1. C6 Databases

2. 2 Traditional file environment 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

3. Lack of Flexibility 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 More problems

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

5. The Database Approach 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 Managing data

6. 6-16 The Database Approach Managing data

7. 5 High Level Data hierarchy

8. 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 6 Database ideas Record

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

10. 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 Types of operations in a relational database

11. 6-18 The Database Approach to Data Management

12. 10 The Database Approach to Data Management

13. 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 Summary on db operations

14. 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 Designing a database

15. 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 DBMS

16. The Database Approach to Data Management 6-29 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

17. Online Analytical Processing Multidimensional data analysis Supports manipulation and analysis of large volumes of data from multiple dimensions/perspectives 14 OLAP

18. 16 Data Warehouse 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

19. 17

20. Tools for analyzing large pools of data Find hidden patterns and infer rules to predict trends Bank of Montreal uses data mining better understand their customers by using various query tools a statistical package, and in-house developed analytics one set of analytics sends prompts to an account manager, indicating that a specific bank customer has changed their banking patterns and that the manager should follow up with that customer This data mining leads to retaining business and customers and even obtaining new business from those customers. 18 Data mining

21. 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 –Quality, management, policy, risk management DBA (Database administrator ) –installation, configuration, upgrade, administration, monitoring and maintenance of databases 6-40

22. 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