Unit 6: Data Processing
Data Processing 1
Foundations of Business Data Analysis
ICT 110: IT for Business
Session Roadmap (60 Minutes)
This session builds the analysis foundation for all business functions.
- 0-10 min: What data processing means in business
- 10-25 min: Analysis workflow and spreadsheet methods
- 25-40 min: Pivot summaries and insight generation
- 40-55 min: Visualization and chart selection
- 55-60 min: Review and management takeaways
What Is Data Processing in Business?
Data processing is the structured workflow of collecting, cleaning, analyzing,
and presenting data so managers can make reliable decisions.
- Finance: Budget variance and profitability checks
- Operations: Inventory and process efficiency tracking
- HR: Workforce and performance analysis
- Marketing: Campaign impact and customer trends
The 5-Step Analysis Flow
- Ask: Define the business question clearly.
- Clean: Fix missing values, duplicates, and format issues.
- Analyze: Use formulas and summaries to find patterns.
- Visualize: Convert results into charts for fast understanding.
- Act: Make a decision and track business impact.
Tool Layer 1: Spreadsheets
Excel and Google Sheets remain the most used tools in business analysis.
Strengths
- Fast for ad-hoc analysis
- Accessible to non-technical users
- Strong formula and table support
- Effective for small and medium datasets
Common Use Cases
- Finance planning and cost tracking
- Operations inventory and service logs
- HR attendance and payroll support
- Marketing lead and sales summaries
Essential Spreadsheet Methods
Logical
IF, AND, OR
Example: Flag delayed deliveries and low stock items.
Lookup
VLOOKUP, HLOOKUP
Example: Merge employee data from separate sheets.
Aggregate
SUMIF, COUNTIF
Example: Total revenue by region or sales rep.
Pivot-Based Decision Support
Business Example
An HR team needs average salary by department and training completion rates.
Pivot setup: Rows = Department, Values = Avg Salary + Count Training Status
Outcome: Department-level insight in minutes instead of manual processing.
Why Visualization Is Mandatory
- Speed: Patterns are detected faster than in raw tables.
- Clarity: Managers can understand performance at a glance.
- Communication: Cross-functional teams align faster on visual evidence.
- Action: Trends and outliers become easier to prioritize.
The goal of a chart is business clarity, not decoration.
Choosing the Right Chart
- Bar/Column: Compare categories
- Line: Show trends over time
- Pie/Donut: Show parts of a whole
- Scatter: Show relationships between variables
Rule: Select chart type based on the decision needed.
Example: If leadership asks "Which region is declining?" use a trend chart, not a pie chart.
From Reports to Dashboards
As data volume and complexity increase, organizations move from static files to interactive dashboards.
- Spreadsheet: Strong for local analysis and flexible models
- BI Dashboard: Strong for shared, interactive, multi-source insight
- Management Value: One screen can show KPIs across Finance, HR, Operations, and Marketing
Key Takeaways
- 1) Data processing is a business discipline, not only a technical task.
- 2) A clean workflow (ask, clean, analyze, visualize, act) improves decision quality.
- 3) Spreadsheets remain essential for operational and tactical analysis.
- 4) Pivot summaries and proper charting accelerate management insight.
- 5) The next step is integrated reporting and domain-specific analytics.