Business Intelligence

Business Intelligence: Effective Decision Making Bellevue College Linda Rumans IT Instructor, Business Division Bellevue College lrumans@bellevuecollege.edu Current Status What do I do??? How do I increase sales???? How do I make my product better??? Business Users Mountains of Data Mountains of Data  From Operational Systems  ERP (Enterprise Resource Planning) – Sales/Order – Inventory   Customer Relationship Management (CRM) Web Sites – Orders – Click-stream  … Mountains of Data   Organizations have lots of data Data is not in a form that is useful to decision-makers – – Not easy to review Not informative nor insightful Today’s Information Flow  Business in 90‟s invested in transactional systems: – – – – – Supply Chain Management (SCM) Customer Relationship Management (CRM) Enterprise Resource Planning (ERP) Manufacturing Resource Planning (MRP) Finance (budget, forecasting and reporting) Proliferation of Data Sales Reporting Layer Procurement Operations Finance Transaction Layer CRM SCM MRP Finance Silos of data by functional area Data from Disparate Sources Sales Reporting Layer Sales Sales Sales Transaction Layer Div 2 Region: B Region: A Div 1 Silos of data within large organizations Business Intelligence   Business is now investing in Business Intelligence Business Intelligence is about making effective business decisions What is BI? The process by which an organization manages large amounts of data, extracting pertinent information, and turning that information into knowledge upon which actions can be taken. What is BI? Business intelligence (BI) is a broad category of application programs and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI    Involves PEOPLE and Technology Involves using a rational approach to management Involves a continuous cycle of measurement, adjustment & re-measurement The BI Cycle BI start Reasons for BI   BI enables organizations to make well informed business decisions and gain competitive advantage. BI enables organizations to use information to quickly and constantly respond to changes. Benefits of BI     Improved performance based upon timely and accurate information Elimination of guesswork Expedited decision making Early visibility of changes: – – – Customer buying patterns Supply chain activity Financial arrangements Benefits of BI   “Single Version of the truth” Accurate, timely data available to all levels of the organization To Note: Although we call it Business Intelligence, the concepts and techniques are applicable to almost any organization including those in health care, biotech, education, government … BI Activities BI applications include the activities of: • decision support, • query and reporting, • online analytical processing (OLAP), • statistical analysis, • forecasting, and • data mining. BI Users  There are many different users who can benefit from business intelligence – – – – – Executives Business Decision Makers Information Workers Line Workers Analysts BI SolutionsHow to make it happen  Two main components: – – Data Consolidation and Storage Data Retrieval, Analysis and Presentation BI Curriculum      Multi-Dimensional Analysis Data Warehousing Data Mining Dimensional Modeling Data Visualization The Problem How do I retain customers? How do I increase sales???? GAP How do I make my product better??? Business People Mountains of Data Bridging the Gap  Need data storage structures to facilitate fast analysis of huge volumes of data Need software to provide access to the data, allow flexible manipulation, and provide meaningful presentation  Data Storage Structures  Multi-Dimensional Databases  Cubes Multi-Dimensional Databases  Measures – – – Any quantitative expression Some are designated as Key Performance Indicators (KPI) Appropriate to the business process. How we describe the measures: Product/Customer/Region/Time These are the “By‟s “What were our Customer Sales by Product Line by Region by Quarter for the past two years?”.  Dimensions – – – Logical Structure Multi-Dimensional Databases (Cubes) Multi-Dimensional Database (Cube) Business Intelligence Programs Data Warehouse ODS ODS ODS Relational Database Programs * ODS = Operational Data Store Multi-Dimensional Databases Multi-Dimensional Database (Cube) Software Applications Business Person Reporting Applications Multi-Dimensional Database (Cube) Business Person Analytic Applications Business Person Score Cards Dashboards Analytics  Reporting Applications – – Limited user interaction Fulfill a significant portion of an organization‟s information needs Allow users to visualize and explore data following their train of thought Extensive interactivity  Analytic Applications – – Analytic Application Summary  Students learn to: – – – Create multi-dimensional databases Create professional quality reports Use analytics to provide in-depth data analysis Data Warehousing Designing a Data Warehouse Data Warehouse Topics   Decision Support Systems – history Where data located, owners, definition, how often updated Determine for table structures Requirements Gathering –  Data Analysis – Data Warehouse  ETL Processes & Deliverables – Cleaning & Conforming   Valid, missing Address, gender Dimension Tables Fact Tables – Schemas   Data Consolidation & Storage Customers Sales Procurement Suppliers Operations Finance Shared Reporting Shared Data Layer Data Warehouse Transaction Layer SCM  CRM MRP Finance Operations and financial information is shared across the organization from same core data Data Warehouses Multi-Dimensional Database (Cube) Data Warehouse ODS* ODS ODS *ODS = Operational Data Store How is data consolidated?  