...understanding about Data Warehousing and how to apply this in emerging fields of big data and online data storage management. Data Warehousing Data Warehousing is more concerned with database administration in a computer based environment. Data Warehousing which is also known as enterprise data warehousing (EDW) is an efficient system to keep the inventory of data pertaining to different aspects of the organization which is ultimately use for reporting and data analysis. Data Warehousing is treated as the core component of business intelligence. It is the main repositories of integrated data from different departments of an organization or different sources (i.e. suppliers,...
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...Discussion Question: 1. When developing a successful data warehouse, what are the most important risks and issues to consider and potentially avoid? Data warehouse projects have many risks. Most of them are also found in other IT projects, but data warehousing risks are more serious because data warehouses are expensive, time-and-resource demanding, large-scale projects. Each risk should be assessed at the inception of the project. When developing a successful data warehouse, it is important to carefully consider various risks and avoid the following issues: • Starting with the wrong sponsorship chain. You need an executive sponsor who has influence over the necessary resources to support and invest in the data warehouse. You also need an executive project driver, someone who has earned the respect of other executives, has a healthy skepticism about technology, and is decisive but flexible. You also need an IS/IT manager to head up the project. • Setting expectations that you cannot meet. You do not want to frustrate executives at the moment of truth. Every data warehousing project has two phases: Phase 1 is the selling phase, in which you internally market the project by selling the benefits to those who have access to needed resources. Phase 2 is the struggle to meet the expectations described in Phase 1. For a mere $1 to $7 million, hopefully, you can deliver. • Engaging in politically naive behavior. Do not simply state that a data warehouse will help managers make better decisions...
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...Data Mining/Data Warehousing Matthew P Bartman Strayer University Ibrahim Elhag CIS 111– Intro to Relational Database Management June 9, 2013 Data Mining/Data Warehousing When it comes to technology especially in terms of storing data there are two ways that it can be done and that is through data mining and data warehousing. With each type of storage there are trends and benefits. In terms of data warehousing there are 5 key benefits one of them being that it enhance business intelligence. What this means is that business processes can be applied directly instead of things having to be done with limited information or on gut instinct. Another benefit of data warehousing is that it can also save time meaning that if a decision has to be made the data can be retrieved quickly instead of having to find data from multiple sources. Not only does data warehousing enhance business intelligence and save time but it can also enchance data quality and consistency.This is accomplished by converting all data into one common format and will make it consistent with all departments which ensures accuracy with the data as well. While these key benefits another one is that it can provide historical intelligence which means that analayze different time periods and trends to make future predictions. One other key benefit is that it provides a great return on investment. The reason being that a data warehouse generates more revenue...
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...According to Lee, the most popular definition is a data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process (2014). Basically a data warehouse is a copy of transaction data specifically structured for query and analysis. According to Frand, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information – information that can be used to increase revenue, cut costs, or both (1997). There are many benefits of data warehousing. Yes, it will cost large amounts of money from businesses to have a data warehouse but, in the long run it is worth it to have in a corporation. One benefit is that data warehouses stores and presents information in a way that allows management to make important decisions (Prathap, 2014). Management and even executives can look at the business as a whole instead of by each department. According to Prathap, another benefit of data warehouses is their ability to handle server tasks connected to querying which is not used in most transaction systems (2014). Creating queries and reports can take time and with data warehousing, the server can handle the tasks in a timely fashion. Again, according to Prathap, one of the most important benefits of data warehouses is that they set the stage for an environment where a small amount of technical knowledge about databases...
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...Importance of Data Warehousing Brenda L Bach The Digital Firm and Business Communications/BU 204-8A November 15, 2014 Ron Rosalik Kenneth and Jane Laudon state that a data warehouse is a database that stores current and historical data that can be of potential interest to decision makers throughout the corporation (Laudon, 2011. p.225). They go on to explain that the data can originate from many core operational transaction systems and could include data from Web site transactions (Laudon, 2011 p.225). Data warehouse extract current along with historical data from all operational systems within an organization. The data warehouse makes the data it collects and stores available to anyone and can be accessed and viewed as needed but cannot be altered in any manner. These data warehouses also provide a large range of ad hoc as well as analytical tools and graphical reports that represent the data. Companies often build enterprise data warehouses and either uses a central data warehouse or a smaller decentralized warehouse called a data mart to preserve the data they collect through its many sources. A data mart is a subset of a data warehouse that summarizes on a highly focused portion of the organization’s data and is placed within a separate data based for a very specific population of users. For example, a car dealer that deals with car sales as well as service may use a data mart to develop marketing and sales data that are specifically focused on the data of the customer...
