Lecture 4 - Business Intelligence
Lecture 4 - Business Intelligence ACC1006
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This 6 page Class Notes was uploaded by Wai Chuan on Sunday August 16, 2015. The Class Notes belongs to ACC1006 at National University of Singapore taught by in Summer 2015. Since its upload, it has received 63 views. For similar materials see Accounting Information Systems in Accounting at National University of Singapore.
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Date Created: 08/16/15
Chapter 6 Business intelligence Lecture 4 61 Whv need Busineis Intelligence Process of business information collection management and analysis To produce patterns relationships clusters and trends and to deliver that info on timely basis to users who need it So that decision makers can acquire knowledge and insight 0 Must know what we want so that we can focus 0 Eg Data on cleaning times of beds at NUH o Eg PSA RFID data will enable the identification in the container yard traceability and control 0 Can know where their assets are and all movements at key locations will be recorded for eventual streamlining and optimizations Business cycles are now extremely compressed 0 Ever changing technologies Data communications and data storage are essentially free Failure to grasp the value of the information at a business39 disposal is more commonplace than one might think 62 Bl systems Can be solutions organizational changes products technologies and methods to organize key data to improve performance and profit Factors Customers competitors business partners competitive environment and internal operations Can be information systems with a more interdepartmental focus and their general overview towards business performance eg SCM CRM and ERP Decision Support Systems DSSs support better decision making Can do market segmentation personalize customer relationships for higher customer satisfaction and retention Can do quota propensity to buy analysis 0 Based on need to increase their loyalty to your product line 0 Target on most likely to buy 63 Bl tool v application v system B tool is one or more computer programs that implement the logic of a particular procedure or process Reporting data mining and KM tools Eg sorting clustering B application is the use of a tool on a particular type of data for a particular purpose Eg using clustering to generate clusters of customers so that we understand each cluster better B system is an information system having all five components hardware software data procedure peopleusers that delivers results of a BI application to users who need those results Advantages of Bl Organization reacts faster more sensitive to the customers needs Knowing customer demands demand forecasting so that your firm can plan Responding to changing trends in the market Optimizing operational processes Optimum utilization of organizational resources Intricate study assisting for future prospects 000000 64 Reporting Applications B application that input data from a sources and apply a reporting tool to the data to produce information The reporting system delivers the information to authorised users at appropriate times Basic reporting operations Sorting grouping calculating filtering and formatting RFM Analysis Analyze and rank customers according to purchasing patterns 0 R how recently a customer purchased your products 0 F how frequently a customer purchases your products o M how much money a customer typically spends on your products 0 The lower the score the better the customer Online Analytical Processing OLAP o What can it do I Dynamic ability to sum count average and perform other arithmetic operations on groups of data I Create ondemand reports and queries and to conduct analysis of data Can change report format I Manipulate and analyze data from multiple perspectives I More generic than RFM I Can look at the analysis at various levels of detail through drill up or down Navigates among levels of data ranging from the most summarized up to the most detailed down 0 OLAP Cube OLAP Report I Measures which are data items of interest In the figure below a measure is Store Sales Net I Dimensions which are characteristics of a measure In the figure below a dimension is Product Family OLAP sewers are special products that reacl clata from an operational database perform some preliminary calculations anti then store the results in an OLAP clataloase 65 Data Mining Applications Application of statistical techniques to find meaningful new correlations patterns or trends among massive storehouses of data for classification and prediction Extracting hidden knowledge rules regularities patterns constraints from large volumes of raw data Whereas data warehousing is simply a method for organization of data data mining is a database application that can take advantage of that organization to find hidden patterns in the data Unsupervised data mining o No models or hypotheses developed 0 Apply data mining techniques to data and to search for patterns and structure among all the variables Then develop model and hypotheses o Eg clustering classification Supervised data mining 0 Develop a model prior to analysis and apply statistical techniques to data to estimate parameters of model I 1 prespecified target variable I 2 algorithm is given many values of target variable I 3 The algorithm learns which values of the target dependent variable are associated with the values of the predictor independent variables 0 Eg regression analysis suitable for continuous quantitative data 66 Data Warehouses and Data Marts Data Warehouse Metadata Data Extra cti o hi i r 1 Cleaning Data Preparation ngrarnsi Business Intelligence Users Data Mart Specific subject oriented repository of data designed to answer specific questions for a specific set of users 0 An organization could have multiple data marts serving the needs of marketing sales operations collections etc 0 Usually one dimensional model as a starschema OLAP cube made of a fact table and multiple dimension tables Data Warehouse DW Single organizational repository of enterprise wide data across many or all subject areas 0 Authoritative repository of all the fact and dimension data at an atomic level data consistency data integrity data dictionary You cannot purchase data marts and grow into data warehouses o lfjust buy data marts flawed architectural structure redundant information inconsistent information interface problems Coordination across departments 0 Data mart I Difficult to coordinate across multiple departments I Each department will have own view of how a data mart should look I The data mart they use will be specific to them 0 Data warehouse I Designed around the organization as a whole I Generally be owned by the entire company Granularity of data 0 Data warehouses Granular ie at the atomic level 0 Data marts Not very granular at all Amount of info 0 Data warehouses contain larger amounts of information 0 Data marts Summarized and department focused 67 Knowledge management Applications What is KM o Create value for an organization from its intellectual capital 0 Share knowledge among and between employees