Data Mining Jessica Jackson Kimberli Klein Kevin Wood.

Slides:



Advertisements
Similar presentations
1 Introduction to Data Management. Understand: meaning of data management history of managing data challenges in managing data approaches to managing.
Advertisements

Chapter 1 Business Driven Technology
Accounting System Insights
5.1 © 2007 by Prentice Hall 5 Chapter Foundations of Business Intelligence: Databases and Information Management.
BUSINESS DRIVEN TECHNOLOGY
Introduction BIM. Objectives Nature of Data Mining Data Mining Tools Ethics Online Survey Techniques Interpret Data.
Data Mining Glen Shih CS157B Section 1 Dr. Sin-Min Lee April 4, 2006.
McGraw-Hill/Irwin © 2006 The McGraw-Hill Companies, Inc. All rights reserved. 8-1 BUSINESS DRIVEN TECHNOLOGY Chapter Eight: Viewing and Protecting Organizational.
Managing Data Resources
Customer Relationship Management..a strategy used to learn more about customers' needs and behaviours in order to develop stronger relationships with them.
Chapter 9: Electronic Commerce Software. Electronic Commerce, Seventh Annual Edition2 Web Development Spectrum HTML Editors – FrontPage, Expression Web,
What is Strategy? (Part Two). Key Concepts Managerial Cognition Business Model Stakeholders The Balanced Scorecard.
Data Mining By Archana Ketkar.
Chapter 1 Accounting System Insights ACCOUNTING INFORMATION SYSTEMS The Crossroads of Accounting & IT © Copyright 2012 Pearson Education. All Rights Reserved.
BUSINESS DRIVEN TECHNOLOGY
Data Resource Management Data Concepts Database Management Types of Databases Chapter 5 McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies,
Chapter 11 Building a Customer-Centric Organization – Customer Relationship Management 11-1.
Data Mining & Data Warehousing PresentedBy: Group 4 Kirk Bishop Joe Draskovich Amber Hottenroth Brandon Lee Stephen Pesavento.
XP Information Information is everywhere in an organization Employees must be able to obtain and analyze the many different levels, formats, and granularities.
What is Business Intelligence? Business intelligence (BI) –Range of applications, practices, and technologies for the extraction, translation, integration,
McGraw-Hill/Irwin McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved.
Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization.
Shilpa Seth.  What is Data Mining What is Data Mining  Applications of Data Mining Applications of Data Mining  KDD Process KDD Process  Architecture.
Data Mining Techniques As Tools for Analysis of Customer Behavior
1.Knowledge management 2.Online analytical processing 3. 4.Supply chain management 5.Data mining Which of the following is not a major application.
5.1 © 2007 by Prentice Hall 5 Chapter Foundations of Business Intelligence: Databases and Information Management.
Intro to MIS – MGS351 Databases and Data Warehouses Chapter 3.
Ihr Logo Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization Turban, Aronson, and Liang.
Building a Customer- Centric Organization – Customer Relationship Management CHAPTER 11 Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights.
1.Understand the essential elements that comprise a customer relationship management program 2.Describe the relationship that exists between marketing.
Chapter 6: Foundations of Business Intelligence - Databases and Information Management Dr. Andrew P. Ciganek, Ph.D.
DECISION SUPPORT SYSTEM ARCHITECTURE: The data management component.
@ ?!.
Ch.3 Data, Text, and Document Management
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 5-1 Chapter 5 Business Intelligence: Data.
Database Design Part of the design process is deciding how data will be stored in the system –Conventional files (sequential, indexed,..) –Databases (database.
Lecturer: Gareth Jones. How does a relational database organise data? What are the principles of a database management system? What are the principal.
Data Mining By : Tung, Sze Ming ( Leo ) CS 157B. Definition A class of database application that analyze data in a database using tools which look for.
Marketing Research Marketing Information Systems.
Chapter 1 Business Driven Technology MANGT 366 Information Technology for Business Chapter 1: Management Information Systems: Business Driven MIS.
BUSINESS DRIVEN TECHNOLOGY
McGraw-Hill/Irwin © 2006 The McGraw-Hill Companies, Inc. All rights reserved. 1-1 BUSINESS DRIVEN TECHNOLOGY UNIT 1: Achieving Business Success Through.
5-1 McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved.
Ihr Logo Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization Turban, Aronson, and Liang.
Introduction – Addressing Business Challenges Microsoft® Business Intelligence Solutions.
Technology In Action Chapter 11 1 Databases and… Databases and their uses Database components Types of databases Database management systems Relational.
5 - 1 Copyright © 2006, The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin © 2008 The McGraw-Hill Companies, All Rights Reserved Chapter 7 Storing Organizational Information - Databases.
6.1 © 2010 by Prentice Hall 6 Chapter Foundations of Business Intelligence: Databases and Information Management.
Chapter 5: Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization DECISION SUPPORT SYSTEMS AND BUSINESS.
DATABASES AND DATA WAREHOUSES
CISB113 Fundamentals of Information Systems Data Management.
Data Mining BY JEMINI ISLAM. Data Mining Outline: What is data mining? Why use data mining? How does data mining work The process of data mining Tools.
Organizing Data and Information
McGraw-Hill/Irwin ©2009 The McGraw-Hill Companies, All Rights Reserved CHAPTER 6 DATABASES AND DATA WAREHOUSES CHAPTER 6 DATABASES AND DATA WAREHOUSES.
Data Warehousing 101 Howard Sherman Director – Business Intelligence xwave.
Chapter 1 Introduction to Social Commerce. Learning Objectives 1.Define social computing and the Social Web. 2.Describe the Social Web revolution. 3.Describe.
Chapter 3 Building Business Intelligence Chapter 3 DATABASES AND DATA WAREHOUSES Building Business Intelligence 6/22/2016 1Management Information Systems.
Data Resource Management – MGMT An overview of where we are right now SQL Developer OLAP CUBE 1 Sales Cube Data Warehouse Denormalized Historical.
Customer Relationship Management. Presentation By: Tarun Rattan Jyoti Sodani Akash Gupta Saloni.
Introduction to Gartner Inc.
Intro to MIS – MGS351 Databases and Data Warehouses
Data Mining.
Introduction BIM Data Mining.
Data Mining Generally, (Sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it.
MIS2502: Data Analytics Advanced Analytics - Introduction
DATA MINING © Prentice Hall.
Datamining : Refers to extracting or mining knowledge from large amounts of data Applications : Market Analysis Fraud Detection Customer Retention Production.
Databases and Data Warehouses Chapter 3
Data mining Data mining is the process of analyzing data from different perspectives and summarizing it into useful information.
Presentation transcript:

