Introduction to Computing

1. Introduction to Computing Unit 3: Information Management

2. Review of the Lecture • Databases • Data Modelling • Relational Databases • Data Integrity and Security • Query Language • Data Mining

3. Databases • What is a database? • A structured store of data • Logically coherent • Designed for a specific purpose • Integrated across an organisation • On a computer system • Based on a model • Allows access to data by all who need it

4. Data Files • Data can be stored in simple files: • A Serial File • Data is stored one item after another. • e.g. Sales – in the order they happen • To find an item: • Start at the beginning • Visit each item in turn • Until found or end of file • Finding an item can take a long time

5. Data Files • A Sequential File • data is stored one item after another in some order • E.g. Sales – in stock number order • To find an item: • start at the beginning • visit each item in turn • until found or stock number higher than the one searched for • Finding an item can be quicker: • can stop the search early if item not present • or…. can use an index and fast forward to the right place

6. Data Files • Adding new data to simple files: • Serial • go to end of file – add new item • Sequential • start at the beginning • write old data to new file until correct position for new item • write new item to new file • write the rest of old file to new file

7. Data Files • Direct Access • This method calculates the correct position and places the data item there. It finds data in the same way.

8. Data Files • Direct Access • A very quick method • It requires a random access storage device such as a disk • Cannot use tape storage

9. Problems with Simple Data Files • Simple data files can be awkward for an organisation. • What if…… • Two or more people need to update the same file? • The software is updated? • The data structure needs to be changed?

10. Errors Lack of data integrity Data Redundancy • The same data may get stored more than once • One copy gets updated • The other does not

11. Data Dependence • What if the organisation’s data storage needs change? • There is a need for: • Updated data structure • Updated software

12. The Database Approach • Data is stored in an integrated database • Data is stored centrally • The organisation can control it • Everyone has access to the same data • Data is not spread around lots of files • Data can have multiple views

13. The Database Approach • Reduced data redundancy • Data is consistent • Data is shared • Corporate standards can be enforced • Better security • Controlled access • Leads to data integrity

14. Keeping Data Safe • Security • Data is protected against loss or unauthorised access • Integrity • Data is as it should be – complete, consistent and correct

15. Data Independence • Simple Filing Systems: • The software must “know about” the way that the data is organised • Changes to the data structure require changes to the software • Databases • Separate the data from the applications • The data is under the control of a database management system (DBMS)

16. DBMS • A set of programs: • for defining a database • for creating a database • maintaining a database • manipulating a database • (queries, reports, updating)

17. DBMS • ADatabase Management Systemmanages the physical data. • Applications can be produced that work on the data through the DBMS. application DBMS data

18. DBMS • The DBMS: • Can enforce rules to ensure integrity. • Can separate the application from the data. • Can allow changes to the applications. • Can perform validation checks. • Provides security features.

19. Data Models - Hierarchical • Data must be structured for ease of processing. • The structure is known as the data model or schema. • The description of the model is stored in the data dictionary. • There are various models, e.g. the hierarchical model. This works in some cases Hierarchical Model

20. Entities • An entity is a real-world object. • We store data about entities. • The entity has attributes. • Each attribute makes up a data field. • Data about one entity makes up a record. 1 record

21. Data Models - Relational • The most common model is relational. • Based on interconnected tables • Each table is made of rows and columns. • A row corresponds to a record. • Each row of a table must have the same structure. • A column corresponds to a field. • Tables are linked by keys.

22. Entity Relations • Arelational databaseseparates the data about different entities into different tables. • A customer can place many orders. • Each order can contain many items.

23. Relational Model Tables Links

24. Key Fields • Each table has a primary key. • This uniquely identifies each record. • It may be one field such as an id number. • It may be a compound key. table: student table: hotel_booking simple primary key compound primary key

25. Links • Aprimary keylinks to a foreign key in a different table. Au_ID is primary key here Au_ID is foreign key here

26. Integrity and Security • The data is held centrally. • Centralised back up • Levels of access • Validation enforces rules on data entry. • Record locking prevents inconsistent updates. • Referential integrity prevents conflicting updates.

27. Validation • A check that data is acceptable. • Carried out by the software at the time of data entry • Does not ensure that data is accurate • Examples:

28. Querying a Database • Databases can get big. • We need a way to extract just the data we need. • Often done using a query language. • DBMS may have QBE (query by example). • There are many examples of query languages.

29. Querying a Database • Some DBMS programs allow Query by example (QBE). This query selects records where the number of items in stock is more than 400.

30. Querying a Database The same query can be constructed in a query language such as SQL: SELECT stock.stock_number, stock.stock_name, stock.number_in_stock, supplier.supplier_name, supplier.supplier_telephone FROM stock INNER JOIN supplier ON stock.supplier_number = supplier.supplier_number WHERE (((stock.number_in_stock)>400)) ORDER BY stock.number_in_stock; The result of running the query is:

31. Creating a Database • The query language can also create databases: CREATE SCHEMA SCHOOL CREATE TABLE STAFF(FName             VARCHAR(15)              NOT NULL, LName             VARCHAR(15)               NOT NULL, SocSecNo       INT                                  NOT NULL,    StaffNum         INT                                 NOT NULL, Title                  VARCHAR(10),    Code               CHAR(5), PRIMARY KEY (SocSecNo), UNIQUE (StaffNum), FOREIGN KEY (Code) REFERENCES DEPARTMENT (DeptCode));

32. Nowadays there is a huge amount of data in databases. There may be useful information that was not part of the plan when the database was set up. • For example, a supermarket with a loyalty card scheme records every purchase made by each customer. Data Mining

33. Data Mining • The supermarket knows the names and addresses of its card holders. • It knows what they have bought. • It can look through the data for patterns. • Maybe people in certain areas tend to buy certain things. • Advertising can now be targeted.

34. Data Mining • Similar items are grouped together. • Attempts to find a model • Data mining: • uncovers patterns • discovers new relationships • can help to make predictions

35. Data Mining • Uses: • Market analysis • Combating terrorism • Predicting genetic disorders • Predicting drug reactions • Traffic analysis

36. Data and Confidentiality • With so much data being stored and easy to copy, people worry about who has access to it. Tax authorities Government Security services Friends and family Insurance companies Criminals

37. Data and Confidentiality • Most countries have data protection laws. • These are designed to protect privacy.

38. Data and Confidentiality • Most data protection laws are similar: • Data may only be used for the specific purposes for which it was collected. • Data must not be disclosed to other parties without consent. • Personal information may be kept for no longer than is necessary. • Personal information may not be transmitted outside a particular area. • Those holding personal information are required to have adequate security measures in place. • Subjects have the right to have factually incorrect information corrected. • …..but it is so easy to copy data, can these laws be enforced?

39. Unit 3 Any questions?