... Creating a Data Warehouse Introduction Data warehouses are the latest buzz in the business world. Not only are they used to store data for reporting and forecasting, but they are part of a decision support system. There are many reasons for creating and using a data warehouse. The data warehouse will support the decisions a business needs to make, usually on a daily basis. The data warehouse collects data, consolidates the data for reporting purposes. Data warehouses are accompanied by analytical tools that accommodate forecasting as part of the decision support system. The purpose of this paper is to explore the creation of a data warehouse. Since the specifics of creating the data warehouse are determined by the database system, this paper will devote its discussion to the design or layout of the data warehouse. Before discussion of the layout of the data ware house proceeds, the basics about a data warehouse need to be discussed. Then the elements of the data ware house will be covered. What is a Data Warehouse? A data warehouse is a warehouse full of data, an electronic warehouse. In a manner of speaking this is true. Don Awalt describes it as follows, “A data warehouse is the cohesive data model that defines the central data repository for an organization. “ He also further stated that “we consider it a complete, integrated data model of the enterprise, regardless of how of where the data is stored.” Thus we can see that the data warehouse collects and stores...
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...Mining the Data Warehouse Summary In “Mining the Data Warehouse”, It speaks of a survey done by Merrill Lynch back in 2006. It tells us that “business intelligence software and data-mining tools were at the top of CIOs’ technology spending list” (Baltzan, Hag, Phillips 87). It gives a few examples of how companies are using the software and tools to gain very valuable information. When Ben & Jerry’s is mentioned, people know the brand and immediately think of ice cream. “Ben & Jerry’s cuts through the din by using integrated query, reporting, and online analytical processing technology from BI software vendor Business Objectives” (Baltzan, Hag, Phillips 87). They use the technology to track each pint’s ingredients throughout its life. If there is a complaint made by a customer, they will track it back through ingredients, suppliers, or whatever caused the issue. They are extremely focused on quality of their products. “The BI tools let Ben & Jerry’s officials access, analyze, and act on customer information collected by the sales, finance, purchasing, and quality-assurance departments” (Baltzan, Hag, Phillis 87). They have gotten it down to a science. They can tell you what milk a customer prefers for the ice cream. In 2005, they tracked over 12,500 customer’s information and comments. The California Pizza Kitchen has 130 casual dining full-service restaurants throughout the many states and other countries. They are known for their premium pizza. People...
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...DIFFERENCE BETWEEN DATABASE AND DATA WAREHOUSE 1 Database vs Data Warehouse Patricta Eric Doller Prudue University Relation Database Management Systems Bob Estein March 14, 2015 DIFFERENCES BETWEEN DATABASE AND DATA WAREHOUSE Relational database versus a data warehouse Businesses use new technology in many aspect of running everyday duties, like record keeping. To keep these records organized, companies have separate database and data warehouses. A database is used for a single application, mostly for transactions. These transactions can range from payroll, inventory to sales and any other transaction the company needs on a daily bases. A data warehouse is used for multiple domains running simultaneously. A company should use a data warehouse to show how they are doing, in whole, rather than just in certain areas. The warehouse can also track business trends. Companies do not usually do not put all their information into one database because of the possibility of being hacked into easily by a Hacker and used for the wrong intent. Although, it 2 would be cheaper to have just one database the security risks are too high. These problems would lead to dissatisfied customers, lack of business and lawsuits. So how is a data warehouse different from your regular database? After all, both of these are database, and they tend to function the same way. If you look deeper into them, you will find that they both have tables and they contain data. They both have indexes, keys...
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...how can data warehousing, data mining & predictive analytics improve a business. Would it be applicable to all types of business or a particular business only? Information Technology develops rapidly, because changes in these technologies are making the people’s lives easier. There’s a growing need for information in market and the competition of handling information. Some businesses needs to improve their ability and capability to handle big data or information. Data warehousing evolved and plays a big or essential role in the storage, information management and to support strategic reporting and analytics of companies. Businesses are investing to integrate their daily operations to be contained in their data warehouse. Businesses aims for a growth to their competitive advantage compared to other organizations. Some of these competitive advantages includes data warehousing, data mining and predictive analytics to be applied with effective use of Information Technology. Data warehouse is designed to support decision making for leaders or owners of an organization. Data warehouse is truly important for which it gives or share all data by every department of an organization that allows decision making in order to achieve good analysis which will help better the organization’s business situation to improve their current operational processes. Data mining is a process that assists data warehouse to dig and analyze big sets of data and extracting the data. It allows...
