Introduction to Databases

Data Organisation

Definition

Data modelling

SQL

DBMS functions

Basics of data Organisation:

DATA HIERARCHY (four categories)

• Fields = represent a single data item

• Records = made up of a related set of fields describing one instance of an entity

• File / Table = a set of related records - as many as instances (occurrence) in the set

• Database = a collection of related files

Example of data structure

Name First name Telephone

Sampras Pete 45 25 65 65Healy Margaret 25 58 96 63Clinton Bill 12 25 28 89Henry Thierry 25 78 85 85

Fields

Records

File / Table + Other files =>complete dataStructure = DB

"A collection of interrelated data stored together with controlled redundancy, to serve one or more applications in an optimal fashion; the data is stored so that it is independent of the application programs which use it; a common and controlled approach is used in adding new data and in modifying existing data within the database."

Database: Definition.

• A collection of interrelated data stored together

• with controlled redundancy

• to serve one or more applications in an optimal fashion

• the data is stored so that it is independent of the application programs which use it

• a common and controlled approach is used in adding new data and in modifying existing data within the database.

Definition - closer look

Advantages of Databases:

• data are independent from applications - stored centrally

• data repository accessible to any new program

• data are not duplicated in different locations

• programmers do not have to write extensive descriptions of the files

• These save enough money and time to offset the extra costs of setting and maintaining DBs

Disadvantages of DBs:

• Data are more accessible so more easily abused

• Large DBs require expensive hardware and software

• specialised / scarce personnel is required to develop and maintain large DBs

• People / business units may object to “their” data being widely available in a DB

Characteristics of DBs…

• High concurrency (high performance under load)

• Multi-user (read does not interfere with write)

• Data consistency – changes to data don’t affect running queries + no phantom data changes

• High degree of recoverability (pull the plug test)

ACID test

• Atomicity

• Consistency

• Isolation

• Durability

All or nothing

Preserve consistency of database

Transactions are independent

Once committed data is preserved

DataBase Management System (DBMS):

• program that makes it possible to:

– create– use

– maintain a database

• It provides an interface / translation mechanism between the logical organisation of the data stored in the DB and the physical organisation of the data

Using a database:

Two main functions of the DBMS :

• Query language - for people who are not programmer (greatest advantage of DB)

• Data manipulation language - for programmers who want to modify the links between data elements within the DB

• Also, Host Language - the language used by programmers to develop the rest of the application - eg: Visual Basic for Applications (VBA) / Oracle developer 2000

Different types of DBs:

• creating the DB = specifying the links between data items

• different types of relationships can be specified - ie different logical views

• they correspond to three main types of DBMSs:

– Hierarchical DBs– Network DBs– Relational DBs– Object Oriented DBs

Hierarchical DBs:

• data item are related as “Parent” and “Child” in a tree-like structure

• “parent” means data item is higher in the tree than “child” and connected to it

• one “parent” can have more than one “child”, but one “child” can only have one “parent”

• most common platform = IBM’s Information Management System (IMS)

Example

Customers

Orders

Items

Unit of packaging

Payments

Currency

Substitution Product

Very fast retrieval

Undesirable side effects:

• Insertion of record:

– dependent record cannot be added without a parent– eg: units of packaging cannot be added without linkage

to an existing item

• Deletion of record:

– deletion of a parent deletes all children– deleting an existing item will delete its replacement

items

• Impossible to have two parents = trouble

Network DBs:

• same as parent and children in Hierarchical DB, but children can have more than one parent

• It is also possible to link items upwards to other items parents

• practically, it means that the DBMS is more flexible for data retrieval

Example

Customers

Orders

Items

Unit of packaging

Payments

Currency

Substitution Product

Suppliers

Relational DBs:

• Data items stored in tables

• Specific fields in tables related to other field in other tables (joint)

• infinite number of possible viewpoints on the data (queries)

• Highly flexible DB but overly slow for complex searches

• Oracle, SyBase, Ingres, Access, Paradox for Windows...

Describing relationships

• Attempt at modelling the business elements (entities) and their relationships (links)

• Can be based on users’ descriptions of the business processes

• Specifies dependencies between the data items

• Coded in an Entity-Relationship Diagram (ERD)

Types of Relationships

• one-to-one: one instance of one data item corresponds to one instance of another

• one-to-many: one instance to many instances

• many-to-many: many instance correspond to many instances

• Also some relationships may be:

– compulsory– optional

Example

• Student registering system

• What are the entities?

• What type of relationship do they have?

• Draw the diagram

Entity Relationship Diagram

Next step - creating the data structure

• Few rules - a lot of experience

• Can get quite complex (paramount for the speed of the DB)

• Tables must be normalised - ie redundancy is limited to the strict minimum by an algorithm

• In practice, normalisation is not always the best

Data Structure Diagrams

• Describe the underlying structure of the DB: the complete logical structure

• Data items are stored in tables linked by pointers

– attribute pointers: data fields in one table that will link it to another (common information)

– logical pointers: specific links that exist between tables

• Tables have a key

• If an attribute seems to belong to a relationship rather than an attribute, it may mean an associative entity must be added

ORDER

order numberItem descriptionItem PriceQuantity orderedCustomer numberItem number

Item

Item numberItem descriptionItem costQuantity on hand

Customer

Customer numberCustomer nameCustomer addressCustomer balanceCustomer special rate

1

2

3

4

* compulsory attributes0 optional attributes

Definitions

• Entity

• Attributes

• Instance(s)

• Domain

• Key (candidate primary and foreign)

Definitions

• Relationship

• Ordinality

• Cardinality

• Associative Entity

Some test questions

• Is it a bird is it a plane?

