...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 processing because the modeling technique will slow down and complicate transaction processing. Also, there are server technologies that that may speed up query and reporting processing but may slow down transaction processing (e.g., bit-mapped indexing) and server technologies that may speed up transaction processing but slow down query and report processing (e.g., technology for...
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...Healthcare Data Warehousing Doug Kelley Health Informatics I Professor Lu December 7, 2012 Abstract ` Dimensional modeling lays the groundwork for data warehouses. Dimensional modeling is a similar process to traditional Entity/Relationship modeling in regards to tables (entities) having joins (relationships) with other tables via primary keys. Dimensional modeling has been used as a standard in industry for decision support systems in other areas such as transportation, production, sales and marketing. (Parmanto, 1) Because healthcare has many complex events, it has lagged behind other industries in terms of data warehousing. This paper will discuss several techniques that can help overcome these complexities. Introduction A data warehouse has been defined as a database optimized for long-term storage, retrieval, and analysis of records aggregated across patient populations, often serving the longer-term business and clinical analysis needs of an organization (Shortliffe, 932). For a data warehouse to perform these roles, it must be architected or modeled appropriately. There are a couple of different approaches to modeling data warehouses. Dimensional modeling is becoming standard approach. Background Review Designing a data warehouse for healthcare presents many unique challenges for designing a database. These include such complexities as multiple diagnoses, multiple payers, multiple physicians; primary and secondary, and late arriving data, such...
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...The 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...
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...Solved Questions |1 |Distinguish between warehouses and distribution centers. | | | | | |Warehouses emphasize the storage of products and their primary purpose is to maximize the use of storage space. In | | |contrast, distribution centers emphasize the rapid movement of products through a facility and thus attempt to maximize| | |throughput (the amount of product entering and leaving a facility in a given time period). | |2 |Explain the four ways that warehousing facilitates the regrouping function. | | | | | |Regrouping involves rearranging the quantities of products as they move through the supply chain and it takes four | | |forms: accumulating (also referred to as bulk-making), allocating (also referred to as bulk-breaking), assorting, and | | |sorting. | | |Accumulating involves bringing together similar stocks from different sources, while allocating involves breaking ...
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...Warehousing plays a vital part in a logistics system. In the past, we always thought that warehouse is used for storage of inventories. In today’s quick response, the growth of warehouse not only serves for storage, but also for movement, information transfer and valued added services. A good warehouse space and layout planning is a primary element for efficient warehouse. Tompkins and Harmelink (2004, p.240) state the purposes of warehouse layout are space usage efficiency; allowing for efficient material handling; cost efficiency; maximum flexibility and good housekeeping. Successful warehouse layout could maximize space utilization, minimize and control movement and location, and provide safety and security environment. The first step in warehouse layout planning is to consider the space requirement. Tompkins et al. (1996, p.430) state space conservation, space limitations, accessibility and orderliness are some factors on designing layout. In layout planning, as space will be limited by floor loads, truss, the height of ceiling, etc, it should be maximized utilization of concentration and cube and also minimized honeycombing. To optimize space utilization, it is not only developed by horizontally but also by vertically. Space concentration and cube utilization can benefit for the flexibility and ability for bulky receipts such as higher and thicker materials. Tompkins and Smiths (1998, p.243) describe honeycombing is storage space losing due to improper use of storage...
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...Warehousing plays a vital part in a logistics system. In the past, we always thought that warehouse is used for storage of inventories. In today’s quick response, the growth of warehouse not only serves for storage, but also for movement, information transfer and valued added services. A good warehouse space and layout planning is a primary element for efficient warehouse. Tompkins and Harmelink (2004, p.240) state the purposes of warehouse layout are space usage efficiency; allowing for efficient material handling; cost efficiency; maximum flexibility and good housekeeping. Successful warehouse layout could maximize space utilization, minimize and control movement and location, and provide safety and security environment. The first step in warehouse layout planning is to consider the space requirement. Tompkins et al. (1996, p.430) state space conservation, space limitations, accessibility and orderliness are some factors on designing layout. In layout planning, as space will be limited by floor loads, truss, the height of ceiling, etc, it should be maximized utilization of concentration and cube and also minimized honeycombing. To optimize space utilization, it is not only developed by horizontally but also by vertically. Space concentration and cube utilization can benefit for the flexibility and ability for bulky receipts such as higher and thicker materials. Tompkins and Smiths (1998, p.243) describe honeycombing is storage space losing due to improper use of storage capacity...
