is a part of the e-business category, and an important one.
The Database Management System (DBMS) is software that enables the users to define, create, maintain and control the access to the database. It is a software that interact with the user’s applications programs and it database. Meanwhile, information retrieval system is a system that involved the activity that the systems obtain the information. The obtaining information action need the information from it resources.