Presentation on theme: "CISB594 – Business Intelligence"— Presentation transcript:
1 CISB594 – Business Intelligence Business Analytics and Data VisualizationPart I
2 ReferenceMaterials used in this presentation are extracted mainly from the following texts, unless stated otherwise.
3 Objectives At the end of this lecture, you should be able to: Describe business analytics (BA) and its importance to organizationsList and briefly describe the major BA methods and toolsDescribe how online analytical processing (OLAP), data visualization, and multidimensionality can improve decision makingDescribe advanced analysis methodsCISB594 – Business Intelligence
4 IntroductionMany organizations have amassed vast amounts of data that employers can use to unlock valuable relationship to enable organization to compete and perform successfullyUsing analytical tools, organizations enable decision analysis through access to all relevant data and information
5 The Business Analytics (BA) : An Overview The Essentials of BAAnalytics : The science of analysis.Business analytics (BA)Provides the analysis procedures to BI, tracking data and analyzing them for competitive advantage.Broad category of applications and techniques for gathering, storing and analyzing to help users make better business and strategic decisionsAllows for automating the thinking for decision making
6 The Business Analytics (BA) : An Overview Many tools can be used – the results will be presented in a form of reports, predictions, alerts or graphical presentationsMore advanced applications of BA includes financial modeling, budgeting, resource allocation and competitive intelligence
7 The Business Analytics (BA) : An Overview Example :An analytic application used for credit card scoring for a loan applicationCalculate a credit worthiness scoreAutomatically accept or deny the loan applicationSelect the loan limitSelect which credit card product/deal to suit the applicant
8 The tools and techniques of BA Three major categories of BA analytic tools and techniquesInformation and knowledge discoveryDecision Support and Intelligent SystemVisualizationIllustrated in the following diagram
10 The Business Analytics (BA) Field: An Overview Vendors classify BA tools in several different ways.MicroStrategy’s classification of BA tools:Enterprise reporting - used to generate highly formatted static reports meant for broad distribution to many peopleCube analysis – used to provide simple OLAP multidimensional slice and dice analytical capabilities to business managersAd hoc querying and analysis – used to allow power users to query a database for answersStatistical analysis and data mining - statistical, mathematical and data mining tools are used to perform predictive analysis and to determine cause-and-effect correlationsReport delivery and alerting – report distribution engines to send full reports/alerts to internal/external users, based on subscriptions and schedules or threshold events
11 The Business Analytics (BA) Field: An Overview Vendors classify BA tools in several different ways.SAP’s classification of strategic enterprise managementThree levels of supportOperational – SAP R/3 mainly supports transaction processing on the operational levelManagerial – middle managers can use SAP/R3 to access all reports, arranged by functional areasStrategic - SAP SEM (Strategic Enterprise Management)
12 The Business Analytics (BA) Field: An Overview Major Capabilities of BA ToolsDrill-downThe investigation of information in detail (e.g., finding not only total sales but also sales by region, by product, or by salesperson).Ad Hoc AnalysisAnalysis made at any time, and with any desired factors and relationshipsSlicing and dicingRearranging data so that they can be viewed from different perspectivesException ReportUsing reports to highlight deviation larger than threshold
13 Online Analytical Processing (OLAP) Variety of activities usually performed by users in online system – usually involving generating and answering queries, requesting ad-hoc reports, conducting statistical analysis and building visual presentationAn information system that enables the user, while at a PC, to query the system, conduct an analysis, and so on. The result is generated in seconds
14 Online Analytical Processing (OLAP) OLAP versus OLTPOLTP concentrates on processing repetitive transactions in large quantities and conducting simple manipulationsOLAP involves examining many data items complex relationshipsOLAP may analyze relationships and look for patterns, trends, and exceptionsOLAP is a direct decision support method
15 Online Analytical Processing (OLAP) Types of OLAPMultidimensional OLAP (MOLAP)OLAP implemented via a specialized multidimensional database (or data store).It summarizes transactions into multidimensional views ahead of timeData are organized into cube structure that users can rotate; particularly suitable for financial summaries
16 Online Analytical Processing (OLAP) Types of OLAPRelational OLAP (ROLAP)The implementation of an OLAP on top of an existing relational databaseExtracts data from relational databaseTends to be used on data that has a large number of attributes, where it cannot be easily placed into a cube structure. Example, customer data as oppose to financial data.Web OLAP – accessible from Web BrowserDesktop OLAP – low priced, simple OLAP, performs local analysis from database
17 Online Analytical Processing (OLAP) Four types of processing that are performed by analysts in an organization:Categorical analysis – static analysis based on historical dataExegetical analysis – also based on historical data, and it adds the capability of drill-down analysis (ability to query further down into data to determine the detail data that were used to obtain the derived value)Contemplative analysis – allows user to change a single value to determine its impactFormulaic analysis - allows changes to multiple variablesOLAP tools are designed to support all of the above activities
