Chapter 9: Business Intelligence Systems

  • Introduction
    • BI systems - IS that can produce patterns, relationships, and other information from organizational structured and unstructured data + from external, purchased data
  • Q9-1: How do organizations use business intelligence (BI) systems?
    • Business Intelligence (BI) systems - identifying patterns, relationships, and trends for use by business professionals and other knowledge workers > from information systems that process operational, social, and other data
      • Components of BI systems / data sources: operational databases, social data, purchased data, and employee knowledge
    • Business Intelligence - the patterns, trends, relationships, and predictions
    • BI application - the BI system's software component 
      • Analyze data through reporting, data mining, BigData, and knowledge management
    • How do organizations use BI? 4 Collaborative Tasks:
      • Project management, problem solving, deciding, and informing
      • Decision support systems - older term, synonym for decision-making BI systems
    • What are typical BI applications?
      • Identifying changes in purchasing patterns > important life events change what customers buy
      • BI for entertainment > classify customers (Netflix) by viewing patterns
      • Predictive policing > analyze data on past crimes, location, data, time, day of week, etc.
      • Just-in-time medical reporting > real-time data mining and reporting
  • Q9-2: What are the three primary activities in the BI process?
    • Acquire data
      • Data acquisition - obtaining, cleaning, organizing, relating, and cataloging data
    • Perform analysis
      • BI analysis - creating business intelligence
      • Reporting, data mining, BigData, knowledge management
    • Publish results 
      • Publish results - delivering business intelligence to knowledge workers who need it
      • Push publishing - without any request from user, delivers BI to users
      • Pull publishing - user is required to request BI
    • Ethics Guide: Unseen Cyberazzi
      • Data broker or aggregator acquires / purchases consumer and other data from public records, retailers, Internet cookie vendors, social media trackers, and other sources
      • Data broker enable you to view data stored about you, but difficult to learn how to request your data
  • Q9-3: How do organizations use data warehouses and data marts to acquire data?
    • Data warehouses - facility that manages BI data of organization
      • Functions of warehouses: obtain, cleanse, organize & relate, and catalog data
      • Basic report and simple analysis not recommended for security and control reasons
      • Operational data is structured for fast and reliable transaction processing
      • Data warehouses include data purchased from outside sources
    • Data warehouse metadata database - holds metadata concerning the data
      • Note: BI users = specialists in data analysis vs. knowledge workers = nonspecialist users of BI results
    • Problems with operational data
      • Dirty data, missing values, inconsistent data, data not integrated, wrong granularity, too much data
      • Granularity - level of detail represented by the data > can be too fine or not fine enough > better to have too fine than too coarse
    • Data warehouses vs. Data marts
      • Data mart - smaller than the data warehouse, it is a data collection that addresses the needs of a particular department or functional area of the business
      • Data warehouse = distributor in a supply chain
      • Data mart = retail store in a supply chain
  • Q9-4: How do organizations use reporting applications?
    • Create meaningful information from disparate data sources & deliver information to user on time
    • Reporting application - inputting data from one or more sources using a BI application, and applying reporting operations to that data to produce business intelligence
      • Basic reporting operations: sorting, filtering, grouping, calculating, and formatting
    • RFM Analysis - used to analyze and rank customers according to their purchasing patterns, a technique readily implemented with basic reporting operations 
    • Online Analytical Processing (OLAP) - more generic than RFM, second type of reporting application that provides ability to sum, count, average, and perform other simple arithmetic operations on groups of data
      • Measure - data item of interest
      • Dimension - characteristic of a measure
      • OLAP cube - some software product show displays using three axes
      • Drill down - further divide the data into more detail
  • Q9-5: How do organizations use data mining applications?
    • Data mining - finding patterns and relationships among data for classification and prediction through the application of statistical techniques
    • Unsupervised data mining - a model or hypothesis is not created before running the analysis, instead, a data mining application is applied to the data & the results are observed
      • Analysts create a hypothesis after the analysis to explain the patterns found
      • Cluster analysis - a common unsupervised technique that identifies groups of entities that have similar characteristics
      • Market-basket analysis - technique for determining sales patterns; shows products that customers tend to buy together
        • Cross-selling - fact that customers that buy X also buy Y
        • Support - probability that two items will be purchased together
        • Confidence - conditional probability estimate
        • Lift - ratio confidence to the base probability of buying an item
    • Supervised data mining - prior to the analysis, a model is developed and statistical techniques are applied to data to estimate parameters of the model
      • Regression analysis - measure the effect of a set of variables on another variable
      • Neural networks - second type, used to predict values and make classifications such as "good prospect" / "poor prospect" customers 
    • Decision Tree - predicting a classification or a value through a hierarchical arrangement of criteria
  • Q9-6: How do organizations use BigData applications?
    • BigData - data collections characterized by huge volume, rapid velocity, and great variety
      • Are at least a petabyte in size, generated rapidly, and has structured data, free-form text, log files, graphics, audio, and video
      • MapReduce - technique for harnessing the power of thousands of computers working in parallel; BigData collection is broken into pieces
      • Hadoop - supported by the Apache Foundation, an open source program that implements MapReduce on thousands of computers
  • Q9-7: What is the role of knowledge management systems?
    • Knowledge management (KM) - creating value from intellectual capital and sharing that knowledge with employees, managers, customers, suppliers, and others who need that capital
      • Benefit organization by improving process quality and increasing team strength
    • What are expert systems?
      • Expert systems - encoding human knowledge, using rule-based systems, in the form of If / Then rules
      • Expert system shells - program that processes a set of rules
      • Drawbacks of Expert Systems:
        • Difficult and expensive to develop
          • Labor intensive
        • Difficult to maintain
          • Changes cause unpredictable outcomes
          • Constantly needs expensive changes
        • Don't live up to expectations
          • Can't duplicate diagnostic abilities of humans
    • What are content management systems?
      • Content management systems (CMS) - knowledge that is encoded in documents; information systems that support the management and delivery of documents including reports, Web pages, and other expressions of employee knowledge
      • Challenges: most are huge, content is dynamic, documents do not exist in isolation of each other, and document contents are perishable
      • CMS alternatives: in-house custom, off-the-shelf, and public search engine
    • How do hyper-socal organizations manage knowledge?
      • Hyper-social knowledge management - application of SM and related applications for management and delivery of organizational knowledge resources
      • Alternative media: 
        • Rich directory - employee directory that includes organizational structure and expertise and the standard name, email, phone, and address
    • Resistance to knowledge sharing:
      • Employees reluctant to exhibit their ignorance + competition
      • Strong management endorsement
      • Strong positive feedback
      • "Nothing wrong with praise or cash ... esp. cash"
  • Q9-8: What are the alternatives for publishing BI?
    • Characteristics of BI Publishing Alternatives
      • Static reports - BI documents that are fixed at the time of creation and do not change
      • Dynamic reports - BI documents that are updated at the time they are requested
      • Subscriptions - user requests for particular BI results on a particular schedule or in response to particular events
    • What are the two functions of a BI server?
      • BI server - purpose-built, Web server application for publishing of business intelligence
      • Management and delivery
  • Q9-9: 2026?
    • Exponentially more info about customers + better data mining techniques
    • Companies able to buy & sell purchasing habits and psyche
    • Singularity > computer systems adapt & create own software without human assistance, machines will create info for themselves
      • Will we know what machines know?