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  • S.NASIRA TABASSUM, SK.ALTHAF AHAMMED / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1689-1694 Data Warehousing and Business Analytics Implementation S.NASIRA TABASSUM SK.ALTHAF AHAMMEDAbstract Data warehousing (DW) has emerged as doing data mining analysis, as well as unstructuredone of the most powerful technology innovations data (thus the need for content managementin recent years to support organization-wide systems) thus providing managerial decision supportdecision making and has become a key for complex business questions. DW is also ancomponent in the information technology (IT) enabling technology for data mining, customer-infrastructure Data warehousing methodologies relationship management, and other business-share a common set of tasks, including business intelligence applications. Although data warehousesrequirements analysis, data design, architectural have been around for quite some time, they havedesign, implementation and deployment. This been plagued by high failure rates and limitedpaper provides an overview of Analytics. It spread or use. Drawing upon past research on theexplains how data from a web servers log can be adoption and diffusion of innovations and on theharvested to generate useful and actionable implementation of information systems (IS), webusiness intelligence, particularly when the data examine the key organizational and innovationis combined with existing customer and sales data factors that influence the infusion (diffusion) of DWin a Data Warehouse. Business Intelligence is within organizations and also examine if moreoften confused and sometimes used intermittently extensive infusion leads to improved organizationalwith data warehouse concepts. We discuss the outcomes. Business intelligence is closely related tosimilarities and differences between these two data warehousing. This section discusses businessconcepts in this paper. intelligence, as well as the relationship between business intelligence and data warehousing. As theKeywords: data warehouse, business intelligence old Chinese saying goes, "To accomplish a goal, make sure the proper tools are selected." This is1. Introduction especially true when the goal is to achieve business Business Intelligence refers to a set of intelligence. Given the complexity of the datamethods and techniques that are used by warehousing system and the cross-departmentalorganizations for tactical and strategic decision implications of the project, it is easy to see why themaking. It leverages technologies that focus on proper selection of business intelligence softwarecounts, statistics and business objectives to improve and personnel is very important. After the tools andbusiness performance. A Data Warehouse (DW) is team personnel selections are made, the datasimply a consolidation of data from a variety of warehouse design can begin phase.sources that is designed to support strategic andtactical decision making. Its main purpose is to 2. Business Intelligence and Data Warehouseprovide a coherent picture of the business at a point Business intelligence (BI) is defined as thein time. Using various Data Warehousing toolsets, ability for an organization to take all its capabilitiesusers are able to run online queries and mine" their and convert them into knowledge. This producesdata. Many successful companies have been large amounts of information that can lead to theinvesting large sums of money in business development of new opportunities. Identifying theseintelligence and data warehousing tools and opportunities, and implementing an effectivetechnologies. They believe that up-to-date, accurate strategy, can provide a competitive marketand integrated information about their supply chain, advantage and long-term stability within theproducts and customers are critical for their very organizations industry. BI technologies providesurvival. This website introduces some key Data historical, current and predictive views of businessWarehousing concepts and terminology. It explains operations. Common functions of businessData Warehousing from a historical context and the intelligence technologies are reporting, onlineunderlying business and technology drivers that are analytical processing , analytics, datamaking Data Warehouses a hot commodity. mining, process mining, complex eventA data warehousing (or data mart) system is the processing, business performance managementbackend, or the infrastructural, component for , benchmarking , text mining , predictiveachieving business intelligence. Business analytics and prescriptive analytics. Businessintelligence also includes the insight gained from intelligence aims to support better business decision- 1689 | P a g e
