Overview f BI and rle f DW in BI Business Intelligence & Why is it ppular? Business Intelligence Steps Business Intelligence Cycle Example Scenaris State f Business Intelligence Business Intelligence Tls Rle f Data Warehuse in BI Characteristics f data in DW Demand Oriented Questins What is the effectiveness f varius gvernment prgrams? What is the cst effectiveness f varius prgrams? What is the breakdwn f the client base by prgram, service, demgraphic makeup? What is the adherence f the prgrams t state wise with respect t regulatins? What are the administrative csts f running district, state, and regin based prgrams? s n The slide shws the Gartner reprt. If yu carefully view the graph shwn n the slide, much f the data t answer these questins exists and mre is available but there is a grwing gap present in the ability f rganizatins t analyze it. Challenges t accessing data in answering questins Multiple surces f data and reprting systems Difficulty in lcating and addressing infrmatin Unreliable infrmatin Pressures t lwer csts and imprve services Infrmatin requests take days r weeks t fulfill Re-keyed data ensuring errrs creep int results The techniques f BI are useful t answer these questins. Business intelligence invlves the gathering, management, and analysis f data fr the purpse f turning that data int useful infrmatin which is then used t imprve decisin making. Organizatins can then make mre strategic decisins abut hw t administer clients and prgrams. These practices can als reduce perating csts thrugh mre effective financial analysis, risk management, and fraud management Business Intelligence represents a fundamental shift in the purpse, bjective and use f infrmatin Business Intelligence Slutins are... "... slutins which enable an end-user t quickly and easily analyze rganizatinal data t make intelligent decisins..." "... systems that put infrmatin in the hands f end-users..." "...the cmbinatin f data warehuse and end-user data access and analysis tls..."
"...an investment in infrmatin technlgy that can assist gvernments in managing limited fiscal resurces..." Relatively new term but the it is synnymus with a range f applicatins that have been arund fr years. That means BI is nthing but An umbrella term that cmbines architectures, tls, databases, applicatins, and methdlgies by building a system which basically assist the rganizatins t make mre infrmed and faster decisins. Business Intelligence Business Intelligence is the prcess f transfrming data int infrmatin and thrugh discvery transfrming that infrmatin int knwledge - Gartner Grup It is the cnversin f data int infrmatin in such a way that the business is able t analyse the infrmatin t gain insight and take actin Smetimes used synnymusly with the infrmatin available in an enterprise fr making strategic decisins Business Intelligence is a discipline f develping infrmatin that is cnclusive, factbased and actinable. Why Business Intelligence Ppular? Business Intelligence gives cmpanies ability t discver and utilize infrmatin they already wn, and turn it int the knwledge that directly impacts crprate perfrmance Tactical Descriptin: Trends, patterns, clustering, planning, cause & effect Why? Hw? When? What? Decisin-making supprt Reprting and QA Frecasting Human-sized reprts BI Questins What happened? What were ur ttal sales this mnth? What s happening? Are ur sales ging up r dwn, trend analysis Why? Why have sales gne dwn? What will happen? Frecasting & What If Analysis What d I want t happen? Planning & Targets Where is Business Intelligence applied?
Operatinal Efficiency ERP Reprting KPI Tracking Prduct Prfitability Risk Management Balanced Screcard Activity Based Csting Glbal Surcing Lgistics Custmer Interactin Sales Analysis Sales Frecasting Segmentatin Crss-selling CRM Analytics Campaign Planning Custmer Prfitability The architecture f BI cnsists f three cmpnents. They are Data Warehuse, Business Analytics and Perfrmance management. In this curse we are discussing nly data warehuse cmpnent nly. Data Warehusing Need fr Data Warehusing Integrated, cmpany-wide view f high-quality infrmatin. Separatin f peratinal and analytical systems and data. Data Warehuse A fundatin f a cmprehensive business intelligence system Business Intelligence Sftware Integratin f OLAP multi-dimensinal technlgy Relatinal database technlgy Web technlgy Scalability fr warehusing Flexibility, perfrmance and business views Web deplyment Business Intelligence Tls Sftware that enables business users t see and use (analyze) large amunts f cmplex data. Database Related Data Strage Sftware (DBMS) Query and Reprting Tls
Data Warehusing Related Data Warehuse/ Data Mart Creatin Tls OLAP Tls Data Mining Related Data Mining Tls Other Special Purpse Tls And with these types f applicatin areas, cupled with the adhc, flexible nature f BI, having clear sight f yur business gals is very imprtant. Althugh the technlgy integrates data surces the ld prblems still exist with data quality & cmplexity Types f Infrmatin used in BI? What types f infrmatin des BI cnsider? Custmer infrmatin Cmpetitrs Business partners Ecnmic Envirnmental Internal peratins This infrmatin is used t make effective and gd quality business decisins Business Intelligence Data Business Intelligence is the prcess f transfrming data int infrmatin and thrugh discvery transfrming that infrmatin int knwledge - Gartner Grup It is the cnversin f data int infrmatin in such a way that the business is able t analyse the infrmatin t gain insight and take actin Smetimes used synnymusly with the infrmatin available in an enterprise fr making strategic decisins Business Intelligence is a discipline f develping infrmatin that is cnclusive, factbased and actinable. Knwn facts that can be recrded and stred n cmputer media (raw facts). Infrmatin Data prcessed int a frm that has a meaning and is useful. Knwledge Knwledge is based n infrmatin and it implies respnsibility and cmmitment t a decisin.
Decisin Ignites actin based n knwledge. At ne side due t rapid develpment f technlgies, data is grwing at rapid rate and at the same time users are expecting a sphisticated infrmatin. The slutin is t uncver the hidden infrmatin. Characteristics f data in DW DW can be viewed as an infrmatinal system with the fllwing attributes It is a database designed fr analytical tasks using data frm multiple applicatins. Supprts small n. f users with lng interactins. Usage is read-intensive. Cntent is peridically updated (mstly additins) Cntains a few large tables Benefits f DW Access t a wide variety f data Results can be presented in a variety f frmats (reprts, graphs) Enhances the value f peratinal business applns. Cst f prduct intrductin cmes dwn with target marketing campaigns. Better decisins at lw cst. Clear picture n asset and liability mgmt, enterprise wide purchasing and inventry patterns. Maintain gd relatins with custmers by knwing their requirements. Limitatins f DW DW cllects and reprt data that already exists. If an rganizatin wishes t analyze the custmers by zip cde but addresses are nt captured then it is nt pssible. Risks f DW Prject team structure and cmpsitin r t the culture f the enterprise Technlgical: these risks relate t the planning, selectin and use f warehusing technlgies. Pr scalability f architectures, insufficient skills f implementers.