managers suppliers and customers 0 Include knowledge that is known to exist in documents or employees brains 0 Collection of processes that govern the creation dissemination and utilization of knowledge 0 Affect our actions and decisions both of which are enabled by knowledge of some type 0 By improving quality of these knowledge processes can improve quality of actions and decisions 0 Not a quota technology thingquot or a quotcomputer thingquot o Concerned with the entire process of discovery and creation of knowledge dissemination of knowledge and the utilization of knowledge 0 Management of the organization towards the continuous renewal of the organizational knowledge base I creation of supportive organizational structures I facilitation of organizational members I putting lTinstruments with emphasis on teamwork and diffusion of knowledge as eg groupware into place 0 Reporting and data mining are used to create new information from data knowledgemanagement systems concern the sharing of knowledge that is known to exist Benefits of KM o fosters innovation by encouraging the free flow of ideas 0 improves customer service by streamlining response time o boosts revenues by getting products and services to market faster 0 enhances employee retention rates by recognizing the value of employees knowledge and rewarding them for it o streamlines operations and reduces costs by eliminating redundant or unnecessary processes 0 preserves organizational memory by capturing and storing the lessons learned and best practices of key employees 0 better decisions particularly at the working level front lines 0 Better decisions are achieved by spending less time on information gathering and more on the creative process 0 Decision support systems help with the analysis but are still driven by the ability to find relevant information Knowledge assets are data documents and employees Sharing Document content 0 O Indexing I Single most important content function in KM applications I Easily accessible and robust means of determining if content exists and includes a link to obtain the content RSS Real Simple Syndication I Standard for subscribing to content sources on Web sites I RSS Reader program that helps users subscribe to content sources I periodically check sources for new or updated content through RSS feeds I place content summaries in an RSS inbox with a link to the full content Expert systems 0 000000 Capture human expertise and format it for use by nonexperts Rulebased systems that use ifthen rules Gather data from people rather than using datamining techniques Difficult and expensive to develop Difficult to maintain because the rules are constantly changing Have been unable to live up to the high expectations set by their name CASE MYCIN I Technology gives diagnosis and recommends therapy I Ethical and legal issues related to the use of computers in medicine I Main difficulty Extraction of the necessary knowledge for the inference engine to use from the human expert in the relevant fields into the rule base the socalled knowledge engineering I Problem State of technologies for system integration especially at the time it was developed 68 How are Bl applications Delivered Metadata Operational data REM Data warehouse Data mart Content material 6 Human interviews an ill DESI Data2539 u meg Bl Application I Any BI Tool Device Bl users Web site v Portal Application server Browser via computer or PDA Custom interface Alerts via email OLAP 39 Other reports 39 Market basket Decision tree or phone Other data mining 39 Export to Of ce or 39 Content indexing other application 39 RSS feed Web service 39 Expert system Bl System Management functions of Bl server 0 O O Maintains metadata about the authorized allocation of Bl results to users Tracks what results are available who is authorized to view them and when the results are provided to users Users can pull their results from a Web site using a portal server with a customizable user interface A server can automatically push information to users through alerts which are messages announcing events as they occur A report server a special server dedicated to reports can supply users with information Delivery function of a BI server 0 O O 0 Tracks authorized users Tracks the schedule for providing results to users Exception alerts that notify users of an exceptional event Procedures used depends on the nature of the BI system I Procedures tend to be more flexible than those in an operational system because users of a BI system tend to be engaged in work that is unstructured I Procedures are determined by unique requirements of users 69 Succe s vs Failure Guidelines for Success 0 A knowledge leader or champion someone who actively drives the knowledge agenda forward creates enthusiasm and commitment Top management support a CEO who recognizes the value of knowledge and who actively supports the knowledge team in its work A clear value proposition identification ofthe link between knowledge and the bottom line business bene t New measures of performance and appropriate rewards A compelling vision and architecture frameworks that drive the agenda forward Creation of a culture that supports innovation learning and knowledge sharing This is usually supported by appropriate reward mechanisms A technical infrastructure that supports knowledge work from simple knowledge support tools to Intranets and ultimately more sophisticated groupware and decision support Simulation data mining and good document management also have a role 0 Systematic knowledge processes supported by specialists in information management librarians but with close partnership between users and providers of information Usually the knowledge agenda develops through a process of evaluation from pilot proiects that are used to build capabilities and derive learning for subsequent applications Issues and Challenges 0 The biggest challenge reported by those practitioners we have met is that of changing the culture from quotknowledge is powerquot to quotknowledge sharing is powerquot Finding time with so many initiatives vying for attention it is easy to sideline more challenging issues like knowledge management ntroversion afraid to learn from outsiders or expose internal operations to customers Too focused on detailed process rather than the big picture and the more chaotic process of knowledge creation Treating it as oneoff project or quickwin knowledge management is a commitment to the long term the organization s future prosperity Individual disciplines and 39turf wars39 knowledge management goes beyond the remit of any single function or discipline All functions must collaborate Organizational recognition and reward systems usually do not sufficiently recognize knowledge contributions They are linked to traditional financial measures None of these challenges are insurmountable Implementing successful knowledge management requires a systematic change and project management approach However it is more than just a project Over time knowledge management changes the way that people work so that their individual knowledge is more effectively harnessed for the benefit of all