1. DATABASE CONCEPTS

5.  It does not have to be computerized  However, due to the high power and relatively low price of current technology, as well as the increasing availability of data prepared in the digital form, most databases are intended for computer use

6. Punch Card Paper Data Reels File Systems digital form

8.  It is needed to provide the abstract view of data i.e. the system hides certain details of how the data is stored and maintained

12. Fig :-External View

13. Fig :-Conceptual View

14. Fig :-Internal View

16. What is Data Model  conceptual tools for describing data, data relationships  A data model visually represents how data will be organized and how the information is structured in the database.

17. Types of Data Models  Entity-Relationship (E-R) Models  UML (unified modeling language)

18. Entity-Relationship Model  Entity Relationship Diagrams (ERD) as this is the most widely used  ERDs have an advantage in that they are capable of being normalized Entity Attributes Primary key

20. A data model consists of entities related to each other on a diagram:

21. Different Data Models

22. Example: Given that …  “Customer” is an entity.  “Product” is an entity.  For a “Customer” we need to know their “customer number” attribute and “name” attribute.  For a “Product” we need to know the “product name” attribute and “price” attribute.  “Sale” is an entity that is used to record the interaction of “Customer” and “Product”.

23. Here is the diagram that encapsulates these rules:

24. If we want to know the price of a Sale, we can ‘find’ it by using the “Product Code” on the instance of “Sale” we are interested in and look up the corresponding “Price” on the “Product” entity with the matching “Product Code”.

25. Database Normalization  ● Overview – Definition of database normalization – Why normalize? – First normal form – Second normal form – Third normal form

26. Database Normalization Optimization process by which data structures in a relational database are as efficient as possible including  the elimination of redundancy  the minimisation of the use of null values and  the prevention of the loss of information.

27. Database Normalization Why Normalize? – Improved speed – More efficient use of space – Increased data integrity (decreased chance that data can get messed up due to maintenance)

28. Database Normalization  First Normal Form (1NF)  Second Normal Form (2NF)  Third Normal Form (3NF) Stages of Normalisation

30. Database Normalization  Unnormalised form student_idclass_nametimelocationprofessor_id 999-40-9876Math 148MWF 11:30Rm. 432Prof145 999-43-0987Physics 113TR 1:30Rm. 12Prof143 999-42-9842Botany 42F 12:45Rm. 9Prof167 999-41-9832Matj 148MWF 11:30Rm. 432prof145 : – Problems ● no need to repeatedly store the class time and professor ID ● redundancy introduces the possibility for error (Matj148)

31. Database Normalization ● First Normal Form  the elimination of repeated groups of data by creating separate tables of related data  – Student information:  Class information:  Professor Information: Student IDStudent NameMajorcollegeCollege Location StudentIDClassIDClassName ProfessorIDProfessorName

32. Database Normalization

35. Tabular or flat file-data in a single table Hierarchical Database Management System Network Database Management System Relational Database Management System

36. Tabular or flat file-data in a single table In this type of data only a single tabled attribute is used e.g. the record of the rainfall data by a meteorological station within 24 hours as: 56 65 68 70 55. And so on…

37. CONTRACT 1990 1989 1988 FX1 FX2FX3FX4 FX1FX2 JONES  Cabinet  Drawer  Document  Folder

38. Hierarchical database  A hierarchical database organizes data as one object of interest related to many other objects of interest. The tree-like structure produced is referred to as an ordered set of parent/child relationships.  In this model, a parent can have one or more children, but a child cannot have more than one parent. When 'real world' data relationships are of this type, the hierarchical model is an effective representation model.

39. Smith Allen Jones Ed Bob Bert

40. Network Database

42.  A relational database is a perception of data as collections of tables that are logically associated to each other by shared attributes.  Any data element can be found in a relation by knowing the table name, the attribute (column) name, and the value of the primary key. Relational Database The advantage of these systems is that they are very flexible and can reply to any kind of query formulated with logical and mathematical operations.

43. note the potential confusion " relation " is a table of records, not a linkage between records And the table acts as the link

44. Relational DBMS  Components of a Relational Database  Table: collection of rows all containing the same columns  Row: Horizontal components of a table. Consists of values for each column. Each row is equivalent to a record  Column: Vertical component of a table. Each column in the record is often referred to as a field

45. Relational DBMS Contain Tables or feature classes in which:  rows: entities, records, observations, features:  ‘all’ information about one occurrence of a feature  columns: attributes, fields, data elements, variables, items (ArcInfo)  one type of information for all features The key field is an attribute whose values uniquely identify each row entity Attribute Key field

46. Relational DBMS  Relational Database Rules  Each column in a table must be unique  The order of the rows in a table is not meaningful  The order of the columns in a table is not meaningful  All data in a column must be the same type  Every table has a primary key, each column in the primary key must have a value

47. Basic operators  Selection – return rows that meet some condition  Projection – return column values  Union  Cross product  Difference  Other operators can be defined in terms of basic operators

48. RDBMS Basics Basic RDBMS Operators: e.g. using PROJECT  PROJECT  Produce list of all values for a selected attribute PROJECT STUDENTID Yields Table Student StudentIDNameAddress 123456789Saenz, Lupe123 Mesa 234567890Chung, Mei37 5 th St. 345678901Adams, John54B Hague 456789012Elam, Mary123-22 E St. 567890123Bush, G.W555 Austin 678901234Clinton, B.89 Congress 789012345Bush, J.555 Austin Given: StudentID 123456789 234567890 345678901 456789012 567890123 678901234 789012345

49. Summary: Why are RDBMS useful?  Data independence – provides abstract view of the data, without details of storage  Efficient data access – uses techniques to store and retrieve data efficiently  Reduced application development time – many important functions already supported  Centralized data administration  Data Integrity and Security  Concurrency control and recovery

50. Database and GIS Spatial data location Attribute DBMS GIS database Text, Images Sound, movie Multimedia

51. SOIL LANDUSE INFRASTRUCTURE Data Storage Spatial Data Non-Spatial Data Population Census Agriculture Census GIS Database Database for GIS

52. Database of a Geographic Information Systems is a central to overall GIS system. Building a GIS database is typically the most resource consuming, about 80% of implementing cost. A GIS database can be divided into two basic type of data; spatial and non-spatial. Many different data types are encountered in GIS database e.g., pictures, words, coordinates, and complex objects. There are so many possible relationship between spatial objects that, not all can be started explicitly. What makes GIS so sophisticated is not just the maps but the data attributed to them and easy handling.. Databases for GIS