MIS 301 Exam 2

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MIS 301 Exam 2
2013-02-22 01:47:42

Midterm 2
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  1. Pyramid of Data
  2. Database
    • Self describing collection of integrated records made up of bytes, used to efficiently store and manage large amount of data
    • i.e. iTunes, Google, Blackboard

    Collection of tables, relations among rows in those tables and special data called metadata

    Each table in a Database should be organized around one theme
  3. Primary Key
    Column or group of columns that identifies a unique row in a table
  4. Foreign Keys
    non key column or field in one table that links to a primary key in another table
  5. SQL
    • Structured Query Language
    • International standard language from processing Databasees
    • all major DBMS products process SQL
    • Can be used to create databases and DB structures 
    • i.e.
    • SELECT StudentID FROM Students WHERE StudentName="Bob";
  6. Why use a database?
    • -Preserve Data Integrity-assurance that data is  consistent, correct and accessible
    • -Eliminate Data Redundancy
    • -Limit Data View- so that users only see what they need to see cleanly and clearly as possible
  7. Bytes
    • What a database is made out of
    • "Characters"
  8. Columns
  9. Rows
  10. Metadata
    • describes database structure
    • -format depends on database software
    • -field properties describe formats 
    • make databases easy to use for authorized purposes
  11. Relational Database
    Store data in tables that represent relationships using foreign key
  12. Database Management System Functions:
    • Create
    • Process
    • Administer
    • i.e. Oracle, MySQL, Access 

    • Different from databases because DBMS is a license software program
    • Database is a collection of tables, relationships and metadata
  13. Database Application
    • collection of forms, reports, queries and application programs that process a database 
    • Database may have 1 or more apps and 1 or more users
    • Each app have different purposes, features and functions but all process the same inventory data stored in a common data
  14. Database Application System Components
    User-Database Application-DBMS-Database
  15. CRUD
    (Data forms)
    • Create
    • Read
    • Update
    • Delete Data 

    Reports show data in structure content
  16. How do you improve Value Chain Functions?
    Improve the quality of connections in the system
  17. Data Model
    • before building a database, developers construct a logical representation of database data
    • -Describes data and relationships stored in database
    • -data model referred to as a blueprint
  18. Entities
    • -person, place, things that users what to track and users want to store information on 
    • -physical object, logical construct, or transaction

    -Table where each entity is show in an rectange; have attributes and a unique identifier that's associated with ONLY one entity
  19. Attribute
    Each characteristics used to describe an entity
  20. Entity Relationship (E-R) data model
    • -most popular technique for creating data model
    • -abstract way to describe database
  21. Cardinality Notations
    • one to one 
    • l   <   
    • one to many (mandatory)
    •   >     
    • many
    •  >l   
    • one or more (Mandatory)
    • ll     
    • One and only one (Mandatory)
    • 0l    
    • Zero or one (optional)
    •  >0 
    • Zero or many (optional)
  22. Database Design
    • Converting data model into database
    • -transforms entities into tables
    • -expresses relationships with foreign keys
  23. Database Normalization
    • the activity of streamlining a database design by eliminating redundancies and repeated calues
    • -eliminated by placing repeating groups of values into separate tables and linking them through foriegn keys
    • -general goal is to construct tables so every table has single topic or theme
  24. Relational Database Design
    • Designer creates a table for every entity 
    • entity identifier becomes a primary key of table 
    • Attributes of entity become columns
    • represent relationships between tables
    • Add foreign key to one or more tables
    • Tables normalized to single theme
  25. Legacy Systems and Transactional Database
    • Legacy Systems- limit data utilization because they werent design to share data, are incompatible with new technology and aren't aligned with current needs 
    • Transactional Databases- aren't set up to be simultaneously accessed for reporting and analysis
  26. Hadoop
    • open source software framework
    • Distributed computing on clusters of computers
    • Distributed file systems (data resides in different locations, often redundant)
    • Implements MapReduce
  27. MapReduce
    • Map-divide/assign works of different nodes
    • Reduce-each node processes and send results back for aggregation
  28. Business Intelligence
    • use data created by other systems to provide reporting and analysis for organizational decision making
    • ability to pull data from across an organization and make decisions
    • able to look for patterns and make business decisions, analyze data
  29. Analytics
    • the science of analysis
    • describes the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions
  30. Sabermetrics
    specialized analysis of baseball through objective, empirical evidence, specifically baseball stats measuring in game activity
  31. Wisdom of Crowds
    the idea that a group of individuals often consisting of untrained amateurs will collectively have more insight than a single or small group of trained professionals
  32. Prediction Market
    • An example of wisdom in crowds
    • Consist of polling a diverse crowd and aggregating opinions in order to form a forecast of an eventual outcome
    • i.e. stock market
  33. Characteristics of Business Analytics
    • Continuous- part of routine daily, monthly, quarterly processes
    • Interative- answers to some questions generate more questions-deeper into data
    • Exploration/Investigation-of unknown, new patters/findings/metrics, anomalies, research hypothesis
    • Past business performance to gain insight
    • Drive business plannng
  34. Analytics in Each Function
    • Supply Chain-simulate and optimize supply chain flows, reduce inventory and stock outs
    • Customer Selection, loyalty and service- idenitfy customers with the greatest profit potential, retain loyalty
    • Pricing- identify the price that will maximize yield
    • Human Capital- select the best employees for particular tasks or jobs, at particular compensation levels
    • Product and Service Quality- detect quality problems early and minimize them
    • Financial Performance- better understand the drives of financial performance and the effects of nonfinancial factors
    • Research and Development- improve quality, efficacy and safety
  35. Stool Model of Analytics
    • Information Technology- helps capture, store and manipulate large volume of data
    • Quantitative Analysis- statistics, operations research, AI, data mining, helps ID patters hidden in data
    • Business Knowledge- enables you to understand the meanings of data
  36. Raw Data
    • usually unsuitable for sophisticated reporting of analytics 
    • missing values
    • inconsistent data
    • data not integrated
  37. Curse of dimensionality
    happens when using too many attributes to describe an entity
  38. SMART information
    • Sufficient
    • Worth Money
    • Accurate
    • Relevant to context and subject
    • Timely
  39. Operational Data Problems
    • raw data usually unsuitable for sophisticated reporting or data mining
    • values may be missing or inconsistent 
    • data can be too fine or too coarse 
    • too much data leads to many rows and the curse of dimensionality
  40. Primary BI Systems
    • Reporting Systems
    • Data Mining Systems
    • Knowledge Management Systems
    • Experts Systems
  41. Reporting Systems
    • integrate and process data by sorting, grouping, summing and formating
    • helps improve decisions by providing relevant, accurate and timely information to the right person allow one to use the right information to the right user at the right time
  42. Data Mining Systems
    Use sophisticated statistical techniques to find patterns and relationships: Regression Analysis and Decision Tree Analysis 

    helps improve decisions by discovering patterns and relationships to predict future outcomes:Market basket analysis, predict donations
  43. Knowledge management systems
    share knowledge of products, product uses, best practices among employees, managers, customers and others

    • helps improve decisions by publishing employee and others knowledge, create value from existing intellectual capital, foster innovation
    • fosters innovation and increased company organization responsiveness
  44. Expert Systems
    Encode human knowledge in the form of if/then rules and process those rules to make a diagnosis or recommendation (AI)

    Helps improve decision making by non experts by encoding, saving and processing expert knowledge