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...huge amounts of data that is stored in a data warehouse that is used for the company’s employees. The employees will pull data that is needed each day to do their daily tasks. The company handles with several different parts that make up one part. Each part is labeled and has a barcode so that the part can be identified. The system that holds all of the data is basically a data warehouse that when an employee needs certain information about a single part can be retrieved from the data warehouse. The data warehouse is also used to follow the vendors to see how well they are doing. What I mean by see how they are doing is to follow how many good parts they build versus the bad parts that are built and sent to the company. The data that is recorded when a bad part is found leads to an inspection of the parts. When the inspection starts there are required steps that are followed and entered into the database. When this data is entered into the database it can show how many parts that have been inspected and how many were good and how many bad. With this company’s regular database that is being used every day and the data warehouse being used to see how the parts are being handle and how the vendors are doing, there are a lot of variables that are put in place for the company. When the employee needs certain data about a vendor to see what parts they are building then the employee can retrieve this information from the data warehouse. The employee...
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...What is a Data Warehouse • A data warehouse is a relational database that is designed for query and analysis. • It usually contains historical data derived from transaction data, but it can include data from other sources. Finance, Marketing, • Data warehouse can be: Subject Oriented Integrated Nonvolatile Time Variant Inventory SAP, Weblogs, Legacy Identical reports produce same data for different period. daily/monthly/quarterly basis Why Data Warehouse • • • • Provide a consistent information of various cross functional activity. Historical Data. Access, Analyze and Report Information. Augment the Business Processes Why is BI so Important Information Maturity Model Return on Information BI Solution for Everyone BI Framework Business Layer Business goals are met and business value is realized Administration & Operation Layer Business Intelligence and Data Warehousing programs are sustainable Implementation Layer Useful, reliable, and relevant data is used to deliver meaningful, actionable information BI Framework Business Requirements Data Sources Data Sources Data Acquisition, Cleansing,& Integration Data Acquisition, Cleansing, & Integration Data Stores Data Stores Information Services Information Delivery Information Delivery Business Analytics Business Analytics Business Applications Business Applications Business Value Business Value Development Data Resource Administration ...
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...Data Warehouse A data warehouse has many different processes that require several different technologies. Batch and transaction processing data has to first be taken out of the operational databases and then it can be cleaned up. Then the data is uploaded onto a relational database. Data warehouses are the basis for customer relationship management systems because they can be used for consolidating customer data and identifying areas of customer satisfaction and frustration. These warehouses can be used for fraud detection, production analysis, profit center, and corporate management. For retailers, a data warehouse can help identify customer demographics, identify shopping patterns, and improve mailing responses. Data Warehouse REI The data warehouse REI is building is going to have many different types of information about its customers. In order to better serve its clientele, REI has to know what their customers do outdoors. With the help from IBM, REI thinks that their data warehouse will help them better identify their individual’s needs and help them better as a company. This will also help them identity what the customers bought online or in the retail stores. The warehouse will also give them insight whether they attended special training for equipment and outdoor activities, or even what items a particular customer has returned. Data Warehouse Concerns There are many issues that are surrounding a data warehouse that companies need to...
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...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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...August 29, 2015 Business Intelligence and Data Warehouses Student’s name: Professor’s name: Course title: 1. Differences between the structures of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data Data Warehouse is a database which is designed to process for query and analysis rather than for transaction processing, and it is usually contains historical data derived from transaction data, but can include data from other sources while relational database optimized for online transaction which includes insertions, updates and deletion. Basically Data Warehouse is defined as a subject-oriented, non-volatile and time –variant collection of database which support management’s decisions. Data Warehouse is very distinct from online transaction systems. Some of distinctions are given below: * One of main difference, a data warehouse you can do separate analysis workload form transaction workload which makes it very much read-oriented systems. * They deal higher amount of volume in comparisons to online transaction database. * They have a far higher amount of data reading versus writing and updating. This enables far better analytical performance and avoids impacting your transaction systems. * A data warehouse system can be optimized to consolidate data from many sources to achieve a key goal. * it prevents many disputes and enhances decision-making efficiency ...
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...Data Warehouses and Data Mining Your Name DBM 384 May 13, 2013 Jim Cervi Data Warehouses and Data Mining Data warehouses serve an integral function within many different industries. In the government and law enforcement agencies this is especially prevalent. Vast amount of data and information from multiple sources is often collected by these agencies. This data and information must be put into a format that allows for workable details by the analysts (HowStuffWorks.com, 2012). Data mining and data warehouses provide these agencies with the ability to select specific data out of the large volumes of data available to the analyst Data Warehouse A data warehouse is a database of information collected from several resources, saved under a specific schema, at only one site according to (Siberschatz, Korth, & Sudarshan, 2011). This type of system is effective for government intelligence agencies in storing and categorizing the data sources. By effectively categorizing and storing the data, the data warehouse provides the analyst with a location where an effective query can produce tailored and specific results from vast stores of records. The data warehouse does this by linking the data sources through common threads. These threads are what allow the analyst to access the correct related information through the query. The data warehouse provides the structure of the data sources that the information will be categorized in. To be truly effective, a well-designed data...
