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ADM1370 Module 3
Databases
| Question | Answer |
|---|---|
| Data | Raw facts that descrive the characteristics of an event |
| Information | Data converted into meaningful and useful content |
| Database | A collection of data organized to serve many applications efficiently by centralizing data and controlling redundant data. A single database services multiple applications. |
| Problems with traditional file organization | Data redundancy: Multiple files all over Data inconsistency: Same attribute with different values Lack of flexibility: not much you can do with data Poor security Lack of data availability: Information cannot flow freely across the organization. |
| Some sources of low quality information | -Customers intentionally enter false information -Call centres enter abbreviated or erroneous information by accident or to save time -Different entry standards |
| Costs of poor information | Tracking customers Selling opportunities Valuable customers Poor marketing |
| Database management system (DBMS) | A software package to create and maintain databases. - Acts as an interface between application and physical data files. -Relieves the programmer from the task of finding logical data (business view) and physical data (actual view) |
| How does DBMS solve the problems of traditional filing? | -Reduces data redundancy by control/minimizing -Uncouples programs and data to stand on its own -Access and availability increases -Managing security is easier |
| Relational DBMS | Represents data as 2D tables. The tables are related by common elements |
| Primary key | A field or group that uniquely identifies a given entity in a table. |
| Foreign key | A primary key of one table that appears as an attribute in another table and acts to provide a logical relationship between two tables. |
| Three Basic Operations in a Relational DBMS | Select: the subset rows that meet a criteria Join: the relational tables Project: relevant information |
| Hierarchical DBMS, Network DBMS | Organizes data in a tree-like structure like a family tree. Supports one-many-relationships Network: Logical many-to-many relationships between data. OUTDATED, not used in new applications Less flexible than Relational DBMS Lack of support |
| Object-Oriented DBMS (OODBMS), Hybrid OODBMS | Stores data and procedures as objects that can be retrieved and shared automatically. Hybrid OODBMS: Combines the benefits of relational and OODBMS |
| Data dictionary | a file that stores definitions of data elements and their characteristics. |
| Distributed Database, - Partitioned database. - Replicated database | Partitioned database: parts of the database are stored in different location Replicated database: duplicates of entire databases at all remote locations |
| Data cleansing | Activities that detect and correct data in a database or file that are incorrect, incomplete, redundant... etc. |
| Data warehouse | A copy of transaction data specifically structured for data mining Stores historical and current data used for decision making |
| Extraction, transformation, and loading (ETL) | Extracts information from internal and external databases transforms the information into common set of definitions Loads into data warehouse. |
| Data Mart | A subset of data warehouse information, contains summarized or highly focused portion of data |
| Online Analytical Processing (OLAP) | Interactive, exploratory analysis of multidimensional data from multiple dimensions/perspectives. |
| Hypermedia Database | Online database, supporting graphic, data organized as nodes |
| Data Mining and its use | Tools for deep down analysis of large pools of data - To find patterns - To predict future behaviour - To guide decision making |
| Cluster analysis | Divides an information set into mutually exclusive groups -members are as close as possible -different groups are far as possible -To study behaviour of groups |
| Data mining and Target marketing (prospects) | -identifies prospects -Chooses appropriate communication channels -Picks suitable messages |
| Customer Relationship Management (CRM) | -Match campaigns to customers Use loyalty programs don't stop marketing -Customer segmentation Find behavioural segments and use techniques -Reduce exposure to credit risk predict deafults, and avoid bad customers |
| Normalization | process of creating small, stable, flexible data structures from complex groups of data ~necessary for effective use of relational database |
| Classification | recognizes patterns describing a group by examining characteristics of a customer |
| Predictive analysis | use of data mining, historical data, and assumptions about future conditions to predict outcomes of events |
| Market Basket Analysis | association information; detection of customers' buying behaviour based on their purchasing choices to predict future behaviour |
| Information policy | -Specifics organization's rules for sharing, acquiring, classifying, and inventory information. -Lays out specific procedures |
| Data administration | -Responsibility for specific policies and procedures of how data can be managed. |
| Data governance | Deals with policies and processes for managing availability, usability, and security of the data employed in an enterprise. -In compliance with government regulation |
Created by:
wli043
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