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...McDonald’s India Behind the golden arches – Building a robust supply chain Some facts about who we are… • International – First restaurant opened in 1955 in Des Plaines, Illinois USA – Single largest Food Service Retailer in the world – Serves around 50 million customers every day – Around than 30,000 Restaurants worldwide across 120+ countries • India – Started in 1996 – Currently present in around 40 cities with around 180 restaurants – Serves around 500,000 customers daily – Unique menu with Vegetarian products and Nonvegetarian products (Fish, Chicken) …World’s largest democracy … 2nd largest population in the world …fastest growing middle class consumers Incredible India A land of huge opportunities • At 175 million tonnes per annum, India is the second largest producer of fruits and vegetables ……but more than 15 billion US$ worth fruits and vegetables wasted every year post harvest …. only 2.2% of the produce is processed 3rd largest producer of potatoes …..but less than 5% of potatoes grown are process grade • • World’s largest producer of milk …however yield per lactation cycle of a buffalo is 1/10th of US Supply Chain Challenges Agriculture •Outdated farming and irrigation practices Logistics & Distribution •Poor road and other infrastructure conditions •Cold chain – virtually non-existent •Huge wastage of natural resources (water, electricity etc.) •Lack of proper storage facility at farm level for storing post harvest produce •Crops like iceberg lettuce...
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...op Consumer Durable Companies in India Advertisements India’s Consumer Durable industry is dominated by some of the top players like Voltas, Kelvinator, Allwyn and Godrej, but after liberalization many foreign companies has also entered the consumer durable industry in India. Some of the major category of good coming under consumer durable industry is washing machines, air-conditioners, refrigerators and CTVs. Some of the top players presently dominating the consumer durable industry in India are: Top players in consumer durable industry: • Nokia India • LG Electronics India Limited • Philips India • Titan Industries • Samsung India Electronics • Whirlpool Appliances • Siemens • Sony India • Videocon Industries • Blue Star Some of the details regarding these top players in the consumer durable industry in India is given below: Nokia India: Nokia India is a world leader in mobile phone industry and they have built a diverse product portfolio with a view to meet the mobile phone requirement of different types of consumer. Their product ranges from an entry-level mobile phone to an advance mobile phones with several applications and multimedia facilities like gaming, music and imaging. LG Electronics India Limited: LG Electronics India Limited came into existence in the year 1997 and they have manufacturing units at Pune, Delhi and greater Noida for manufacture of consumer durable goods like televisions, IT products, vacuum cleaners...
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...Warehouse function Historically warehouses were a dominant part of the urban landscape used from the start of the Industrial Revolution through the 19th century and into the twentieth century: the building remained when their original usage had changed. There are four identifiable types of warehouses. The cotton industry was co-terminus with the development of the warehouse, and all five types were represented in Manchester, United Kingdom. Warehouses in Manchester were often lavishly decorated juxtaposing with the modern view of warehouses which are assumed to be standard industrial buildings. Display of Goods for Sale These displayed goods for the home trade. This would be finished goods- such as the latest cotton blouses or fashion items. There street frontage was impressive, so they took the styles of Italianate Palazzos. Richard Cobden's construction in Mosley Street was the first palazzo warehouse. There were already seven warehouses on Portland Street when they commenced building the elaborate Watts Warehouse of 1855, but four more were opened before it was finished. It was this type of warehouse that inspired the Germans in Duesseldorf and Muenchen to name their prestigious departmental stores, 'Warenhausen'. Overseas Warehouses These catered for the overseas trade. They became the meeting places for overseas wholesale buyers where printed and plain could be discussed and ordered. Trade in cloth in Manchester was conducted by many nationalities. Behrens Warehouse...
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...Data Warehousing Saikrishna Burugula IST 7000 Data Management Wilmington University Abstract A data storage could be a subject-oriented, integrated, time-variant, non-updateable assortment of knowledge utilized in business intelligence and support of organizing decision-making method (Inmon, Strauss & Neushloss, 2008). In data warehousing when the data is stored it is not updated, commonly data warehousing intended for evaluation connected with data source in addition to addressing queries it can be called copy of addressing data (Prabhu, 2002). The key intention with this paper is typically to target on the actual design connected with data warehouse in addition to modeling techniques like ER modeling and Dimensional modeling. Introduction A Data Warehouse is not just a new combination of all of the in business databases in an organization. Because of its attention on business intelligence, exterior data, and time variant information, a data warehouse is usually a special type of database. The good thing is, you should not learn another number of database abilities to do business with a new information storage place. Most data warehouses tend to be relational databases designed in many ways optimized pertaining to selection assistance, definitely not in business information running. Facts warehousing could be the procedure whereby organizations create and gaze after information...
