Chapter 5

Chapter 5

1. Definitions

   • SAP?
     • Integrated software suite includes models in enterprise resources planning+data warehouse supporting enterprise wide real time tracking, reporting, analysis
     • 1. shows IT role in data mgmt
     • 2. illustrate digital tech ability keeping low cost and high performance
   • DataBase?
     • files with records on people,places,things, used to be file cabinets
   • Entity?
     • general category showing person/place/thing that we store +maintain info on
     • Ex: Supplier+part
   • Attributes?
     • charcarestics of the entity. Ex; Supplier(name/adress), Part (descriptiong/unit price/supplier)
   • Data quality Audit?
     • structered survey of the accuracy/ completelness of data
   • Data cleansing?
     • detects/correct incorrect. incomplete, imporperely formatted redundant data
   • Info policy?
     • states org rules for /organizing /managing /storing/ sharing info
   • Data administrations?
     • policies/procedures that data would be managed as a resouce
   • DataBase administration?
     • Design/mgmt group defines/organizes structure/content and maintinance
   • Web Mining?
     • Discover&analyse patterns of info from web
     • 1. content mining
     • 2. structure mining
     • 3. Usage mining
   • Text Mining?
     • unstructered data (text files) has 80% of org useful info
       • 1. extracting key elements
       • 2. discovering patterns
       • 3. summerizing large unstructered data sets

2. what causes data quality problems?

   • 1. redundent/inconsistant data by multiple systems
   • 2. data input errors

3. Types of info in data mining?

   • 1. Associations
     • occurrences linked to single event
   • 2. Sequences
     • events linked over time
   • 3. classifications
     • patterns describing a group an item belongs to
   • 4. Clustering
     • discovering as yet unclassified groupings
   • 5. Forecasting
     • uses series of values to forecast future values

4. Data mining?

   • finds hidden patterns/relationships in large databases + infers rules to predict future behaviour

5. Online Analytical Processing OLAP

   • Supports multideminstional analysis helping users view same data in different ways

6. Relational database tables

   • 1. One to one relationship
   • 2. one to many relationship
   • 3. many to many relationship

7. Entity-relationship diagram ?

   • Clairifies rable relationship in relational databases

8. Normalization ?

   • Streaming complex groups of data to
     • 1. Minimize redundant data elements
     • 2. Minimize awkward many-to-many relationships
     • 3. Increase stability and flexibility

9. DBMS ?