  • S.NASIRA TABASSUM, SK.ALTHAF AHAMMED / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.making. Thus a BI system can be called a decision 4. Business Intelligence Servicessupport system(DSS). Though the term business 3. Related Workintelligence is sometimes used as a synonym Dell helps create a successful businessfor competitive intelligence (because they both intelligence solution.support decision making), BI uses technologies, Business needs and current state of informationprocesses, and applications to analyze mostly assets are analyzed to define a BI strategy that mayinternal, structured data and business processes include new or revised dashboards, redesigned datawhile competitive intelligence gathers, analyzes and models and integration of source systems.disseminates information with a topical focus on Business Intelligence Advisory Servicescompany competitors. If understood broadly, The Dell Business Intelligence Advisory Servicesbusiness intelligence can include the subset of include:competitive intelligence. Often BI applications use  Framework for establishing a businessdata gathered from a data warehouse or a data mart. intelligence competency center (BICC)However, not all data warehouses are used for  Plans for building out a successful businessbusiness intelligence, nor do all business process management (BPM) program, includingintelligence applications require a data warehouse. a collaborative approach to workshops andIn order to distinguish between concepts of business process flowsintelligence and data warehouses, Forrester  Business solutions defined and aligned toResearch often defines business intelligence in one corporate strategyof two ways: Business Intelligence Advisory Services helps to Using a broad definition: "Business develop a comprehensive business intelligence (BI)Intelligence is a set of methodologies, processes, strategy and roadmap that aligns with strategicarchitectures, and technologies that transform raw enterprise goals and get the information needed todata into meaningful and useful information used to make fast, fact-based decisions.enable more effective strategic, tactical, and operational insights and decision-making."[6] When Business Intelligence Design and Planusing this definition, business intelligence also After BI analysis, the next step is to designincludes technologies such as data integration, data and plan the business intelligence data that isquality, data warehousing, master data management, needed by the organization. The BI design and plantext and content analytics, and many others that the helps to create a detailed business and technologymarket sometimes lumps into the information design that will scale to the business needs, improvemanagement segment. Therefore, Forrester refers data quality and turn information into actionableto data preparation and data usage as two separate, intelligence.but closely linked segments of the businessintelligence architectural stack. Business Intelligence ImplementationForrester defines the latter, narrower business The designed BI is then implemented usingintelligence market as "referring to just the top the right tools that help to speed up deployment andlayers of the BI architectural stack such as reporting, ensure a successful adoption of business intelligenceanalytics and dashboards."[7] Thomas and data warehouse (BIDW) solution.Davenport has argued that business intelligenceshould be divided into querying ,reporting, OLAP, BI Management and Supportan "alerts" tool, and business analytics. In this The BI needs frequent maintenance anddefinition, business analytics is the subset of BI support after it is implemented. This maximizes thebased on statistics, prediction, and optimization‘[8]. value of business intelligence and data warehouseBefore implementing a BI solution, it is worth (BIDW) investment with 24x7 production support,taking different factors into consideration before maintenance and administration services.proceeding. The Business Intelligence Analyst should be able to According to Kimball et al., these are the three think strategically about business issues andcritical areas that you need to assess within your understand product & service portfolios as well asorganization before getting ready to do a BI emerging technologies and their benefits toproject:[12] customers.1. The level of commitment and sponsorship of the In addition to being a professional in the project from senior management Intelligence, the Business Intelligence Analyst2. The level of business need for creating a BI partners closely with the Business Analysts and implementation Product Managers to support the release of new3. The amount and quality of business data products and proof-of-concept pilots.available. 4. Strategy of Implementation 1690 | P a g e