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...head: SHORT TITLE OF PAPER (<= 50 CHARACTERS) Data Warehousing and Data Mining Bruce Nimo CIS 111 March 19, 2012. Prof Jones Data mining is a process of numerical analysis. Analysts use technical tools to query and sort through terabytes of data looking for patterns. Usually, the analyst will develop a hypothesis, such as customers who buy product X usually buy product Y within six months. Running a query on the relevant data to prove or disprove this theory is data mining. Data warehousing describes the process of designing how the data is stored in order to improve reporting and analysis. Data warehouse experts consider that the various stores of data are connected and related to each other conceptually as well as physically. A business's data is usually stored across a number of databases. However, to be able to analyze the broadest range of data, each of these databases needs to be connected in some way. This means that the data within them need a way of being related to other relevant data and that the physical databases themselves have a connection so their data can be looked at together for reporting purposes. Businesses then use this information to make better business decisions based on how they understand their customers' and suppliers' behaviors. Examples of businesses that use data warehousing and data mining are amason.com, Wal-Mart stores Inc etc. Both data mining and data warehousing are business intelligence tools that are used to turn information...
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...Coffing Data Warehousing Education Outline 02/17/05 TERADATA EDUCATION OUTLINE Coffing Data Warehousing has provided quality Teradata education, products and services for over a decade. We offer customized solutions to maximize your warehouse. Toll Free: 1-877-TERADAT Business Phone: 1-937-855-4838 Email: mailto:CDWSales@CoffingDW.com Website: http://www.CoffingDW.com In addition to the course material listed in this outline, we also offer Teradata classes in Teradata Basics, Implementation, SQL, Database Administration, Design and Utilities. Please contact us so we can customize a course to fit your specific needs. © 2006 Coffing Data Warehousing – All rights reserved. Confidential. 1 Coffing Data Warehousing Education Outline 02/17/05 PURPOSE Coffing Data Warehousing has been providing quality Teradata education for over a decade. We offer customized courses to maximize the effectiveness of each class. The purpose of this proposal is to build a lasting relationship with your company. To this end, we have combined our comprehensive Teradata education services in a unique package that we feel best suits the diverse needs of your company while offering our high quality product at competitive pricing. Coffing Data Warehousing is excited to offer you, our preferred partner, an innovative new way to look at training at the CoffingDW Teradata University (CDW-TU). This approach provides the ability to maximize learning potential. Our goal is to make your employees...
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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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...Future of Warehouse Design being shaped by Warehouse Science The current scenario of Indian warehousing design is optimistic as it is fast picking up the western practices and technology. However there is still a wide disparity across the whole of India. Some warehouses which are owned by rich MNCs are of high standards, on the other hand, there are also many warehouses which are of low standards. Many warehouses in India are constrained by small spaces. Unlike large warehouses owned by MNCs in the USA and Europe have area of 250,000 to 1-million-square-feet, generally the large of warehouses in India are quite small in comparison, between 5,000 and 25,000 square feet. This is due to less demand, expensive land at the outskirts of a major city in India and difficulty to acquire large piece of lands due to many owners of a small pieces of land. In addition, the demand for storage of products is much lesser than compared to western countries. The warehouse structures are not properly Inefficient space utilisation is also a huge problem as many warehouses in India don’t have proper shelving system and the floors are dirty because it is not cemented. In addition, considerable number of warehouses lack the basic semi-automated equipment such as MHEs, conveyors, dock levellers, for movement of goods inside the warehouse. Fully - automated machines and systems are very rare to be found in India. Automatic sorting and automatic packaging systems (which include pouching, carton...
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...Data Warehousing Essay, Research Paper Contents 1. Introduction 2. What is a data warehouse 3. Past, Present and Future 4. Data Warehouses and Business Organisations 5. Conclusion 6. Bibliography 1.0 Introduction In recent years, data warehousing has emerged as the primary method of analysing sales and marketing data for a competitive advantage. As the number of knowledge workers using the data warehouse/data mart grows and the amount of data increases daily, performance problems have become a major concern of both the Information Systems staff and the users. Many options have been tried in an attempt to solve the performance problems – from bigger hardware to different software or database tuning and redesign using star schemas or snowflake data structures. However, all have limitations – either in functionality or in terms of cost – and their strengths are almost inevitably outstripped by users’ demands. During the past three years, data warehousing has emerged as one of the hottest trends in information technology for corporations seeking to utilise the massive amounts of data they are accumulating. Managers from all business disciplines want enterprise wide information access, as well as the ability to manipulate and analyse information that the company has gathered for a single purpose, to make more intelligent business decisions. Whether to increase customer value, identify new markets or improve the management of the firm’s assets, the data warehouse...
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