Business Intelligence: Effective Decision Making

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Business IntelligenceEffective Decision Making

• Bellevue College

Linda Rumans IT Instructor, Business
Division Bellevue College lrumans_at_bellevuecollege.
edu
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Current Status
What do I do???
How do I increase sales????
How do I make my product better???
Business Users
Mountains of Data
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Mountains of Data

• From Operational Systems
• ERP (Enterprise Resource Planning)
• Sales/Order
• Inventory
• Customer Relationship Management (CRM)
• Web Sites
• Orders
• Click-stream

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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

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Todays Information Flow

• Business in 90s 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)

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Proliferation of Data
Operations
Sales
Finance
Procure- ment
Reporting Layer
Transaction Layer
MRP
SCM
CRM
Finance
Silos of data by functional area
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Data from Disparate Sources
Sales
Sales
Sales
Sales
Reporting Layer
Transaction Layer
Region A
Region B
Div 2
Div 1
Silos of data within large organizations
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Business Intelligence

• Business is now investing in Business
  Intelligence
• Business Intelligence is about making effective
  business decisions

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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.

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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.

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BI

• Involves PEOPLE and Technology
• Involves using a rational approach to management
• Involves a continuous cycle of measurement,
  adjustment re-measurement

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The BI Cycle
Analysis
Insight
BI
Measurement
Action
start
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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.

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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

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Benefits of BI

• Single Version of the truth
• Accurate, timely data available to all levels of
  the organization

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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

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BI Activities

• BI applications include the activities of
• decision support,
• query and reporting,
• online analytical processing (OLAP),
• statistical analysis,
• forecasting, and
• data mining.

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BI Users

• There are many different users who can benefit
  from business intelligence
• Executives
• Business Decision Makers
• Information Workers
• Line Workers
• Analysts

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BI Solutions-How to make it happen

• Two main components
• Data Consolidation and Storage
• Data Retrieval, Analysis and Presentation

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BI Curriculum

• Multi-Dimensional Analysis
• Data Warehousing
• Data Mining
• Dimensional Modeling
• Data Visualization

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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
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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

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Data Storage Structures

• Multi-Dimensional Databases
• Cubes

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Multi-Dimensional Databases

• Measures
• Any quantitative expression
• Some are designated as Key Performance
  Indicators (KPI)
• Appropriate to the business process.
• Dimensions
• How we describe the measures Product/Customer/R
  egion/Time
• These are the Bys
• What were our Customer Sales by Product Line by
  Region by Quarter for the past two years?.

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Logical Structure
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Multi-Dimensional Databases (Cubes)
Multi-Dimensional Database (Cube)
Business Intelligence Programs
Data Warehouse
ODS
ODS
ODS
Relational Database Programs
ODS Operational Data Store
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Multi-Dimensional Databases
Multi-Dimensional Database (Cube)
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Software Applications
Business Person
Reporting Applications
Multi-Dimensional Database (Cube)
Business Person
Analytic Applications
Score Cards Dashboards
Business Person
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Analytics

• Reporting Applications
• Limited user interaction
• Fulfill a significant portion of an
  organizations information needs
• Analytic Applications
• Allow users to visualize and explore data
  following their train of thought
• Extensive interactivity

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Analytic Application
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Summary

• Students learn to
• Create multi-dimensional databases
• Create professional quality reports
• Use analytics to provide in-depth data analysis

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Data Warehousing

• Designing a Data Warehouse

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Data Warehouse Topics

• Decision Support Systems
• history
• Requirements Gathering
• Where data located, owners, definition, how often
  updated
• Data Analysis
• Determine for table structures

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Data Warehouse

• ETL Processes Deliverables
• Cleaning Conforming
• Valid, missing
• Address, gender
• Schemas
• Dimension Tables
• Fact Tables

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Data Consolidation Storage
Customers Sales Procurement Suppliers
Operations Finance
Shared Reporting
Shared Data Layer
Data Warehouse
Transaction Layer
MRP
CRM
SCM
Finance

• Operations and financial information is shared
  across the organization from same core data

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Data Warehouses
Multi-Dimensional Database (Cube)
Data Warehouse
ODS
ODS
ODS
ODS Operational Data Store
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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

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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)

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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

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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!!!!

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Data Mining
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Data Mining

• The process of identifying patterns in data
• Goes beyond simple querying of the database
• Goes beyond multi-dimensional database queries as
  well

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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.

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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.

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Data Mining Applications

• Fraud detection
• Targeted Marketing
• Risk Management
• Business Analysis

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Origins of Data Mining

• Mathematics
• Statistics
• Numerical Analysis
• Artificial Intelligence/Machine Learning
• Computer Science
• Data Storage and Manipulation

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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.

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How does Data Mining work?
NOT What-Cha-Ma-Call-Its
What-Cha-Ma-Call-Its
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How does Data Mining work?
Which of these are What-Cha-Ma-Call-Its?
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Data Mining Process
List of Customers -some bicycle buyers
-some not
Data Mining Software
Model
List of Likely Buyers
List of Prospective Buyers
Model
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Overview of Mining Strategies
Note This representation is over-simplified and
data mining strategies are continually being
invented.
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More on our Curriculum
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Skills

• Written communication
• Problem Solving
• Analytical
• Troubleshooting
• Software
• Microsoft SQL Server Management Studio
• SQL Server BI Development Studio
• SQL Server Reporting Services
• Pro Clarity

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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

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Delivery Methods

• Use of Camtasia for
• Software demonstrations
• PowerPoint lectures
• Pod casting

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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,
  multi-dimensional II, data warehousing II (more
  programming with SQL Server)
• Web site www.bcc.ctc.edu/bi

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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

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Jobs

• Business Analyst
• Data Analyst
• Functional Analyst
• Marketing Analyst

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Jobs

• Report Developer
• Data Modeler
• ETL Developer
• Data Architect
• Data Warehouse Designer
• Data Warehouse Developer
• Data Warehouse Administrator
• Database Administrator

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Jobs

• Business Intelligence Consultant
• Business Intelligence Developer
• Business Intelligence Analyst
• Business Intelligence Project Team Member

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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

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Questions?