...(online analytical processing) is computer processing that enables a Big data analytics Data modeling Ad hoc analysis user to easily and selectively extract and view data from different points of view. For example, a user can request that data be analyzed to display a spreadsheet showing all of a company's beach ball products sold in Florida in the month of July, compare revenue figures with those for the same products in September, and then see a comparison of other product sales in Data visualization Extract, transform, load (ETL) Florida in the same time period. To facilitate this kind of analysis, OLAP data is stored in a multidimensional database. Whereas a relational database can be thought of as two-dimensional, a multidimensional database considers each data attribute (such as product, geographic sales region, and time Association rules (in data mining) Relational database period) as a separate "dimension." OLAP software can locate the intersection of dimensions (all products sold in the Eastern region above a certain price during a certain time period) and display them. Attributes such as time periods can be broken down into subattributes. Denormalization OLAP can be used for data mining or the discovery of previously Master data management (MDM) undiscerned relationships between data items. An OLAP database does not Predictive modeling needed for trend...
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...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 of the applications, may it be web applications or windows applications or mobile applications, are completely database dependent. Most of the application developments are becoming database driven environments, hence rendering databases as one of the most key elements in a software environment. This dependency on databases can attributed to the increasing number of data requirements from the...
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... Benefits of Data Warehousing Data warehousing is intended to support reporting and analysis of data. Here are the benefits as follows: • Potential High Returns on Investment • Competitive Advantage • Increased Productivity of Corporate Decision Makers Problems of Data Warehousing Here are some problems associated with developing and maintaining a data warehouse as follows: • Underestimation of Resources for Data Loading • Hidden Problems with Source Systems • Required Data not Captured • Required Data not Captured • Increased End User Demands • Data Homogenization • High Demand for Resources • Data Ownership • High Maintenance • Long Duration Projects • Complexity of Integration Data Warehouse Architecture Operational Data Store • A repository of current and integrated operational data used for analysis Load Manager • Performs all the operations associated with the extraction and loading of data into the extraction and loading of data into the warehouse Warehouse Manager • Performs all the operations associated with the management of data in the warehouse Query Manager • Performs all the operations associated with the management of user queries Detailed Data • The area of the warehouse which stores all the detailed data in the database schema Lightly and Highly Summarized Data • The area of the warehouse which stores...
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...Introduction Many organizations and companies rely on databases to run their operations and achieve competitive advantage. Database design refers to the different parts of the design of an overall database system. It can be thought of as the logical data structures used to store data, and the forms and queries used as part of the overall database application within the database management system (Wikipedia.org). The paper focuses on database design methods and steps that can be taken to achieve a good design structure that avoids redundancy, duplicate data or the absence of required data. The need to understand database models Databases are important to the organizational setting. Databases allow organizations to share data across multiple applications and systems. Organizations build several databases each one sharing data with several information systems. This is because it is almost impractical to build one database to meet an entire organization’s needs. Therefore data design is critical to the consistency, integrity and accuracy of the data in a database. A database that is improperly designed will make it difficult to retrieve certain types of information. Besides, there is the risk that searches will produce inaccurate results or information that may have potential damaging effects on a company's bottom line. Inaccurate database may also affect the daily operations of a business and its future direction. A good database addresses the informational and operational needs of...
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...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 warehouses and acquire meaning and notify selection generating using their company informative assets as a result of these kinds of data warehouses. Successful data warehousing involves subsequent established information warehousing techniques, sound project management, solid organizational...
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...OBJECT-RELATIONAL DATABASE MODELING USING UML Table of Contents Introduction……………………………………………………………………………………..4 Overview of ER Modeling and UML…………………………………………………………...4 UML Meta-model……………………………………………………………………………… 6 UML Components………………………………………………………………………………7 UML Data Profile……………………………………………………………………………….9 UML Diagrams……………………………………………………………………………….....10 UML Diagram Classification – Static, Dynamic, and Implementation…....................................12 4+1 View of UML Diagrams……………………………………………………………………13 Object-oriented Class Model and Relational Database Model..............................................…...14 Use of UML to develop Ontologies…………………………………………………………..…17 References……………………………………………………………………………………….19 Abstract The Unified Modeling Language (UML) is being used as the de-facto standard in the software industry. With the adoption of UML 2.0, the new enhancements allow this version to describe many of the elements found in today's software technology as well as Model Driven Architecture and Service-Oriented Architecture. Many existing software applications involve complex application layer implemented in object-oriented programming languages and at the same time use relational database systems as the back-end data store. Modeling the whole system in a consistent manner will help developers and end users better understand the application. The Unified Modeling Language (UML) is a standard language for modeling software and database systems. Data...
