Relational Data Analysis I

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1 Relational Data Analysis I

2 Relational Data Analysis Prepares Business data for representation using the relational model The relational model is implemented in a number of popular database systems Access Oracle MySQL SQL Server DB2

3 The Relational Model A relation is a table of data A relational database is therefore one in which tables are used to store data This implies that there are other ways of storing data Tables will be related to each other in some way Because the data held in them is related The context of the system we are developing governs which data items are related and how they are related

4 Relational Data Analysis Relational data analysis therefore involves: Building related tables of data Retrieval of data from one or more related tables Inserting, Updating and Deleting data from related tables

5 Relational Data Analysis Relational Data Analysis is quite formal Based on set theory Uses Relational Algebra to define operations on tables We will take a less formal approach

6 Definitions A relation corresponds to a table A tuple is a row in a table An attribute is a column in a table A Primary Key is the attribute by which we uniquely identify each row The number of rows in a table is called the cardinality The number of attributes in a table is called the degree

7 Example Relation (Table) The table can also be described without its data: Student (Student ID, Student Name, Course, Module Code, Module Name, Grade) We should use CamelCase for Attributes and Table Names: Student (student ID, studentname, course, modulecode, modulename, grade)

8 Example Relation (Tuple) A Tuple is a row in a table Each tuple should be unique The sequence of tuples should not be important A Primary Key Attribute is added to ensure each row is unique This data is for a machine to read not a person

9 Example Relation (Attribute) An Attribute is a column in a table Each attribute should have a unique name The order of the columns should not be significant

10 Example Relation (Table) Our example has a cardinality of 4 and a degree of 6 The primary key will be student ID as this will uniquely identify each row We cannot know this without having an understanding of the data If there is no existing primary key then we must invent one

11 Exercise Name Tom Number Town Manchester No of contracts 2 Depot Manchester Dick Leeds 1 Manchester Harry Manchester 3 Stoke Sue Oxford 1 Reading Frieda Cardiff 7 Cardiff Imran Manchester 1 Stoke Yue Manchester 7 London

12 Exercise What is the cardinality of the table? What is the degree of the table? Identify the Primary Key of the table?

Exercise Name Tom Number 0050065 Town Manchester No of contracts 2 Depot Manchester Dick 0338178 Leeds 1 Manchester Harry 1922029

13 Exercise Name Tom Number Town Manchester No of contracts 2 Depot Manchester Dick Leeds 1 Manchester Harry Manchester 3 Stoke Sue Oxford 1 Reading Frieda Cardiff 7 Cardiff Imran Manchester 1 Stoke Yue Manchester 7 London

14 Exercise What is the cardinality of the table? How many rows? 7 What is the degree of the table? How many attributes? 5 Identify the Primary Key of the following table? Number But how do we know? Why not Name?

15 Tables and Entities Each table is equivalent to an entity in an ERD Each attribute is equivalent to an attribute in an ERD Each tuple is an occurrence of an entity in an ERD The primary key is equivalent to the key attribute in an ERD entity

16 Rules A table cannot have any empty cells No two rows in a table are identical i.e. there are no duplicate tuples/rows Every relation has a Primary Key attribute The sequence of the rows should not be significant The sequence of the columns should not be significant Each attribute must have a unique name

17 Problems with Tables Problems with tables can be classified into three groups: Insert Anomalies Problems caused when inserting new information Update Anomalies Problems caused when updating existing data Delete Anomalies Problems caused when deleting data

18 Problems with Tables Insert Anomoly: We cannot add a new course unless we have a student ID Update Anomoly: What if Big John changes his name? Assume there are 1000s of records Delete Anomoly: What if we remove Terrence Halfwit from the database?

19 The Solution? To remove these anomalies we must rearrange the data and create new tables The process for doing this is called Normalisation

20 Normalisation First Three Stages First Normal Form (1NF) Second Normal Form (2NF) Third Normal Form (3NF) 1NF can be considered as Normalised But there could still be problems Most common problems are solved by 3NF Further Normalisation will solve rarer problems

21 First Normal Form All data in a table must be dependant on the key In order to do this we must remove repeating groups This is done by analysing the relationship between the primary key and the rest of the data

22 Example 1 - Students Student ID Student Name Course ID Course Module Code Module Name Grade Attributes are moved if there is more than one for each instance of the primary key

23 Example 1 - Students Student ID Student Name Course Course ID Module Code Module Name Grade For each Student ID How many Student names are there? 1 or Many?

24 Example 1 - Students Student ID Student Name Course Course ID Module Code Module Name Grade For each Student ID How many Courses are there? 1 or Many?

25 Example 1 - Students Student ID Student Name Course Course ID Module Code Module Name Grade For each Student ID How many Course IDs are there?

26 Example 1 - Students Student ID Student Name Course Course ID Module Code Module Name Grade For each Student ID How many Module Codes are there?

27 Example 1 - Students Student ID Student Name Course Course ID Module Code Module Name Grade For each Student ID How many Module Codes are there?

28 Example 1 - Students Student ID Student Name Course Course ID Module Code Module Name Grade For each Student ID How many Module Names are there?

29 Example 1 - Students Student ID Student Name Course Course ID Module Code Module Name Grade For each Student ID How many Module Names are there?

30 Example 1 - Students Student ID Student Name Course Course ID Module Code Module Name Grade For each Student ID How many Grades are there?

31 Example 1 - Students Student ID Student Name Course Course ID Module Code Module Name Grade For each Student ID How many Grades are there?

32 Example 1 - Students Student ID Student Name Course Course ID Module Code Module Name Grade Indented data is a repeating group We need to put it into a new table This table will describe the module a student is taking We will call it Student Module

33 Example 1 - Students Student ID Student Name Course Course ID Student ID Module Code Module Name Grade We now have two tables Student details Primary Key = Student ID Student s module details PK = Student ID, Module Code Called a compound Key

34 Example 1 - Students Update Anomoly: What if Big John changes his name? Delete Anomoly: What if we remove Terrence Halfwit from the database? Insert Anomoly: We still cannot add a new course unless we have a student ID

35 Yes But No But There are still Anomalies Update If Creative Accounting name is changed Insert Cannot add a new module unless we have a student enrolled Delete When a student leaves we could lose course information These are dealt with by later Normal Forms

36 Example 2 - Library Student ID Name Faculty Book ID Title Author Return Date Put this data into First Normal Form

37 Example 3 Customer ID Customer Name Address Branch No Branch Manager Stock ID Title Format Put this data into First Normal Form

38 Remember 1NF can be considered as Normalised But it doesn t solve all of our problems Need to go through second and third Normal Forms in Tutorials and next week

39 Second Normal Form Only Applies to tables with compound keys (Tables without compound keys are already in 2NF) Data in a table must depend on the whole key We must remove any partial dependencies

David M. Kroenke and David J. Auer Database Processing 11 th Edition Fundamentals, Design, and Implementation. Chapter Objectives

David M. Kroenke and David J. Auer Database Processing 11 th Edition Fundamentals, Design, and Implementation Chapter One: Introduction 1-1 Chapter Objectives To understand the nature and characteristics