1. Chapter11 Databases1 A file is a set of related records –A file is named by its owner –It is a user’s minimal accessible unit on secondary storage What if multiple people want to share information (perhaps about employees) –Do multiple files have the same information? Then how do we guarantee consistency when an update is made? –Can we maintain a single file? Then how do we guarantee proper access? Databases

2. Database A database is a collection of organized information –In computer terms, information is contained in files Databases organize multiple files –Provide answers to complex queries Databases control access –Restrict rights to information Databases support data consistency –Every user’s view has the most current values Chapter11 Databases2

3. Database Management Database Management tasks include: –Collecting data –Updating data (adding and deleting) Working with static data is called data mining –Storing data for efficient retrieval –Organization of data Sorting; securing access, etc. –Outputting data – concurrency handled Chapter11 Databases3

4. Database Management Data input –The most problematic part of database management –Humans may enter incorrect or partial values Handwriting may be illegible Keys or buttons may be punched incorrectly –Sensors may enter incorrect data values –It is difficult to correct false information Chapter11 Databases4

5. Data Organization If you have a telephone directory, how do you insert a name in the middle? If you have a database, data can be inserted at the end (or wherever there is room) and the system will order it logically Do you have several lists of people that you have invited to different parties. Do they overlap? What if an address gets changed? Chapter11 Databases5

6. Databases in Use Banks, Credit Card Companies, Search engines, Super Markets with customer cards, charities all maintain databases –Mailing lists are generated by selecting: Name and Addresses from perhaps multiple files –Select name, address from * –Selected names can be targeted based on attributes –Select from * where last-payment-year < 2011 Chapter11 Databases6

7. Data mining Data extracted from multiple databases and stored in data warehouse Data from operational (active) databases may also be extracted and copied to data warehouse Analysis can result in, for example, –Lower insurance rates based on expectations –Smaller reorders of inventory items Chapter11 Databases7

8. Predictive analytics Statistical algorithms, neural networks, and optimization research applied to data mining to find patterns in data –Predict the amount of money a state must set aside for employee pensions –Predict the lottery numbers to be chosen this May –Predict how much a house will appreciate in value from 2007 to 2011 Chapter11 Databases8

9. How to store data Simplest way to store data is in a flat file –For example, an Excel spreadsheet –Rows and columns in an Excel flat file Field- smallest building block –Has a unique identifier –Variable or fixed length Record: collection of related fields –Medical records Chapter11 Databases9

10. Record type Student record –Name –ID –Starting Date –Courses enrolled in Note: typically an ID is the unique key for a specific student record Name, Id, date, courses are fields (attributes) Chapter11 Databases10

11. Record occurrence (instance) Name: John Doe ID : 0003456 Starting Date: 1/12/09 Courses: CSCI 1105; ENG 2001 Data fields are variable in length; data values are typically assigned and changed dynamically. Course attributes doesn’t fit with the other static data. Chapter11 Databases11

12. Relationships “A relationship is an association between data that is stored in different record types” Given: a file of student records Given: a file of courses (with attributes of course #, room #) Relationship –For each student in the student record file, find the classroom that they are in on Monday April 7 th (if any) Chapter11 Databases12

13. Relational Database Mgmt Systems Collections of related tables –Think of an Excel spreadsheet –Each table is a sequence of records Each row is a record instance Each column defines attributes (field) Chapter11 Databases13

14. Vintage Music Shop (from text) Table 1 Albums Cat# Title ArtistName ReleaseDate InStock SellingPrice 1011 AA Ella 2/10/59 no 45.95 1010 BB George 2/15/64 yes 22.05 1101 CC William 4/1/00 yes 5.85 Each record must have a unique key (possibly combined fields) Chapter11 Databases14

15. Vintage Music Shop Table 2 Orders OrderNumber CustomerNumber Total OrderDate Chapter11 Databases15

16. Vintage Music Shop Table 3 OrderDetails OrderNumber CatNumber Quantity DiscountPrice Chapter11 Databases16

17. Vintage Music Shop Table 4 Customers Cust ID FirstName LastName Street City Tel# Chapter11 Databases17

18. Vintage Music Shop Table 5 AlbumDetails Cat# TrackTitle TrackLength TrackSample Chapter11 Databases18

19. How to partition data into tables? You don’t want customers and orders in one table. –A customer might have many orders You don’t want orders and order details in one table –Order details lets you access the specific item and quantity for inventory purposes –Orders are for billing customer Chapter11 Databases19

20. Database design is not obvious Just like PowerPoint, it takes some practice to separate information Placing information in different “modules” makes it easier to handle Chapter11 Databases20

21. Dimensional Database Systems Your multi-worksheets for drugstore inventory were 3-dimensional –Rows – different items handled –Columns – sales each month –Years 2009/2010 were a 3 rd dimension Relational database systems can be 3- dimensional Chapter11 Databases21

22. Object oriented databases Data are stored as objects Objects are grouped into classes –Each object is an instance of a class Attributes for the class are the same as fields –Valid methods are also defined for the class For Vintage Record Company, method for the class Orders might include checkInventory, checkCustomerCredit Chapter11 Databases22

23. Inheritance in Object-oriented databases If different records have some different attributes, the database might have to contain different record types –Customer form for phone or web customers In object-oriented databases, methods are defined on the class type and differentiated for different types of orders Chapter11 Databases23

24. Relational and OO databases Some relational databases have been modified to include object-oriented features –SQL, besides being used for queries, can also be used to define functions, such as for playing a song Chapter11 Databases24

25. Data management with spreadsheets Columns// fields or attributes Rows// records or instances Methods// sort, search, some mathematical functions, graphs Visual Basic code, macros can be inserted into Excel for other functions Chapter11 Databases25

26. Types of DBMS Entry level –Microsoft Access Cannot scale up to large amounts of traffic Public domain SQLite Database server software –Oracle Database –IBM DB2 –Microsoft SQL Server –Sun’s open source MySQL Chapter11 Databases26

27. Database access through the Web Static Web publishing –Convert database report into HTML document Displayed by browser –Data is read only; it’s not changed dynamically –Secure (read access-- to web page, not to database) –Simple (access allows you to “export” the data as an HTML or XML file) Chapter11 Databases27

28. “view” in databases It is possible to allow different users to see only part of the data –This is called a view Providing views on the web requires server- side programming –Cookie on customer (client) site provides client identification –Client id is used to generate a query to the DB Chapter11 Databases28

29. Updating a database Clients can be provided rights to make changes in the data values –Not changes in attributes – that is DBMS function On the web, a form is provided to customers –HTML forms, for example, with JavaScript Server-side programs such as ASP, CGI, PHP, ColdFusion process client input Chapter11 Databases29

30. XML XML as a standard for client output and input alpha.fdu.edu/~levine/xml/albums.xml alpha.fdu.edu/~levine/xml/album1.xml Chapter11 Databases30