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C6 Databases.

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Presentation on theme: "C6 Databases."— Presentation transcript:

1 C6 Databases

2 Problems with traditional file environments
Data Redundancy and Inconsistency: Data redundancy: The presence of duplicate data in multiple data files so that the same data are stored in more than one place or location Data inconsistency: The same attribute may have different values. Program-Data Dependence: The coupling of data stored in files and the specific programs required to update and maintain those files such that changes in programs require changes to the data and vice versa 2

3 More problems Lack of Flexibility Poor security
A traditional file system can deliver routine scheduled reports after extensive programming efforts, but it cannot deliver ad-hoc reports or respond to unanticipated information requirements in a timely fashion Poor security Management may have no knowledge of who is accessing or making changes to the organization’s data Lack of data sharing and availability: Information cannot flow freely across different functional areas or different parts of the organization. 3 3

4 Types of databases Relational Hierarchical and Network Object-oriented
The focus of this lecture is on relational databases. 4 4

5 The Database Approach to Data Management
Relational DBMS Represents data as two-dimensional tables called relations Relates data across tables based on common data element Examples: Access, DB2, Oracle, MS SQL Server 6-15

6 The Database Approach to Data Management

7 Data hierarchy High Level 5

8 Important ideas In a database A group of records makes a table (file)‏
A group of values for the set of fields makes a record (tuple) (row)‏ A group of records makes a table (file)‏ A group of tables (files) makes a database A field name serves to label each column of each table Record 6 8

9 Types of fields Fields can contain Strings (text characters) Numeric
Sometimes very specific formats (e.g. Date)‏ 8 9

10 Types of operations in a relational database
Select: Creates subset of rows that meet specific criteria Join: Combines relational tables to provide users with information requires a field in common between the tables being joined Project: Create a subset consisting of certain columns of the table results in a new smaller table 9 10

11 10 11

12 The Database Approach to Data Management
6-18 12

13 Summary on db operations
Selections are related to choosing table rows. Projections are related to choosing table columns Joins are related to choosing records that have a common value in a field shared by two tables. 11


15 Designing a database Conceptual design: Abstract model of database from a business perspective Physical design: how data are actually structured on physical storage media Entity-relationship diagram: Methodology for documenting databases illustrating relationships between database entities Normalization: Process of creating small stable data structures from complex groups of data Primary Keys: Each table requires a unique identifier (a field or a set of fields)‏ 11 15

16 Data Base Management Systems
Data definition language: Specifies content and structure of database and defines each data element Data manipulation language: Used to process data in a database; permits users to extract data Data dictionary: Stores definitions of data elements and data characteristics; can indicate usage and ownership 13 16

17 The Database Approach to Data Management
Distributed database: A database that is stored in more than one physical location Reduce the vulnerability of a single, massive central site Increase service and responsiveness to local users Can often run on smaller, less expensive computers Depend on high-quality telecommunications lines The Database Approach to Data Management 6-29 17

18 Multidimensional data analysis
Also called Online Analytical Processing (OLAP)‏ Supports manipulation and analysis of large volumes of data from multiple dimensions/perspectives 14

19 Example of OLAP 15 19

20 A massive database that stores current and historical data
Data are standardized into a common data model Consolidated across entire enterprise for management analysis and decision making Data Warehouse 16 20

21 Example of a data warehouse
17 21

22 Data mining Tools for analyzing large pools of data
Find hidden patterns and infer rules to predict trends 18 22

23 Managing Data Resources
Establishing an information policy Specifies the organization’s rules for sharing, disseminating, acquiring, standardizing, classifying, and inventorying information Data administration is responsible for specific policies and procedures through which data is managed Data governance Database administration 6-40 23

24 Managing Data Resources
Ensuring Data Quality Data Quality Audit Structured survey of the accuracy and completeness of data in an information system Data cleansing consists of activities for detecting and correcting data in an information system 6-41

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