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...they will be used. A great example would be an analyst who understands exactly how users would think, react, communicate and work with the systems software, databases, and/ or Hardware. Knowing these points would allow the analyst to prevent future issues, correct future needs, fulfill current requirements and create a great user experience. Not understanding these points would cause for an uneasy project that potentially would need a lot of maintenance down the line because it doesn’t fit what the user/ people needs. What is the role of systems theory relative to system analysis methods? First, to define the two terms: Systems Theory according to buisnessdictionary.com is defined as “One of the several methodologies (such as operations research, systems analysis, systems dynamics) which employ systems approach to understanding complex phenomenon and problems.” System Analysis methods according to buisnessdictionary.com is defined as “In a broad sense, a general methodology (not a fixed set of techniques) that applies a 'systems' or 'holistic' perspective by taking all aspects of the situation into account, and by concentrating on the interactions between its different elements.” From the definitions listed above, it can be conclude that Systems theory is the understanding of systems in its entirety; while Systems analysis methods are methods used to try to understand the system, why it reacts the way it does or how it needs to act in a certain instance. An example would...
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...Logical Modeling in Systems Analysis Table of Contents Topic Page Chapter One Abstract . . . . . . . . . . . . . . . . . . . 3 Chapter Two Introduction . . . . . . . . . . . . . . . . . . 4 Information Systems . . . . . . . . . . . . . . . 5 IS Analysis Phase . . . . . . . . . . . . . . . . 5 Modeling Definition and Concepts. . . . . . . . . 5 Traditional Approach Logical Models . . . . . . . . 7 Object Oriented Approach Logical Models . . . . . . 9 Chapter Three Current Topics in Data Modeling . . . . . . . . . . . 12 Bibliography . . . . . . . . . . . . . . . . . . 14 CHAPTER ONE Abstract Today’s organizations are utilizing their core competencies while exploiting the core competencies of subcontractors to produce highly differentiated and high quality products at a lower cost. Business process reengineering has played a key role in remaining competitive, enabled through information technology. Existence of the automated information system, developed through Systems Analysis and Design, has become a requirement for survival of today’s companies. Process requirements...
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...Vilnius Gediminas Technical University Jelena Mamčenko Lecture Notes on INFORMATION RESOURCES Part I Introduction to Dta Modeling and MSAccess Code FMITB02004 Course title Information Resourses Course volume 3,0 cr. (4,50 ECTS cr.) Teaching methods (Full-time, daytime studies): Lectures - 16 h per semestre Laboratory works - 32 h per semestre Individual work - 72 h per semester Course aim Understandig of models and system of information resourses. Jelena Mamčenko Introduction to Data Modeling and MSAccess CONTENT 1 Introduction to Data Modeling ............................................................................................................... 5 1.1 Data Modeling Overview ............................................................................................................... 5 1.1.1 Methodology .......................................................................................................................... 6 1.1.2 Data Modeling In the Context of Database Design................................................................ 6 1.1.3 Components of A Data Model................................................................................................ 6 1.1.4 Why is Data Modeling Important? ......................................................................................... 6 1.1.5 Summary ................................................................................................................................ 7 1.2 The...
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...Database Modeling Kelli Clipp Business Systems Analysis INF322 Arman Kanooni February 10, 2013 This paper discusses database modeling and one tool that can be used for the process. The tool I’ve chosen is based on the material in our textbook and article ‘Modeling for the future’. Database modeling is the process of software engineering which allows for the creation of an information system. In the article ‘Modeling for the future’, they compare database modeling to constructing a house (Carreon, Wang, & Watt, 1996). This comparison is based on the fact that one would use a blueprint when building a house and database modeling can be considered as the same concept. A data model is in essence a blueprint or a plan for the database and without it the database may not be very well built, as with any program, house or building you need a plan. There are several tools available for database designers to utilize and the key is choosing the tool which is right to be used that will meet all the requirements of the database to be created. In the article ‘Modeling for the future’ they discussed and compared products from 1996, and although this article appeared to cover the four key products for database modeling at that time, the market has changed...
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...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 from multiple OLTP data sources (including DB2, Oracle, IMS databases, and flat files) using Extract, Transfer, and Load (ETL) tools. The warehouse is located in a presentation server. It can span enterprisewide data needs or can be a collection of “conforming” data marts [8]. Data marts (subsets of data warehouses) are conformed by following a standard set of attribute declarations called...
