Business Intelligence Dr. Mahdi Esmaeili 1 تعاریف متفاوت از هوش تجاری • هوش تجاری مدیریت درست و موثر اطالعات برای ً به ارتباط بین کاربر هدفی تجاری است و اساسا و سیستمهای فناوری اطالعات مربوط میگردد • هوش تجاری عبارت است از شرح نیازهای سازمان برای تجزیه و تحلیل به همراه گزارشدهی • هوش تجاری رویکردی راهبردی است برای هدفگذاری به صورت سیستماتیک ،ردیابی ،مخابره و نهایتا ً تبدیل و ترجمه سیگنالها و عالئم ضعیف کسبوکار به یکسری اطالعات کاربردی که اساس تصمیمگیری- های راهبردی شوند 2 • هوش تجاری به عنوان تغییرشکلدهندهای آگاه و روشمند است که دادههای مختلف را از منابع مختلف دریافت و به شکلهای جدید تغییر میدهد تا اطالعاتی نتیجهگرا و تجاری را فراهم کند • هوش تجاری مبحث بسیار وسیع است که کارکردها تعاریف متفاوت از هوش تجاری معمول عنصر اصلی آن ا • هوش تجاری که انبار داده محسوب میشود برای انجام تجزیه و تحلیلهای پیچیده و بهبود عملکرد در جستجوهای پایگاه داده – که شامل هزاران رخداد است -ایجاد و بهینهسازی شده است .هوش تجاری در واقع برای ایجاد ارزش در سازمانها بر پایه داده و به بیان دقیقتر واقعیات میباشد. 3 • هوش تجاری دسته وسیعی از برنامهها و تکنولوژی- ها را دربر میگیرد که برای جمعآوری ،ذخیره- سازی ،تجزیه و تحلیل و فراهم کردن دسترسی آسان به دادهها به وجود آمده است تا کاربران بنگاه را در اتخاذ تصمیمات درست تجاری کمک کند. همچنین شامل مجموعهای از مفاهیم و روشها است که تصمیمگیریهای تجاری را با استفاده از سیستم- های کاربردی مبتنی بر حقایق بهبود میبخشد. تعاریف متفاوت از هوش تجاری • هوش تجاری ابزاری است که توسط بنگاهها برای جمعآوری ،مدیریت ،تجزیه و تحلیل دادهها و اطالعات اساسی و ساختیافته و یا غیر آن استفاده میشود و این کار با به کارگیری قابلیتهای فناوری اطالعات صورت میپذیرد .هوش تجاری همچنین از دادههای معتبر جمعآوری شده حاصل از فرایندهای عملیاتی روزانه استفاده کرده و با تبدیل این دادهها به اطالعات و دانش از احتماالت و بیخبریها در بنگاه جلوگیری می- کند. 4 • هوش تجاری با فرایندی سیستماتیک سروکار دارد تا با تجزیه و تحلیل و مدیریت دانش و اطالعات درون و برونسازمانی به فرایند تصمیمگیری یک سازمان کمک کرده و آن را بهبود بخشد. • هوش تجاری نه یک محصول است و نه یک سیستم .در • • • • • • • • • • Transaction Processing System (TPS) Office Automation Systems (OAS) Individual Information System (IIS) Organizational Information Systems (OIS) Information System (IS) Management Information System (MIS) Decision Support System (DSS) Strategic Information Systems (SIS) Enterprise Information System (EIS) Executive Information System (EIS) 5 ده های مختلف مدیران و اهمیت تصمیم گیری تصمیمات راهبردی مدیرانًاجرایی (ارشد) تصمیمات تاکتیکی SIS, EIS مدیرانًوًکارمندانً MIS, DSS میانیً(یقهًسفیدها) 6 تصمیمات اجرایی مدیرانًعملیاتیً (فعالیتًهایًدفتریًوًتولیدی OAS, TPS BI decision-support applications facilitate many activities • • • • • • • • • • • • • Multidimensional analysis, for example, online analytical processing (OLAP) Click-stream analysis Data mining (Mining for text, content, and voice) Forecasting Business analysis Balanced scorecard preparation Visualization Querying, reporting, and charting (including just-in-time and agent-based alerts) Geospatial analysis Knowledge management Enterprise portal implementation Digital dashboard access Other cross-functional activities 7 Examples of BI decision-support databases • • • • • • • • Enterprise-wide data warehouses Data marts (functional and departmental) Exploration warehouses (statistical) Data mining databases Web warehouses (for click-stream data) Operational data stores (ODSs) Operational marts (oper marts) Other cross-functional decision-support databases 8 Engineering Stages 9 10 Parallel Development Tracks (for Steps 5–14) 11 Steps Performed in Parallel Development Tracks 12 Core Team Roles and Responsibilities Role Major Responsibilities Application lead developer Designing and overseeing the development of the access and analysis application (e.g., reports, queries) BI infrastructure architect Establishing and maintaining the BI technical infrastructure Business Representative Participating in modeling sessions, providing data definitions, writing test cases, making business decisions, resolving disputes between business units, and improving the data quality under the control of the business unit represented by this role Data Administrator Performing cross-organizational data analysis, creating the project-specific logical data models, and merging the logical data models into an enterprise logical data model Data mining Expert Choosing and running the data mining tool; must have a statistical background Data quality analyst Assessing source data quality and preparing data-cleansing specifications for the ETL process Database administrator Designing, loading, monitoring, and tuning the BI target databases 13 Core Team Roles and Responsibilities Role Major Responsibilities ETL lead developer Designing and overseeing the ETL process Meta data administrator