Managing Data | Year 8 Computing (Cambridge) PDF Download

Data Types in Databases

• Advanced data types used in databases include arrays and linked lists.
• Arrays allow storing multiple values of the same type in a structured format.
• Linked lists organize data into nodes with pointers, facilitating efficient data manipulation.

Collecting Qualitative Data

• Techniques for collecting qualitative data include interviews and focus groups.
• Example: Interviewing customers about their shopping experiences.
• Example: Conducting focus groups to gather opinions on new product ideas.

Data Visualization

• Data visualization presents data in graphical formats like charts and graphs.
• Example: Creating a bar chart to show sales figures over a year.
• Example: Using a pie chart to illustrate market share among competitors.

Purpose of Managing Databases

• Managing databases involves organizing and storing data for easy retrieval and manipulation.
• Example: Storing customer information in a CRM system for efficient client management.
• Example: Keeping inventory records to track stock levels and manage orders.

Spreadsheet Functions for Data Analysis

• Common spreadsheet functions include SUM for calculating totals.
• Example: Using SUM to add up sales figures for a quarterly report.
• Example: Applying AVERAGE to find the average score of a class.

Pivot Tables for Data Summarization

• Pivot tables automatically summarize data by calculating totals and averages.
• Example: Summarizing monthly sales data by product category.
• Example: Analyzing customer feedback ratings across different service areas.

Data Normalization in Database Management

• Data normalization reduces redundancy and improves data integrity.
• Example: Storing customer details in separate tables linked by a unique customer ID.
• Example: Ensuring each product record only contains information relevant to that product.

Role of Data Mining

• Data mining extracts patterns and trends from large datasets.
• Example: Predicting customer behavior based on past purchasing patterns.
• Example: Identifying market trends from social media interactions.

Data Visualization Tools

• Tools like Tableau create interactive dashboards and reports from data sources.
• Example: Visualizing website traffic data to understand visitor demographics.
• Example: Creating a geographic map showing sales distribution across regions.

Structured Query Language (SQL)

• SQL facilitates querying and manipulating databases.
• Example: Writing a SELECT statement to retrieve customer contact information.
• Example: Using UPDATE to modify product prices based on market changes.