Data Mining Jessica Jackson Kimberli Klein Kevin Wood

Overview Brief Introduction What Can Data Mining Do? How Does Data Mining Work? Important Aspects Charts and Graphs Examples Wrap up

Data, Information, Knowledge Data Items that are the most elementary descriptions of things, events, activities, and transactions May be internal or external Information Organized data that has meaning and value Knowledge Processed data or information that conveys understanding or learning applicable to a problem or activity

What is Data Mining? The process of analyzing data from different perspectives and summarizing it into useful information This information can be used to increase revenue, cuts costs, or both

What Can Data Mining Do? Primarily used today by companies with a strong customer focus Determines impact of sales, customer satisfaction & corporate profits Determines relationships among “internal” factors and “external” factors Internal factors: price, product positioning, or staff skills External factors: economic indicators, competition, customer demographics

How Does Data Mining Work? Data mining software analyzes relationships and patterns in stored transaction data based on open-ended user queries The four types of relationships: Classes Clusters Associations Sequential patterns

Important Aspects Three important considerations include: Clean data, Security and Scalability Large amounts of access- Data must be accurate and free of errors and inconsistencies Must establish access rights to the data and to enforcing those rights The infrastructure must be in place includes web servers, report servers, databases and networks to support scalability

Dig, Discover, & Share*

Flow of Data Mining

The Life Cycle of a Data Mining Project

Example of Data Mining Software Oracle Data Mining (ODM) Oracle Data Mining Enables you to produce predictive information Build integrated business intelligence applications Find patterns and insights hidden in your data Extract greater value from corporate data resulting in better decision making

Field Use "...Using Oracle Data Mining, medical researchers are discovering trends and patterns that will Improve the health care for millions of people around the globe.“ -Dr. Carolyn Hamm, Director of Decision Support, Walter Reed Medical Center. "Saving Lives with Oracle"

Customer Successes of ODM Xerox Corporation Walter Reed Medical Center Internal Revenue Services CitiGroup Stuart Maue, Inc. Rexter Analytics Management Information Analysis

Company Uses Of Data Mining Starbucks- Reduce Insurance Claims The data is analyzed to uncover locations, floor designs and time patterns where customers slip and fall more frequently from coffee spills Dow Jones Wall Street Journal- Site Performance How the site is performing by correlating the log and click-stream information generated with the customer files The Royal Dutch/Shell Group- Operates in 135 countries with 90,000 employees and 1,700 separate operating companies. Help negotiate better contracts and identify products that are doing well or declining on a global basis.

Questions Comments