• Is it an entity or an attribute?

Normalisation

• Process of simplifying the relationships amongst data items as much as possible (see example provided - handout)

• Through an iterative process, structure of data is refined to 1NF, 2NF, 3NF etc.

• Reasons for normalisation:

– to simplify retrieval (speed of response)– to simplify maintenance (updates, deletion, insertions)– to reduce the need to restructure the data for each new

application

First Normal Form

• design record structure so that each record looks the same (same length, no repeating groups)

• repetition within a record means one relation was missed = create new relation

• elements of repeating groups are stored as a separate entity, in a separate table

• normalised records have a fixed length and expanded primary key

Second Normal Form

• Record must be in first normal form first

• each item in the record must be fully dependent on the key for identification

• Functional dependency means a data item’s value is uniquely associated with another’s

• only on-to-one relationship between elements in the same file

• otherwise split into more tables

Third normal form

• to remove transitive dependencies

• when one item is dependent on an item which is dependent from the key in the file

• relationship is split to avoid data being lost inadvertently

• this will give greater flexibility for the design of the application + eliminate deletion problems

• in practice, 3 NF not used all the time - speed of retrieval can be affected

Beyond data modeling

• Model must be normalised – purpose ?

• Outcome is a set of tables = logical design

• Then, design can be warped until it meets the realistic constraints of the system

• Eg: what business problem are we trying to solve? – see handout [riccardi p. 113, 127]

Realistic constraints

• Users cannot cope with too many tables

• Too much development required in hiding complex data structure

• Too much administration

• Optimisation is impossible with too many tables

• Actually: RDBs can be quite slow!

Key practical questions

• What are the most important tasks that the DB MUST accomplish efficiently?

• How must the DB be rigged physically to address these?

• What coding practices will keep the coding clean and simple?

• What additional demands arise from the need for resilience and security?

Analysis - Three Levels of Schema

Internal Schema

Logical Schema

External Schema 2 External Schema …External Schema 1

Disk Array

Tables Tables

4 way trade-off

Performance

Clarity of code

Ease of use

Security

Key decisions

• Oracle offers many different ways to do things– Indexes– Backups…

• Good analysis is not only about knowing these => understanding whether they are appropriate

• Failure to think it through => unworkable model

• Particularly, predicting performance must be done properly– Ok on the technical side, tricky on the business side

Design optimisation

• Sources of problems:– Network traffic– Excess CPU usage

• But physical I/O is greatest threat (different from physical I/O)

• Disks still the slowest in the loop

• Solution: minimise or re-schedule access

• Also try to minimise the impact of Q4 (e.g. mirroring, internal consistency checks…)

Creating links between the tables

• use common fields to join tables / queries

• very easy when data is properly normalised

• Gives total flexibility in terms of data retrieval

• Main strength of RDBs (SQL)

Structured Query Language

• used for defining and manipulating data in Relational DBs

• aimed at:

– reducing training costs– increasing productivity– improve application portability– increase application longevity– reduce dependency on single vendors– enable cross systems communication

• In practice, SQLs can be a bit different

Querying RDBs with SQL• use a form of pseudo english to retrieve data in

a view (which looks like a table)

• syntax is based on a number of “clauses”

• Select: specifies what data elements will be included in the view

• From: lists the tables involved

• Where: specifies conditions to filter the data

– specific values sought– links between tables

Example with one table

• find the name and address of customer number 1217

Example with a range

• find the items which are priced between £50 and £15000

Example with two tables

• find the rep name of all customers

Example with two tables

• same for customer Robson only

Use of a Search Condition - nested queries

• find the name and address of the customer who ordered order # 110

Additional syntax

• Add computation in the “select” statement:

– select SUM(price)– select AVG(price), MAX, MIN, COUNT

• Simplify comparisons with a BETWEEN clause and LIKE clause (with *, ?)

• Add sorting instruction after the where clause

– ORDER BY name (alphabetical)– ORDER BY price (ascending)

• Provide aggregate information by grouping data:

– GROUP BY customer

• find contents (item# and description) of order 110:

• find the average price of the cars for sale

• find the average price of all orders taken so far by customer “Jones”

• find how much cash customer “Barry” has generated in total

find the average price of all orders taken so far

CUSTOMER TABLE

PRODUCT TABLE

ITEM TABLE

SALES_ORDER TABLE

PRICE TABLE

Oracle Demo Set -Sales Order Processing

DEPARTMENT TABLE

EMPLOYEE TABLE

JOB TABLE

LOCATION TABLE

Oracle Demo Set -Employee Data