Data Management - Introduction to Computing - Lecture Slides, Slides of Introduction to Computing

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CS101 Introduction to Computing

Lecture 36

Data Management

During the last lecture … (Intelligent Systems)

• We looked at the distinguishing features of intelligent systems w.r.t. other software systems
• We looked at the role of intelligent systems in scientific, business, consumer and other applications
• We discussed several techniques for designing intelligent systems

Not a Suitable Hammer for All Nails!

if the nature of computations required in a task

is not well understood

or there are too many exceptions to the rules

or known algorithms are too complex or inefficient

then AI has the potential of offering an

acceptable solution (^) Docsity.com^4

Selected Applications

• Games: Chess, SimCity
• Image recognition
• Medical diagnosis
• Robots
• Business intelligence

Genetic Algorithms (1)

• Based on Darwin's evolutionary principle of ‘survival of the fittest’
• GAs require the ability to recognize a good solution, but not how to get to that solution

Rulebased Systems (1)

• Based on the principles of the logical reasoning ability of humans

The Right Technique

• Selection of the right AI technique requires intimate knowledge about the problem as well as the techniques under consideration
• Real problems may require a combination of techniques (AI and/or nonAI) for an optimal solution

Three exciting areas areas of AI

applications

Autonomous Web Agents (1)

• Computer program that performs various actions continuously, autonomously on behalf of their principal!

Decision Support Systems

• Interactive software designed to improve the decision-making capability of their users
• The do not make decisions - just assist in the process

Data Management

• Keeping track of a few dozen data items is straight forward
• However, dealing with situations that involve significant number of data items, requires more attention to the data handling process
• Dealing with millions - even billions - of inter- related data items requires even more careful thought

BholiBooks.com (1)

• Consider the situation of a large, online bookstore
• They have an inventory of millions of books, with new titles constantly arriving, and old ones being phased out on a regular basis
• The price for a book is not a static feature; it varies every once in a while

BholiBooks.com(3)

• For each order, the customer’s particulars –_ name, address, phone number, credit card number – are required
• Generally, that data is not deleted after the completion of the transaction; instead, it is kept for future reference

BholiBooks.com(4)

• All the transaction activity and the inventory changes result in: - Thousands of data items changing every day - Thousands of additional data items being added everyday
• Keeping track & taking care (i.e. management) of all that constantly changing and expanding data is not a trivial task and requires disciplined attention and actions for ensuring the smooth & profitable operation of the bookstore (^) Docsity.com^20