Building or licensing (buying), enhancing, loading, and maintaining the meta data repository Project manager Defining, planning, coordinating, controlling, and reviewing all project activities; tracking and reporting progress; resolving technical and business issues; mentoring the team; negotiating with vendors, the business representative, and the business sponsor; has overall responsibility for the project Subject matter Expert Providing business knowledge about data, processes, and requirements 14 Extended Team Roles and Responsibilities Role Major Responsibilities Application developer(s) Coding the report programs, writing query scripts, and developing the access and analysis applications BI support (help desk staff) Mentoring and training the business staff Business sponsor Championing the BI initiative and removing businessrelated roadblocks for the BI project team ETL developer(s) Coding the ETL programs and/or preparing the instructions for the ETL tool IT auditor or QA analyst Determining the risks and exposures of the BI project due to internal lack of controls or external forces Meta data repository developer(s) Coding the meta data repository migration programs to load the meta data repository database; providing meta data reports and an online help function Network services staff Maintaining the network environment Operations staff Running the batch processes for the ETL cycles, the access and analysis application, and the meta data repository 15 Extended Team Roles and Responsibilities Role Security officer Major Responsibilities Ensuring that security requirements are defined and that security features are tested across all tools and databases Handling limited responsibilities on the BI project, such Stakeholders (other business representatives or as reviewing and ratifying the cross-organizational standards and business rules the BI project team uses IT managers) or develops Strategic architect Managing the overall technical infrastructure for the organization, including the BI technical infrastructure Technical services staff Maintaining the hardware infrastructure and the operating systems Testers Testing programming code created by the developers from the ETL, Application, and Meta Data Repository tracks Tool administrators Installing and maintaining the developer tools and the access and analysis tools Web developer(s) Designing the Web site and creating the Web pages for displaying reports and queries on the intranet, extranet, or Internet Web master Setting up the Web server and Web security 16 Business Justification Components 17 Benefit Categories 18 Revenue increase • • • • Identification of new markets and niches More effective suggestive selling Faster opportunity recognition Faster time to market 19 Profit increase • Better targeted promotional mailings • Early warning of declining markets • Identification of under-performing product lines or products • Identification of internal inefficiencies • More efficient merchandise management 20 Customer satisfaction improvement • Improved understanding of customer preferences • Improved customer-to-product matching • Up-selling to customers • Increased repeat business • Faster resolution of customer complaints 21 Savings increase • Reduction in wasted or out-of-date merchandise • Reduction in requests for customized reporting Market share gain • Increased numbers of customers who defect from the competition • Much higher customer retention rate as compared with previous years and with the competition 22 Risk Assessment • • • • • • The technology used for implementing the project The complexity of the capabilities and processes to be implemented The integration of various components and of data The organization and its financial and moral support The project team staff's skills, attitudes, and commitment levels The financial investment in terms of ROI Green = low risk—go ahead with the project Yellow = medium risk—caution, proceed slowly Red = high risk—stop, reevaluate before proceeding 23 Basic Risk Assessment Matrix Level of Risk Variable Green (Low) Yellow (Medium) Red (High) Technology Experienced with mature technology Minimal experience with technology New technology, little experience Complexity Simple, minimal workflow impact Moderate, some workflow impact Mission critical, will require extensive reengineering Integration Stand-alone, no integration Limited integration required Extensive integration required Organization Solid internal support Supportive to a large extent Little internal support Project team Business experience, Some business business-driven, experience, businesstalented, great attitude driven, talented, fair attitude Financial Investment Possible ROI within