ICT 0417 - Topic 7: The Systems Life Cycle

Objective: Know and understand the use of live data

This section focuses on the importance and application of live data within the different stages of a system's life cycle. Understanding live data is crucial for effective system development, maintenance, and improvement.

What is Live Data?

Live data refers to information that is currently being generated, collected, and used by a system. It is dynamic and constantly changing, providing real-time insights into system performance, user activity, and external factors.

Why is Live Data Important?

Live data offers several key benefits:

• Real-time insights: Provides up-to-the-minute information for informed decision-making.
• Performance monitoring: Allows for continuous tracking of system performance and identification of potential issues.
• User behaviour analysis: Helps understand how users interact with the system, enabling improvements to usability.
• Proactive maintenance: Enables early detection of problems, reducing downtime and improving system reliability.
• Improved decision-making: Supports data-driven decisions throughout the system's lifecycle.

Live Data in the Systems Life Cycle

Live data plays a vital role in each stage of the systems life cycle:

1. Planning

Before a system is developed, analysis of existing live data (if available) is crucial. This helps identify needs, potential problems, and inform design decisions. For example, analyzing website traffic data can inform the design of a new e-commerce platform.

2. Analysis

During the analysis phase, live data is collected and examined to fully understand the requirements of the system. This might involve gathering data from existing systems, user surveys, or website analytics. The analysis identifies what the system needs to do and how it should behave in real-world scenarios.

3. Design

The design phase considers how the system will handle live data. This includes designing databases, user interfaces, and data processing algorithms to efficiently collect, store, and present live information. Scalability and data security are key considerations.

4. Implementation

During implementation, systems are set up to receive and process live data. This involves configuring data feeds, integrating with existing systems, and ensuring data integrity. Testing with live data is essential to identify and fix any issues before the system goes live.

5. Testing

Testing with live or simulated live data is a critical step. This ensures the system can handle real-world data volumes and accurately process information. Different types of testing, such as load testing and stress testing, are used to evaluate system performance under various conditions.

6. Deployment

Once the system is tested, it is deployed into a live environment. Data feeds are activated, and the system begins collecting and processing real-time information. Monitoring is essential during the initial deployment phase to ensure stability and identify any unforeseen issues.

7. Maintenance

Ongoing maintenance involves monitoring live data to identify performance issues, security threats, and user feedback. Data analysis helps in identifying areas for improvement and implementing updates and enhancements. Regular backups of live data are crucial for disaster recovery.

8. Review

At the end of the system's lifecycle, a review is conducted to assess its effectiveness and identify lessons learned. Analysis of historical live data provides valuable insights for future system development. This helps in understanding what worked well and what could be improved in subsequent iterations.

Examples of Live Data Use

Here are some examples of how live data is used in various systems:

1. E-commerce website: Tracking website traffic, sales figures, and customer behaviour to optimize product offerings and marketing campaigns.
2. Social media platform: Monitoring user activity, engagement metrics, and trending topics to personalize content and improve user experience.
3. Financial trading system: Real-time stock prices, market data, and trading volumes to facilitate informed trading decisions.
4. Weather forecasting system: Current weather conditions, atmospheric data, and radar information to provide accurate forecasts.
5. Traffic management system: Real-time traffic flow data to optimize traffic light timings and route drivers.

Data Security and Privacy

When dealing with live data, it's essential to prioritize data security and privacy. This includes implementing appropriate security measures to protect data from unauthorized access, modification, or disclosure. Compliance with data protection regulations (e.g., GDPR) is crucial.

Stage of Life Cycle	Use of Live Data	Example
Planning	Analyze existing data to identify needs.	Website traffic analysis for e-commerce platform design.
Analysis	Collect and examine data to define system requirements.	User surveys and website analytics for a new application.
Design	Design data storage and processing to handle real-time data.	Database design for a financial trading system.
Implementation	Configure systems to receive and process live data.	Integrating a weather forecasting system with a mobile app.
Testing	Test with live or simulated live data to ensure accuracy.	Load testing a website with simulated user traffic.
Deployment	Activate data feeds and monitor system stability.	Launching a social media platform with real-time user feeds.
Maintenance	Monitor data for performance issues and security threats.	Analyzing server logs for unusual activity.
Review	Analyze historical data to inform future system improvements.	Reviewing sales data to identify areas for product development.