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...com/product/cis-499-project-deliverable-3/ Contact us at: SUPPORT@ACTIVITYMODE.COM PROJECT DELIVERABLE 3: DATABASE AND DATA WAREHOUSING DESIGN This assignment consists of two (2) sections: a design document and a revised project plan. You must submit both sections as separate files for the completion of this assignment. Label each file name according to the section of the assignment it is written for. Additionally, you may create and / or assume all necessary assumptions needed for the completion of this assignment. One of the main functions of any business is to be able to use data to leverage a strategic competitive advantage. This feat hinges upon a company’s ability to transform data into quality information. The use of relational databases is a necessity for contemporary organizations; however, data warehousing has become a strategic priority due to the enormous amounts of data that must be analyzed along with the varying sources from which data comes. Since you are now the CIO of a data-collection company which gathers data by using Web analytics and operational systems, you must design a solution overview that incorporates data warehousing. The executive team needs to be clear about what data warehousing can provide the company. Section 1: Design Document 1.Write a four to six (4-6) page design document in which you: ◦Support the need for data warehousing within your company and elaborate on the best practices that the company will adhere to. ◦Create a schema that supports...
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...Data warehousing is a fairly new but not so new development in the information systems field. Data warehousing can be traced back being in existence since the 1980’s when Teradata in 1983 introduced a database management system (DBMS) designed for decision support systems (Ponniah, 2010). The influence from the two Irish IBM architects Barry Devlin and Paul Murphy who in 1988 laid the foundations for what we call today a data warehouse in their original article “An Architecture for a Business and Information Systems” (Bouman & van Dongen, 2009). It was not long after that Bill Inmon, referred to as the father of data warehousing authored one of the most influential decision support books “Building the Data Warehouse” in 1991(Ponniah, 2010). Since then Prism Solutions in 1991 introduced the Prism Warehouse Manager software for developing data warehouses. The Data Warehousing Institute was also founded 1995 and has and continues to promote data warehousing by way of serving as the leading voice in the business world providing education, research, and support (Ponniah, 2010). With the business environment being more global, competitive, multifaceted and unpredictable there is a need for systems that would satisfy emerging business needs and new technological advances (Wixom & Watson, 2001). The enterprise for enhanced customer relations and e-commerce alone these days require large integrated repositories and advanced analytical repositories (Wixom & Watson, 2001). Data warehousing...
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...Airlines Real- time data warehousing works with Continental's strategies and plans through providing the best service possible to its customers. Continental had the goal of getting people to their destinations on time and with everything that they were traveling with. Real-time data warehousing helps to track the flight information, connection information, and passenger information in order for the company to be effective and for the passenger to have an enjoyable flight. With the fast paced environment of society and businesses today, the real-time data warehouse is the most efficient method of information travel for the company to use. At the click of a few keys, anyone with access is able to find information about connecting flights, passenger information and also problems that the passenger might run into with their flights. The real-time data warehousing was able to address the problems with airline reservations and connection people to other airlines for flight transfers, this makes things easier so the airline is able to see where each customer is going and the service that they need to provide to that customer to get them to their location on time with the least amount of glitches as possible. This feature also tracks passenger information such as all of their demographics and also tracks any disturbances that they might have had on a flight before so that the airline can work to avoid anything in the future. Another feature that the data warehouse offers is...
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...Week 2 Assignment Kaplan University 12/12/11 Part A What are the primary reasons for changing the current systems? Butler University’s IT department provides and is responsible for technologies in the areas of network and systems, administrative, computing, web applications, instructional technologies among others. Staying on top of new innovative technological offerings is key to the success of how the university operates and conducts their day to day business. As stated in the case study readings, “many of the administrative users are displeased with outdated Centex and Centigram capabilities, although they lauded the communication systems high reliability. (Brown, 179) There was also one major problem with Butler’s current communication system. They were unable to communicate to the entire campus via the current system; in the event of an emergency it would be almost impossible to disseminate emergency information. The overall reason for this change is to improve communication by leveraging newer technologies. What role did Butler’s IS department play? Butler’s IS department will be very instrumental during this process. The IS team will first have to assist with the initial assessment of the current systems to identify the requirements for the new systems. Once the requirements are identified the IS department will also help to identify the right systems that will be acquired to replace Butlers current system. During the...
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...middleware, and industry standards as relating to the enterprise data repository. Data warehousing, data mining, and data marts are covered from an enterprise perspective. Policies Faculty and students will be held responsible for understanding and adhering to all policies contained within the following two documents: • • University policies: You must be logged into the student website to view this document. Instructor policies: This document is posted in the Course Materials forum. University policies are subject to change. Be sure to read the policies at the beginning of each class. Policies may be slightly different depending on the modality in which you attend class. If you have recently changed modalities, read the policies governing your current class modality. Course Materials Coronel, C., Morris, S., & Rob, P. (2011). Database systems: Design, implementation and management (9th ed.). Mason, OH: Cengage Learning. Eckerson, W. W. (2011). Performance dashboards: Measuring, monitoring, and managing your business (2nd ed.). Hoboken, NJ: John Wiley & Sons, Inc. Hoffer, J. A., Ramesh, V., & Topi, H. (2011). Modern database management (10th ed.). Upper Saddle River, NJ: Pearson. Linoff, G. S., & Berry, M. J. A. (2011). Data mining techniques: For marketing, sales, and customer relationship management (3rd ed.). Indianapolis, IN: Wiley Publishing, Inc. Ponniah, P. (2010). Data warehousing: Fundamentals for IT professionals (2nd ed.). Hoboken, NJ: John Wiley ...
