ISQS 3358: Business Intelligence Introduction Spring, 2016 Instructor: Zhangxi Lin Office: BA E311 Phone: Homepage: Class meetings: MWF 1-1:50p, BA103 Office hours: MWF 2:30-3:30p, or by appointment 1

Course Description Business intelligence (BI) is referred to as applications and technologies which are used to gather, provide access to, and analyze data and information about their company operations. Three main topics ◦ Data warehousing ◦ Big Data ◦ Data analysis 2

Driving Force - Big Data A collection of data sets so large and complex that it becomes awkward to work with using on-hand database management tools. Difficulties include capture, storage, search, sharing, analysis, and visualization. ate smaller sets with the same total amount of data. Videos ◦ What is big data 1’33” What is big data ◦ Big Data Analytics 3’05” Big Data Analytics 8/14/2012 Copyright

ISQS7339, Fall

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Big Data Companies IBM Oracle Facebook LinkedIn Cloudera (Hortonworks) Yahoo Amazon Google 7

Data, information, and knowledge Data – a collection of raw value elements or facts used for calculating, reasoning, or measuring. Information – the result of collecting and organizing data in a way that establishes relationship between data items, which thereby provides context and meaning Knowledge – the concept of understanding information based on recognized patterns in a way that provides insight to information. ISQS 6339, Data Mgmt & BI 8

What is Business Intelligence A Simple Definition: The applications and technologies transforming Business Data into Action ◦ Business intelligence (BI) is a business management term  refers to applications and technologies which are used to gather, provide access to, and analyze data and information about their company operations. ◦ Business intelligence systems can help companies gain more comprehensive knowledge of the factors affecting their business, and help companies to make better business decisions. YouTube: ◦ What is BI? – B, 2’ What is BI? ◦ Global warming 0’31” Global warming ◦ World Economy & Population 2’45” World Economy & Population ◦ Microsoft Business Intelligence Surface Demo 6’34” Microsoft Business Intelligence Surface Demo ISQS 6339, Data Mgmt & BI 9

The process of BI ISQS 6339, Data Mgmt & BI 10 Data -> information -> knowledge -> actionable plans Data -> information: the process of determining what data is to be collected and managed and in what context Information -> knowledge: The process involving the analytical components, such as data warehousing, online analytical processing, data quality, data profiling, business rule analysis, and data mining Knowledge -> actionable plans: The most important aspect in a BI process

Actionable Knowledge ISQS 6339, Data Mgmt & BI 11 An information asset retains its value on if the converted knowledge is actionable. ◦ Need some methods for extracting value from knowledge ◦ This is not a technical issue but an organizational one – need empowered individuals in the organization to take the action ◦ There is an issue of Return on Investment (ROI)

BI Problems ISQS 6339, Data Mgmt & BI 12 Structured ◦ Detecting Credit card fraud ◦ Setting Loan parameters ◦ Market segmentation/Mass customization ◦ Deciding Marketing mix ◦ Customer Churn ◦ Reducing employee turnover ◦ Improving Quality/Efficiency ◦ … Unstructured ◦ Data exploration ◦ Utilization of resources (stored knowledge) to maximum effectiveness ◦ …

BI Applications ISQS 6339, Data Mgmt & BI 13 Customer Analytics ◦ Customer profiling ◦ Targeted marketing ◦ Personalization ◦ Collaborative filtering ◦ Customer satisfaction ◦ Customer lifetime value ◦ Customer loyalty Sales Channel Analytics ◦ Marketing ◦ Sales performance and pipeline

BI Applications (2) ISQS 6339, Data Mgmt & BI 14 Supply Chain Analytics ◦ Supplier and vendor management ◦ Shipping ◦ Inventory control ◦ Distribution analysis Behavior Analysis ◦ Purchasing trends ◦ Web activity ◦ Fraud and abuse detection ◦ Customer attrition ◦ Social network analysis