  • 1691 S.NASIRA TABASSUM, SK.ALTHAF AHAMMED / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.A. Background: This includes identifying the integrated. Although there is no absolute dollar background of the business which includes the value assessed for the BI effort, it is clear that needs of the business clients. integrated dataB. Obtaining consistent data and creating (1) minimizes the need for duplicate data entry and meaningful reports. This has been a major reconciliation of inconsistent information thus challenge for most of the organizations as the reducing manpower needs, information needs keeps changing for various (2) drives management decisions to improve reasons and very frequently, no consensus of operation, and what is the ‗appropriate‘ data for different (3) improves the intelligence questions, and only few individuals have been It should be noted as well that BI seeks to able to access and make use of data minimize the ―cost of distrust.‖ If the integrated successfully. data are not trusted, then users will seek the ability Decision makers have routinely depended to ―massage‖ that data based on the perception oron IT experts to compile data, sometimes waiting the actuality of its inaccuracy, and frequently then todays or weeks for the needed answers. However, optimize a portion of the overall business.day-to-day activities demand timely and accurate But this optimization of the part does not optimizeinformation and increasing demand for more the whole—if data inaccuracies are not corrected atinformation to make business decisions which at their source (within the transactional systems andpresent has been very difficult to provide on short associated business processes) then the cycle willnotice. continue. Enormous amounts of integrated data will BI seeks fundamentally to address thislead to faster and better decision making. The cycle by providing high-quality data and tools andobjectives of the Business Intelligence (BI) associated business processes, so that the BI way isImplementation are to provide a new approach to clearly recognized as the superior way.data management, presentation and analytics. Goals for BI are at two levels. Firstly, there is theImplementing Business Intelligence enables to goal to enable a smooth (i.e. non-interrupted)access and retrieve financial, research, personnel transition from the old to the new system, so as notand miscellaneous data from one single source, give to disrupt the current operation.easy and secure access of relevant data to all levels Secondly, a more challenging goal is to create a dataof management or units, spend minimal time on environment that will answer questions that havedata retrieval, but dedicate significant time to data not been previously possible. Much of theanalysis and decision making, make data, reports, implementation plan focuses on data migration, dataanalysis and models available to a broad user base. warehousing and reporting.Business intelligence primarily focuses on processes As vast amounts of data are collected, newand people. To this purpose the BI team will need to opportunities to analyze and model data will presentensure data conversion and data warehousing themselves. The now ready availability of statisticalconsistent with the needs of current and future tools to perform data mining will allow theorganizational goals. exploration of the relationships among data in order Business Intelligence effort encompasses to extract value and ultimately new insights.data conversion and cleansing, data warehousing A plan to manage the transition and not interruptand data consumption. Only ―good‖ data will be the flow of business reporting is key to the successconverted and migrated into the data warehouse; of the BI implementation.older (non-cleansed) data is stored for historicalpurposes only. 6. Audience of Business Intelligence The data warehouse allows secure storage It is important to understand the audienceand access to data from the new transactional of the business intelligence project or data. Thissystems and will allow additional storage of other would help in analyzing the requirements ofapplications and individual departmental needs. different business users and building an efficientRapid advances in processing speed, innovative data database which is helpful to the actual end users.warehouse design and pioneering concepts of data Power-users / developers: This can be adisplay such as dashboards are opening up new group of technicians that produce reports that theyopportunities for data management. use themselves or that they distribute to others. The project will serve this audience by providing access5. Objectives of Business Intelligence to a richer set of transaction data and by providing The objective of BI is to increase its technological efficiencies that allow them to spendoperational effectiveness. Decision makers need to less time ‗pulling‘ information and more timehave easy access to data that is timely, accurate and ‗analyzing‘ information. 1691 | P a g e