18 Online Analytical Processing (OLAP) OLAP Products Evaluation Rules: Codd’s 12 Rules for OLAPMultidimensional conceptual view for formulating queriesTransparency to the userEasy accessibility: batch and online accessConsistent reporting performanceClient/server architecture: the use of distributed resourcesGeneric dimensionality7. Dynamic sparse matrix handling8. Multiuser support rather than support for only a single user9. Unrestricted cross- dimensional operations10. Intuitive data manipulation11. Flexible reporting12. Unlimited dimensions and aggregation level
19 Reports and QueriesThe oldest activities of OLAP and BI are using reports and queries.ReportsRoutine reportsAd hoc (or on-demand) reportsMultilingual supportScorecards and dashboardsReport delivery and alertingReport distribution through any touch pointSelf-subscription as well as administrator-based distributionDelivery on-demand, on-schedule, or on-eventAutomatic content personalization
20 Reports and Queries Ad hoc query A query that cannot be determined prior to the moment the query is issued . User might need to place such a query after seeing a report
21 Multidimensionality Multidimensionality Raw and summary data can be organized in different ways for analysis and presentationThe ability to organize, present, and analyze data by several dimensions, such as sales by region, by product, by salesperson, and by time (four dimensions)Three factors are considered in multidimensional presentationDimensions – products, salespeople, business unitsMeasures - money, sales, sales volumes, head countTime – daily, weekly, monthly, quarterly
22 How multidimensionality works A manager wants to know the sales of a product (by unit or dollar) in a certain geographic area, by a specific salesperson, during a specific month. The answer to such question can be provided fast if the data is organized in multidimensional database or if query or related software products are designed for multidimensionality. This will allow users to navigate through the many dimensions and levels of data via tables or graphs and are able to make quick interpretations, such as uncovering significant deviations or important trends.
23 Multidimensionality Multidimensional database A database in which the data are organized specifically to support easy and quick multidimensional analysisData cubeA two-dimensional, three-dimensional, or higher-dimensional object in which each dimension of the data represents a measure of interestProvides an opportunity to retrieve decision support information in an efficient way.
24 Multidimensionality Cube The term cube refers to a subset of highly interrelated data that is organized to allow users to combine any attributes (e.g., stores, products, customers, suppliers) with any metrics (e.g., sales, profit, units, age) to create various two-dimensional views, or slices, that can be displayed on a computer screen
25 Multidimensionality More on cube Example : A database contains transaction information relating company sales of products (p) to a customer (c ) at different store (s) locations. The data cube formed from this database is a three dimensional representation, with each cell ( p, c, s). The cube can be used to retrieve information within the database about, for example which store should be given a certain product to sell in order to make greater profit.
27 Multidimensionality Limitations of dimensionality The multidimensional database can take up significantly more computer storage room than a summarized relational databaseMultidimensional products cost significantly more than standard relational productsDatabase loading consumes significant system resources and time, depending on data volume and the number of dimensionsInterfaces and maintenance are more complex in multidimensional databases than in relational databases
28 Advanced Business Analytics While OLAP concentrates on reporting and queries, a more sophisticated way of analyzing data and information is neededUsers today will want to perform statistical and mathematical analysis such as hypothesis testing, multiple regression, churn prediction and customer scoring models. Such investigation cannot be done with basic OLAP and will require special tools, including data mining and predictive analysis – hence, advanced business analytics
29 Advanced Business Analytics A major step in managerial decision making is forecasting or estimating the results of different alternative courses of actionsTwo methods that can be used for advanced business analytics areData mining and predictive analysisData miningPredictive analysis
30 Advanced Business Analytics Data miningTools that would automatically extract hidden, predictive information from databases, search for pattern in large transaction database. OLAP can only answer questions you are certain to ask, whereas data mining answers questions you don’t necessarily know you should ask (to be discussed further in the next chapter)Predictive analysisUse of tools that help determine the probable future outcome for an event or the likelihood of a situation occurring. These tools also identify relationships and patterns
31 Data Visualization Data visualization A graphical, animation, or video presentation of data and the results of data analysisVisual technologies can condense 1000 numbers in one picture and make decision support applications more attractive and understandableThe ability to quickly identify important trends in corporate and market data can provide competitive advantageCheck their magnitude of trends by using predictive models that provide significant business advantages in applications that drive content, transactions, or processes
32 Data Visualization New directions in data visualization Dashboards and scorecardsVisual analysisFinancial data visualization
35 Now ask if … You are now be able to: Describe business analytics (BA) and its importance to organizationsList and briefly describe the major BA methods and toolsDescribe how online analytical processing (OLAP), data visualization, and multidimensionality can improve decision makingDescribe advanced analysis methodsCISB594 – Business Intelligence