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...2013.6.6.25 Enterprise Business Processes System Analysis and Design Geng Yushui and Sun Jianjun School of Information, Qi Lu University of Technology Jinan250353, China gys@qlu.edu.cn, 631901036@163.com Abstract At present, more and more enterprises or departments seek to extend the application of information technology to the more complicated business processes, these business processes are characterized by a number of business activities, capable of handling multiple business objects, business logic and business rules complex. Thus, the enterprise business process management system arises at the historic moment. Enterprise business processes management system is not only a software product that provides a single function, but also you can customize for the different areas of the business process according to user's actual business needs. In the process of management platform, Process simulation for the process simulation module is put forward based on probability analysis, and for the process modeling module, more collaborative process modeling technology is put forward. In the business application layer, process monitoring application based on application driven is proposed. Positioning in the implementation of enterprise business process management system for business process simulation software implementation or, as well as to simulate the processes or processes of monitoring, diagnostic analysis and optimization. The innovation points of system design...
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...MARKETING ENGINEERING FOR EXCEL • CASE • VERSION 2.0.0 Case Bookbinders Book Club By Gary L. Lilien & Arvind Rangaswamy Introduction About 50,000 new titles, including new editions, are published in the United States each year, giving rise to a $20+ billion book publishing industry. About 10 percent of the books are sold through mail order. Book retailing in the 1970s was characterized by the growth of chain bookstore operations in concert with the development of shopping malls. Traffic in bookstores in the 1980s was enhanced by the spread of discounting. In the 1990s, the superstore concept of book retailing was responsible for the double-digit growth of the book industry. Generally situated near large shopping centers, superstores maintain large inventories of anywhere from 30,000 to 80,000 titles. Superstores are putting intense competitive pressure on book clubs, mail-order firms and retail outlets. Recently, online superstores, such as www.amazon.com, have emerged, carrying 1–2.5 million titles and further intensifying the pressure on book clubs and mail-order firms. In response to these pressures, book clubs are starting to look at alternative business models that will make them more responsive to their customers’ preferences. Historically, book clubs offered their readers continuity and negative option programs that were based on an extended contractual relationship between the club and its subscribers. In a continuity program, popular...
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...ranow, E. B. “Developing Good Data Definitions.” Database Programming & Design 2 (8) (1989): 36–39. Booch, G. Object-Oriented Analysis and Design with Applications. 2d ed. Redwood City, CA: Benjamin Cummings, 1994. Bruce, T. A. Designing Quality Databases with IDEF1X Information Models. New York: Dorset House, 1992. Chen, P. P-S. “The Entity-Relationship Model—Toward a Unified View of Data.” ACM Transactions on Database Systems 1 (March 1976): 9–36. Codd, E. F. “A Relational Model of Data for Large Relational Databases.” Communications of the ACM 13 (6) (1970): 77–87. Dutka, A. F., and H. H. Hanson. Fundamentals of Data Normalization. Reading, MA: Addison-Wesley, 1989. Finkelstein, R. “Breaking the Rules Has a Price.” Database Programming & Design 1 (June 1988): 11–14. Fleming, C. C., and B. von Halle. “An Overview of Logical Data Modeling.” Data Resource Management 1 (1) (1990): 5–15. Fowler, M. UML Distilled: A Brief Guide to the Object Modeling Language. 2d ed. Reading, MA: Addison-Wesley, 2000. Gibson, M., C. Hughes, and W. Remington. “Tracking the Trade-Offs with Inverted Lists.” Database Programming & Design 2 (January 1989): 28–34. Gottesdiener, E. “Turning Rules into Requirements.” Application Development Trends 6 (7) (1999): 37–50. Hay, D. Data Model Patterns: Conventions of Thought. New York: Dorset House, 1996. Hoffer, J. A., V. Ramesh, and H. Topi. Modern Database Management. 10th ed. Upper Saddle River, NJ: Prentice Hall, 2011. Inmon, W. H...
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...establishing the methods to source for the information, and how to use this information to improve a business position . Data mining is the sourcing of any hidden and predictive business information from a relevant database. It involves a thorough analysis of data gained from various sources, manipulating it into useful tool - a tool that leads to raising business revenue, saving on the running costs or both (http://en.wikipedia.org/wiki/Data_mining). Data mining tool incorporates analytical tools that helps build a useful predictive relationship. Data mining tools helps get answers as it scrutinizes data from different perspective to a precision, than any expert could do. Interplay of data mining process with software and hardware utilities is a big step in data analysis. The integration of artificial intelligence and databases heightens the data-mining goal as the information is translated into human-understandable format. This brings a chain link between databases and other data processing and management systems. When data mining and analysis are paired with decision support system, appropriate responses to the summarized data is given, which serves as a determinant to business’ future position. Data mining is a powerful tool in business modeling. Business modeling...
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