  • S.NASIRA TABASSUM, SK.ALTHAF AHAMMED / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp. To mitigate the risk of inappropriate use ofOperational Decision Makers: This is a group of data, the BI team advocates that a balance be struckmanagers or leaders in administrative and academic between electronically restricting data access andorganizations. These managers, directors, business training users to handle data responsibly. Besidesofficers, departmental managers who are typically the enormous cost, if too many technology barriersdependent upon dedicated reports today. This leads are built into the system, data users will circumventto a disparity in access to and use of information for the new data system, and proliferation of differentday-to-day decision making. The project will serve data repositories will continue, thus defeating thethis audience by providing them a set of dashboard purpose of BI.reports that they can individually access through aneasy-to-use web self-service reporting portal. 8. Success Critieria of Business Intelligence Success criteria of a business intelligenceExecutive Decision Makers: This group of deans, application include:AVPs and VPs are reliant upon dedicated report • Positive feedback from users on vastly improvedwriters today as well. This audience generally does access to data and informationnot have ‗direct‘ access to information, but their • Perfect reproducibility and consistency of dataposition means that they generally have when queried though different channelsprogramming staff who can provide information to • Improved communications and decision makingsupport their decisions. Unfortunately, this at all levels.information frequently needs to be ‗cobbledtogether‘ from a number of different sources, lacks 9. Methodology of Data Warehousecontext (relationship to the same number last year or This section explains the steps to developin another unit), and is generally provided on- and deploy a data warehouse. In addition it willdemand only (i.e., no notifications or early show differences between DW Methodology andwarnings). The project will serve this audience by Traditional IT Methodologies.providing self-service dashboard reports that blend The Data Warehousing Methodology iscurrent information with contextual information. BI organized into the different phases. Like all softwarewill also serve this audience by beginning to produce implementations, Business Intelligencea dashboard that quickly displays some of the implementations follows all Software Developmentindicators. Life Cycle Management guidelines, which start with There is in reality an overlap between the establishing scope or goals and identifying keydifferent audiences. Generally, BI intends to provide stakeholders, users and managers to guarantee thea richer set of information to a significantly broader credibility and commitment with Businessaudience and to shift the allocation of time away Intelligence project.from ‗pulling and maintaining‘ information and Developing data warehouses is definitely differenttoward analyzing and using information. than developing other IT systems and so requires aIt is also important to note that self-service reporting different methodology.provided through the BI project is not just a tool Data Warehousing Methodology:technology, or project – it is a disruptive change to • Use of data is exploratory and less predictabledecision makers at all levels. • Multidimensional Modeling • Focus is on loading and presenting data7. Access and Security of Business Intelligence Traditional IT Methodology: From an access and security standpoint the • Automated processes are repeated andvision is to ensure that decision makers at all levels predictablehave access to data needed to perform their jobs. • ERD Data ModelingAny data directly accessible by the public should be • Focus is on rapid on-line updating of datahighly controlled. General security should be Data warehousing is not simply creating aprovided through encryption for users and for set of reports that are run periodically. It involvesapplications that access information. questions that may lead to initially unpredicted Authentication should be provided to the places. Requirements describe the needed solution inweb application. Access to highly sensitive data such business terms. In the analysis phaseas social security numbers, credit card numbers, detailed requirements for data warehouse arebanking information, driver license numbers and defined.benefit information should be granted on a ‗need Acknowledgementsonly‘ basis and available only to the authorized The satisfaction and euphoria thatusers. accompanies the successful completion of any task would be incomplete without the mention of the 1692 | P a g e
