MIS 325 Lecture Notes - Lecture 19: Data Mining, Knowledge Extraction, Unstructured Data
2 May 2018
School
Department
Course
Professor
● Informational System:
○ A system designed to support managerial decision making
○ Based on historical point-in-time and prediction data for complex queries or
data-mining applications
○ Primary users
■ Managers
■ Business analysts
■ Customers
○ Broad, ad hoc, complex queries and analysis
○ Design goal: Ease of flexible access and use
○ Periodic batch updates and queries requiring many rows
● Business intelligence
○ Knowledge discovery and extraction in databases (KDD)
○ Data/pattern analysis
○ Information harvesting
○ Extraction of potentially useful (yet previously unknown) patterns or knowledge
from large volumes of both structured and unstructured data
● Patterns
○ Summarization of data
○ Relationship, regularity, and structure hidden in data
○ Tendencies
● Business intelligence (BI) systems:
○ Use data created by other systems
○ Provide reporting
○ Sophisticated data modeling
○ Analysis for organizational decision making
○ Understand the past and present
● Business analytics:
○ Extensive use of data
○ Statistical and quantitative analysis
○ Explanatory and predictive models
○ Fact-based management to drive decisions and actions
○ Predicting the future to help decision making again
○ Using sophisticated tools
● Reporting tools
○ Integrate data from multiple sources
○ Process data
■ Sorting
■ Grouping
■ Summing
■ Averaging
■ Comparing
Document Summary
A system designed to support managerial decision making. Based on historical point-in-time and prediction data for complex queries or data-mining applications. Broad, ad hoc, complex queries and analysis. Design goal: ease of flexible access and use. Periodic batch updates and queries requiring many rows. Knowledge discovery and extraction in databases (kdd) Extraction of potentially useful (yet previously unknown) patterns or knowledge from large volumes of both structured and unstructured data. Relationship, regularity, and structure hidden in data. Fact-based management to drive decisions and actions. Predicting the future to help decision making again. Data mining: the automated search in large databases for non-obvious patterns and. Why mine data? relationships to anticipate events or predict outcomes. Internet a lot of data accumulated in databases, data warehouses, and other information repositories. Data creates value for consumers and businesses: competitive advantage. To date, only ~5-10% of data is analyzed.