a very short time Possible ROI within a moderate time frame No business experience, only technology-driven, limited talent, bad attitude Possible ROI after a few years 24 Case Study: A Detailed Risk Assessment Matrix (1-3) Level of Risk Variable Green (Low) Yellow (Medium) Red (High) Project requirements: ad hoc reporting Supports every critical ad hoc reporting requirement Supports most critical ad hoc reporting requirements Fails to support critical ad hoc reporting requirements Project requirements: AS/400 Supports every key business requirement Supports most key business requirements Fails to support key business requirements Business workflow support Supports business workflow seamlessly Requires some manual intervention Requires significant manual intervention Architecture evaluation Well-architected application Existence of some architectural issues Poorly architected application Extensibility into subsequent releases Fully extensible into subsequent releases Extensible for most requirements Not extensible into subsequent releases Logical data model: completeness All information requirements met Most information requirements documented Significantly mis-sing information requirements Logical data model: extensibility Fully extensible Some extensibility issues Not extensible Meta data (business and technical) Complete and easily maintainable Incomplete or not easily maintainable Not incorporated 25 Case Study: A Detailed Risk Assessment Matrix (2-3) Level of Risk Variable Green (Low) Yellow (Medium) Red (High) Physical data model: completeness Complete and tuned Complete but not tuned Incomplete, cannot be evaluated Physical data model: extensibility for new product types Fully extensible for new Limited product type product types extensibility Incomplete, cannot be evaluated Physical data model: source system feeds Acceptable design support for source systems Performance or timing concerns Incomplete, cannot be evaluate Interfaces (external and internal) Supports external and internal interfaces Limited support for external and internal interfaces Poor support for external and internal interfaces Analysis dimensions and measures: adding new product lines Easy to add Can be added, but requires significant cube reconstruction Cannot be evaluated at the current time Analysis dimensions and measures: adding new tools for data analysis Proposed cubes and set Proposed cubes and set of Proposed cubes and set of dimensions sufficient dimensions provide of dimensions to support the business minimum sufficiency insufficient analysts Use of meta data repository Fully developed Limited meta data support No meta data support 26 Case Study: A Detailed Risk Assessment Matrix (3-3) Level of Risk Variable Green (Low) Yellow (Medium) Red (High) Loading of the BI target databases Load procedures established and perform well Load procedures poorly documented or perform poorly Load procedures not developed, cannot be evaluated Physical database issues Effective and efficient physical database design Minor issues with physical Physical database design database design incomplete, cannot be evaluated Performance issues Conforms to stated performance requirements Some performance issues Cannot be evaluated at this time Systems management issues: maintenance Support procedures well established and documented Limited support documentation Support issues Backup and disaster Backup and disaster recovery procedures recovery procedures developed and installed developed but not installed No thought given to backup and disaster recovery procedures Security implementation Satisfies application needs and is easy to maintain Security design incomplete, cannot be evaluated Difficult to maintain No support procedures 27 Business Case Assessment Activities 28 Deliverable Resulting (Step 1) 1.Business case assessment report - Strategic business goals of the organization - Objectives of the proposed BI application - Statement of the business need (business problem or business opportunity) - Explanation of how the BI application will satisfy that need - Ramifications of not addressing the business need and not committing to the proposed BI solution - Cost-benefit analysis results - Risk assessment - Recommendations for business process improvements to the operational systems or to the operational business processes and procedures The assessment report should also have a one- or two-page executive overview that summarizes the details of the report. 29 Roles Involved in Step 1 • • • • • Business representative Business sponsor Data quality analyst Project manager Subject matter expert 30 Risks of Not Performing Step 1 no strong business driver and does not support a strategic business goal. 31