This is difficult!!!!! – Data is often spread across multiple systems, stored in different formats, and may even be localized for different countries Transforming Data  Data must be transformed for consistency and meaning – – Transformations may be as simple as copying columns or may be incredibly complex Common transformations include:    Hard-coded changes („T‟ to 1) Looking up values in a table (mapping a customer number across disparate systems) Inserting dummy records and mapping them to unknowns (inserting an „Unknown‟ customer) Cleansing Data  Data must be cleansed to be meaningful – – – – All companies have “bad” data in their systems Data may be missing Data may be inconsistent Data may be wrong Data Warehouses  ETL (extract, transform and load) processes are needed to create data warehouses – This is an arduous and technical process that can account for a large percentage of a BI project cost!!!! Data Mining Data Mining    The process of identifying patterns in data Goes beyond simple querying of the database Goes beyond multi-dimensional database queries as well Data Mining  Data Mining works for problems like: – – – Develop a general profile for credit card customers … Differentiate individuals who are poor credit risks … Determine what characteristics differentiate male & female investors. Data Mining vs. Data Query   Use data query if you already almost know what you are looking for. Use data mining to find regularities in data that are not obvious. Data Mining Applications     Fraud detection Targeted Marketing Risk Management Business Analysis Origins of Data Mining  Mathematics – – Statistics Numerical Analysis   Artificial Intelligence/Machine Learning Computer Science – Data Storage and Manipulation How does Data Mining work?  Uses induction-based learning: The process of forming general concept definitions by observing specific examples of concepts to be learned. How does Data Mining work? What-Cha-Ma-Call-Its NOT What-Cha-Ma-Call-Its How does Data Mining work? Which of these are What-Cha-Ma-Call-Its? Data Mining Process List of Customers: -some bicycle buyers -some not Data Mining Software Model List of Prospective Buyers Model List of Likely Buyers Overview of Mining Strategies Data Mining Strategies Supervised Learning Market Basket Analysis Unsupervised Clustering Note: This representation is over-simplified and data mining strategies are continually being invented. More on our Curriculum Skills   Written communication Problem Solving – – Analytical Troubleshooting Microsoft SQL Server Management Studio SQL Server BI Development Studio SQL Server Reporting Services Pro Clarity  Software – – – – Delivery Methods   Online: Distance Education, reaches wider market Telecourse: tremendous effort to create, but once created easy to deliver – Televised, DVDs, online for homework, exams   Hybrid: Meet once a week, the rest online On campus: evenings only Delivery Methods  Use of Camtasia for – – Software demonstrations PowerPoint lectures  Pod casting Certificates  Business Intelligence Analyst (5 classes) – – Multi-dimensional analysis, data warehousing, data mining, statistics, general business 2 quarters full-time/ 3 quarters part-time  Business Intelligence Developer (4 additional classes) – Dimensional modeling, data visualization, multidimensional II, data warehousing II (more programming with SQL Server)  Web site: www.bcc.ctc.edu/bi Certificates  Relational Database Analyst (6 classes) – – SA & D, programming, reporting, spreadsheets, db theory 2 quarters full-time/ 3 quarters part-time  Relational Database Developer (3 additional classes) – Programming, SQL, group processes  Web site: www.bcc.ctc.edu/bi Jobs     Business Analyst Data Analyst Functional Analyst Marketing Analyst Jobs         Report Developer Data Modeler ETL Developer Data Architect Data Warehouse Designer Data Warehouse Developer Data Warehouse Administrator Database Administrator Jobs     Business Intelligence Consultant Business Intelligence Developer Business Intelligence Analyst Business Intelligence Project Team Member Jobs   One of the fastest growing segments of IT Less likely to be outsourced  May exist in business units rather than IT Knowledge/understanding of the organization is key 