IS 425

Enterprise Information LECTURE 4

Winter 2006-2007

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Agenda

Review/Discussion Exercise HCI / Usability Engineering Data Mining Quiz

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Pulling It Together

1. What kind of aptitude does a security engineer need?

2. What skills does a security engineer need?

3. What kind of aptitude does a software engineer need?

4. What skills does a software architect need?

5. Are they different?

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Exercise

1. Each team debates and comes up with the tradeoffs between doing the risk analysis in the management inception phase and doing it in the deployment phase of a large scale IT project.

2. Is it possible to do risk analysis on different security threats at different times? If so, then indicate which view/phase is best for threat.

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HCI – Usability Engineering HCI –

Grew out of shared interest between Cognitive scientists Computer scientists

Learning challenges of interactive systems Using them Designing them

Usability – The quality of a system with respect to: Ease of learning Ease of use User satisfactionScope expands to cover social/organizational aspects of systems development/use

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Usability

Three distinct, complementary perspectives contribute: Human performance

time and error Learning and cognition

mental models of plans and actions

Collaborative activitydynamics and workplace context

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Usability Engineering

Focus on Design of the user interface Requirements analysis Envisioning the system

Relies on use of: Iterative development Tradeoff analysis resulting in design rationale User Interaction Scenarios

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User Interaction Scenario

Describes behaviors and experiences of actors

Has a plot – sequences of Actions Events

Task goals: High-level is the primary goal of the scenario Sub-goals are the lower-level goals

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User Interaction Scenarios

Stories about people and their activities Elements

Setting –details that motivate/explain or starting state Actors – humans interacting Task goals – motivate actions Plans – mental activity directed at converting goal into a

behavior Evaluation – mental activity directed at interpreting features

of the situation Actions – observable behavior Events – external actions or reactions

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User Interaction Scenario Analysis is to find those things that affect goal

achievement by Aiding Obstructing Being irrelevant

Is type of Use Case which is: More general Includes multiple responses (not just one) Intended to describe what system will do Can specify the user-system exchanges for scenario

examination Useful in Tradeoff analysis

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Tradeoffs Addressed by scenarios 5 mentioned in text

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Scenario-Based Usability Engineering

Overview Iterative Interleaved Idealized

progression

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Scenario Based Analysis Phase

Used to evoke reflection / discussion Claims

Stimulate analysis and refinement Lists important features of a situation Lists impacts on users experiences Organize / documents “what-ifs” for prioritizing

alternatives

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Scenario Based Design Phase

3 sub-stages of scenarios Activities

narratives of typical or critical services Information

details about info provided Interaction

details of user action and feedback

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Scenario Based Prototyping/Evaluation

Assumption – design ideas in scenarios continually evaluated using prototyping

Evaluation Formative – guides redesign Summative – system verification

“go/no-go” test

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Summary

Combination of structured development and prototyping thru scenarios

Scenarios organize analysis of user needs Scenarios help in uncovering tradeoffs Major focus of development are tradeoff

analysis Thru scenarios can develop measurable

usability objectives

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Data Mining

Definition – process by which analysts apply technology to historical date (mining) to determine statistically reliable relationships between variables.

This lets data tell what is happening rather than testing the validity of rigorous theory against samples of data.

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Data Mining

Required – data warehouses with huge volumes of information to access for finding hidden relationships patterns, affiliations.

Utilize tools of mathematics and statistical testing

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Major Data Mining Technologies

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Data Mining Approaches & Aims Directed – identify relationships between drivers and targets (DIR) Undirected – tools unleashed on data with no guidance (UDIR) Strategic Insight – tools that reduce data into a few key perceptions (HESI) Just-In-Time – tools that analyze data as it arrives at the organization (JIT)

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Data Mining Technologies in Use Clustering algorithms – group data on basis of similarity -- UDIR Association analysis – used to assist sales –JIT Visualization – graphical representation for easy digestion – JIT Slice & dice – extract summary data quickly “on the fly” – DIR Segmentation algorithms – group data by target – DIR Forecasting algorithms – probability of future actions – DIR Regression – finding the relationship between variables – HESI Neural Nets – AI – more intensive analysis using linear,

nonlinear and patterned relationships to identify relationships – HESI

Optimization – uses output from other DM to find best strategy given – HESI

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Personalization

Uses information from tracking, mining and data analysis to customize a person’s interactions with a company’s products, services, Web site and employees

Collaborative filtering (Recommender System) Compare a present user’s interests with those of past

users to offer recommendations Rules-based personalization : based on the subjection of

a user’s profile to set rules or assumptions. Excite.com (My excite start page

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Insights

Who will HCI professionals interact with? Who will DM professionals interact with? What aptitudes are required of HCI

professionals? What aptitudes are required of data mining

professionals?