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...Data Warehouses The basic reasons organizations implement data warehouses are: To perform server/disk bound tasks associated with querying and reporting on servers/disks not used by transaction processing systems most firms want to set up transaction processing systems so there is a high probability that transactions will be completed in what is judged to be an acceptable amount of time. Reports and queries, which can require a much greater range of limited server/disk resources than transaction processing, run on the servers/disks used by transaction processing systems can lower the probability that transactions complete in an acceptable amount of time. Or, running queries and reports, with their variable resource requirements, on the servers/disks used by transaction processing systems can make it quite complex to manage servers/disks so there is a high enough probability that acceptable response time can be achieved. Firms therefore may find that the least expensive and/or most organizationally expeditious way to obtain high probability of acceptable transaction processing response time is to implement a data warehousing architecture that uses separate servers/disks for some querying and reporting. To use data models and/or server technologies that speed up querying and reporting and that are not appropriate for transaction processing There are ways of modeling data that usually speed up querying and reporting (e.g., a star schema) and may not be appropriate for transaction...
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...Research Proposal Modernizing a data warehouse for business advantage Introduction Ten years ago, Data Warehousing was largely unknown. Today most organizations relay on effective warehousing concepts to analyse data in efforts to predict future trends and assist in decision making. In this increasingly competitive business environment Data Warehousing is one of the most important developments in recent Information Systems. There is a large need to acquire data, anywhere at any time, thus there is a need for a development that can facilitate data from different sources with different formats. What is Data Warehouse? “Data warehouse is the hottest tool in information systems” (W.H. Inoman, 2002). A data warehouse is capable of organizing...
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...Data warehousing: what is it, why do we want to do it, how is it done? How do data warehouses compare with operational databases? What do we want to consider when doing so, and what are our options in terms of implementation? In this article, I discuss data warehouses: what they are, how they compare to operational databases, and how they are designed, implemented and maintained. An operational database is one which is used by the enterprise to run its day to day operations. They are created to support fast transaction processing, with frequent updates. Speed is key to operational databases. They typically are used by clerical staff, and are on the order of megabytes of data to gigabytes. Database consistency is very important to operational databases, and consistency checks and constraints are rigidly enforced. They contain the most current set of data applicable to running enterprise operations. These are our sales and inventory databases. A data warehouse differs from this in many ways. They are used by management for making decisions, watching trends, and running reports. They are typically used offline, have few users and are very large: gigabytes to terabytes. They contain historical data, are read only, and are added to but rarely or never updated (the rows in the database are not changed, I mean). The data in the data warehouse is time sensitive – each row is the warehouse is timestamped so that trending of data versus time can be done. The kinds...
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...roles. Are these the right roles? What roles in particular should be modified? How might such role modifications be accomplished? 2. Focus on the role of the software vendor- Unitrak Software Corporation. Was it an appropriate role? Did Unitrak act responsibly? 3. How much is Kovecki to blame for this situation? 4. One of the recurring themes of this book is the importance of information systems politics. To what extent does IS politics explain the situation that has developed at the Midsouth Chamber of Commerce? 5. The case involves what appears to be a fairly routine use of information technology to support a service organization. Yet the Midsouth Chamber of Commerce encountered major problems in bringing up its new system. Is there a lesson here for organizations seeking to adopt new information technology? What is it? 6. What should Lassiter do now? Case Study 11-1- Vendor-Managed Inventory at NIBCO 1. What was the catalyst for NIBCO to develop a VMI program, and why was it able to respond? 2. Describe what types of transactions are involved in NIBCO's VMI program. 3. What types of benefits have been attributed to the VMI initiative-for both NIBCO and NIBCO's customers? 4. What new initiatives would you recommend that NIBCO pursue next to continue to take advantage of its current IT capabilities? Case Study 11-2- Real-Time Business Intelligence at Continental Airlines 1. Describe "active" data warehousing as it is applied at Continental...
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...Data Warehousing Methodologies Using a common set of attributes to determine which methodology to use in a particular data warehousing project. DATA INTEGRATION TECHNOLOGIES have experienced explosive growth in the last few years, and data warehousing has played a major role in the integration process. A data warehouse is a subjectoriented, integrated, time-variant, and nonvolatile collection of data that supports managerial decision making [4]. Data warehousing has been cited as the highest-priority post-millennium project of more than half of IT executives. A large number of data warehousing methodologies and tools are available to support the growing market. However, with so many methodologies to choose from, a major concern for many firms is which one to employ in a given data warehousing project. In this article, we review and compare several prominent data warehousing methodologies based on a common set of attributes. Online transaction processing (OLTP) systems are useful for addressing the operational data needs of a firm. However, they are not well suited for supporting decision-support queries or business questions that managers typically need to address. Such questions involve analytics including aggregation, drilldown, and slicing/dicing of data, which are best supported by online analytical processing (OLAP) systems. Data warehouses support OLAP applications by storing and maintaining data in multidimensional format. Data in an OLAP warehouse is extracted and loaded...
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