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...diagram, the following: Primary Data Warehouse and Data Mart. In this connection, explain the difference between ROLAP and MOLAP. A Primary Data Warehouse is a central repository of a database of a complete organization. It holds multiple subject areas and very detailed information. A Data Mart is a subset or an aggregation of the data stored to a primary data warehouse. It often holds only one subject area – for example, a specific department, finance or sales. It may hold more summaried data, and is typically smaller than a warehouse because of its employment on a different grain. Figure 1.1 illustrates the difference between data mart and a primary data warehouse. Since the data mart typically holds one subject area, it is much smaller than a primary data warehouse. These data marts can be viewed as small, local data warehouses replicating the part of primary data warehouse which is required by a specific domain or department. Data Warehouse Data Mart Data Warehouse Data Mart Figure 1.1 A data warehouse does not necessarily use a dimensional model, since it is partly normalized RDBMS, but data marts are multidimensional cubes. This connection gives arise to two concepts, ROLAP and MOLAP. ROLAP is an implementation based on a relational database, in our case which is a primary data warehouse, and MOLAP is an implementation based on a multidimensional database which are data marts. ROLAP tools use the relational database to access the data and generate SQL queries to calculate...
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...Data Warehouse is an application that collects data information to assist marketing and financial improvements through sales transactions and other dealings. This storage system holds large data files of consumers and other dealings within a company. The data collected from transactions assists companies with making decision that can better serve consumers as well as company reports. This stored information is more reliable because of its day-to- day transactions reports. Utilizing this type of system can be cost effective for storing large information for various companies. Once data is stored, the information is available to anyone, however it cannot be altered (Laudon & Laudon, 2013, p. 160). REI is building a data warehousing system, in order for the organization to have a better method to recognize each consumer’s interactions with the company. Information collected such as purchases and transactions through online, catalogs, stores and websites browsing is stored within the system. This will enhance REI’s customer service by allowing them to track the interest of co-ops, send notifications of recalls for particular items, and make it easier to search or query items up with a specific product number. REI had a vision of being connected with its consumers so they could better serve them. They also wanted to tailor the products to the needs of the consumer, while also being user-friendly. Although the data warehouse is good for business there are various concerns for...
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...CSCI 1507 (1903) "Enterprise level data work flows and Data Warehousing" Professor Rajni Palikhey University of Northern Virginia Acknowledgement This Research Paper would not have been possible without the guidance and the help of my co-students and respected Professor who in one way or the other contributed and extended their valuable assistance in the preparation and completion of this research paper. I would to like to convey my sense of gratitude to Professor.Rajni Palikhey who helped and supported us right throughout the semester. This paper would not have been possible without her cooperation and technical assistance. We would also thank our Institution and our faculty members without whom this project would have been a distant reality. We also extend our heartfelt thanks to our family and well wishers. I would like to take this occasion to specially thank University of Northern Virginia to provide us with excellent faculty and also in supporting us getting quality education remotely. Contents SL No Title Page no 1 Abstract 5 2 Introduction to Databases 6 3 OLTP and OLAP Systems 7 4 Difference between OLTP and OLAP 9 5 Data Modeling 13 6 Workflows in Enterprise level Data warehousing 18 7 Business Intelligence tools used in Data flow and Data Warehousing 21 8 Analysis in Data warehousing 24 9 Conclusion 28 10 Foot Note 30 11 References 31 ABSTRACT These days majority...
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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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...Intelligence and Data Warehouses Kevin Sloley Professor Dammlash Gebre CIS-111 Intro to Related Database Management Systems Due March, 2016 Outline the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data. The primary difference between your application database and a data warehouse is that while the former is designed (and optimized) to record, the latter has to be designed (and optimized) to respond to analysis questions that are critical for your business. Application databases are OLTP (On-Line Transaction Processing) systems where every transaction has to be recorded, and super-fast at that. Consider the scenario where a bank ATM has disbursed cash to a customer but was unable to record this event in the bank records. If this started happening frequently, the bank wouldn't stay in business for too long. So the banking system is designed to make sure that every trasaction gets recorded within the time you stand before the ATM machine. This system is write-optimized, and you shouldn't crib if your analysis query (read operation) takes a lot of time on such a system. A Data Warehouse (DW) on the other end, is a database (yes, you are right, it's a database) that is designed for facilitating querying and analysis. Often designed as OLAP (On-Line Analytical Processing) systems, these databases contain read-only data that can be queried...
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