The Evolution of Business Intelligence ISQS 6339, Data Mgmt & BI 15 1 st Generation – Traditional analytics (query and reporting) 2 nd Generation – Traditional generation (OLAP, data warehousing) 2.5 nd Generation – New traditional generation 3 rd Generation - Advanced analytics ◦ Rules, predictive analytics and realtime data mining ◦ Stream analytics

ISQS 6339, Data Mgmt & BI 16 Business Intelligence Classifications Traditional Analytics 1 st Generation Analytics (Query & Reporting) 2 nd Generation Analytics (OLAP, Data Warehousing) Advanced Analytics/Optimization Rules Predictive Analytics Real-time and traditional Data Mining Stream Analytics* Real-time, continuous, sequential analysis (ranging from basic to advanced analytics) * In lieu of stream analytics, “embedded analytics,” although architecturally different, could potentially play the same role 3 rd -Generation BI Legacy BI “New Traditional” Analytics “2.5-Gen” Analytics (In-Memory OLAP, Search-Based) Source: Bill O’Connell IBM, Aug 2007

ISQS 6339, Data Mgmt & BI 17 Business Intelligence Use Cases Traditional Analytics 1 st Generation Analytics (Query & Reporting) 2 nd Generation Analytics (OLAP, Data Warehousing) Advanced Analytics/Optimization Rules Predictive Analytics Real-time and traditional Data Mining Stream Analytics* Real-time, continuous, sequential analysis (ranging from basic to advanced analytics) * In lieu of stream analytics, “embedded analytics,” although architecturally different, could potentially play the same role “New Traditional” Analytics “2.5-Gen” Analytics (In-Memory OLAP, Search-Based) Example Target Solutions: Fraud Detection / Risk CRM Analytic Supply Chain Optimization RFID / Spatial Data Other High-Volume Focus on what is happening RIGHT NOW Real-Time Threshold Focus on what will happen Analytic applications that apply statistical relationships in the form of RULES Focus on what did happen Turning data into information is limited by the relationships which the end-user already knows to look for. Data mining to determine why something happened by unearthing relationships that the end-user may not have known existed. Source: Bill O’Connell IBM, Aug 2007

SAS Enterprise Guide SAS Enterprise Guide is available in the Citrix server. ◦ Download Citrix Receiver from ◦ Use your eRaider ID and password from Citrix Receiver to access for the applications. Potential problem: The Citrix server could be slow when many users use it simultaneously. 18

Big Data Tools Pentaho: A company that offers Pentaho Business Analytics, a suite of open source Business Intelligence (BI) products, founded in 2004 by five founders, headquartered in Orlando, FL, USA, acquired by Hitachi in 2015 ( ◦ Pentaho Data Integration (PDI) ◦ Pentaho for Big Data ◦ Pentaho Data Mining Tableau Software: Founded in Mountain View, California in January, 2003 by Chris Stolte, Christian Chabot and Pat Hanrahan, headquartered in Seattle, Washington. It produces a family of interactive data visualization products focused on business intelligence. Qlik: Qlik, founded in Lund, Sweden in 1993 as a software company in business intelligence (BI), is a software company based in Radnor, Pennsylvania. Qlik is the provider of QlikView and Qlik Sense, business intelligence & visualization software. 19

Syllabus Textbook and references Deliverables: projects, exercises Exams Grading policy Schedule 20

Your checklist Website ◦ Class home page, Schedule, online Notes Shared network drive ◦ \\TechShare\coba\d\ISQS3358\ \\TechShare\coba\d\ISQS3358\ Citrix application account (download Citrix Receiver at ◦ SAS Enterprise Miner Downloadable materials ◦ E-Textbooks ◦ Datasets ◦ Homework assignments ◦ Slides ◦ Exercises ◦ Demonstrative Videos 21

Your opportunities to contact BI industry Student Poster, SAS Analytics 2015 Conference, ◦ October 26-27, Bellagio, Las Vegas. Check How about this year? 22