  • 1693 S.NASIRA TABASSUM, SK.ALTHAF AHAMMED / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.people who made it possible and whose 9. ^ "Are You Ready for the New Businessencouragement and guidance have crowned our Intelligence?". Dell.com. Retrieved 2012-efforts with success. We extend our deep sense of 06-19.gratitude to Principal Dr. S. M. Afroz, and HOD, 10. ^ Jeanne W. Ross, Peter Weil, David C.Computer Science and Engineering, Nizam Institute Robertson (2006) "Enterprise Architectureof Engineering and Technology, Deshmukhi, Mr. As Strategy", p. 117 ISBN 1-59139-839-8.M. S Qaseem, HOD, Information Technology, 11. ^ a b c d Swain Scheps "BusinessNizam Institute of Engineering and Technology, Intelligence For Dummies", 2008, ISBNDeshmukhi, for his support and encouragement. I 978-0-470-12726-0am indebted to Ms. Asma, Associate professor, 12. ^ a b Watson, Hugh J.; Wixom, Barbara H.Nizam Institute of Engineering andTechnology, (2007). "The Current State of BusinessDeshmukhi, Nalgonda (A.P), India for giving her Intelligence". Computer 40 (9):helpful comments and sharing ideas in carrying out 96.doi:10.1109/MC.2007.331.this research work. 13. ^ Pendse, Nigel (7 March 2008). "Consolidations in the BIReferences industry". The OLAP Report. 1. ^ (Rud, Olivia (2009). Business 14. ^ Imhoff, Claudia (4 April 2006). "Three Intelligence Success Factors: Tools for Trends in Business Intelligence Aligning Your Business in the Global Technology". Economy. Hoboken, N.J: Wiley & 15. ^ a b c Rao, R. (2003). "From unstructured Sons. ISBN 978-0-470-39240-9.) data to actionable intelligence". IT 2. ^ a b D. J. Power (10 March 2007). "A Professional 5 (6): Brief History of Decision Support Systems, 29.doi:10.1109/MITP.2003.1254966. version 4.0". DSSResources.COM. 16. ^ a b c Blumberg, R. & S. Atre Retrieved 10 July 2008. (2003). "The Problem with Unstructured 3. ^ Kobielus, James (30 April 2010). "What‘s Data". DM Review: 42–46. Not BI? Oh, Don‘t Get Me Started....Oops 17. ^ a b Negash, S (2004). "Business Too Late...Here Goes....". "―Business‖ Intelligence".Communications of the intelligence is a non-domain-specific Association of Information Systems 13: catchall for all the types of analytic data 177–195. that can be delivered to users in reports, 18. ^ a b Inmon, B. & A. Nesavich, dashboards, and the like. When you specify "Unstructured Textual Data in the the subject domain for this intelligence, Organization" from "Managing then you can refer to ―competitive Unstructured data in the organization", intelligence,‖ ―market intelligence,‖ ―social Prentice Hall 2008, pp. 1–13 intelligence,‖ ―financial intelligence,‖ ―HR 19. ^ Gartner Reveals Five Business intelligence,‖ ―supply chain intelligence,‖ Intelligence Predictions for 2009 and and the like." Beyond. gartner.com. 15 January 2009 4. ^H P Luhn (1958). "A Business 20. ^ Campbell, Don (23 June 2009). "10 Red Intelligence System". IBM Journal 2 (4): Hot BI Trends".Information Management. 314. doi:10.1147/rd.24.0314. 21. ^ Wik, Philip (11 August 2011). "10 5. ^ Power, D. J.. "A Brief History of Decision Service-Oriented Architecture and Business Support Systems". Retrieved 1 November Intelligence". Information Management. 2010. 22. ^ Rodriguez, Carlos; Daniel, Florian; 6. ^ Evelson, Boris (21 November Casati, Fabio; Cappiello, Cinzia (2010). 2008). "Topic Overview: Business "Toward Uncertain Business Intelligence: Intelligence". The Case of Key Indicators". IEEE Internet 7. ^ Evelson, Boris (29 April 2010). "Want to Computing 14 (4): know what Forresters lead data analysts 32.doi:10.1109/MIC.2010.59. are thinking about BI and the data 23. ^ Rodriguez, C., Daniel, F., Casati, F. & domain?". Cappiello, C. (2009),Computing Uncertain 8. ^ Henschen, Doug (4 January Key Indicators from Uncertain Data, 2010). Analytics at Work: Q&A with Tom pp. 106–120 | conference = ICIQ09 | year = Davenport. (Interview). 2009 1693 | P a g e
  • S.NASIRA TABASSUM, SK.ALTHAF AHAMMED / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1689-1694[1] S.Nasira tabassum has received her Masters [2] SK.Althaf ahammed has received his Masters Degree in computer application from degree in computer application from M.J.College of Science and Technology, m.k.university madhurai (T.N). He is currently Affiliated to Osmania University, Hyderabad working as an Associate professor in Shadan and Pursuing M.Tech in Software Engineering Group of Colleges, Hyderabad. from Nizam Institute of Engineering and Technology, Deshmukhi, Nalgonda Dist, Affiliated to JNTU Hyderabad, AP India. 1694 | P a g e