What is data analysis?
Data analysis is the process of inspecting, cleansing, transforming and modelling data to discover useful information, inform conclusions and support decision-making.
Why data analysis matters
- Identify patterns and trends in business data
- Make informed decisions based on facts
- Anticipate outcomes and market trends
- Optimise processes and operations
- Improve customer satisfaction and engagement
- Reduce costs and increase profitability
The four types of analytics
Descriptive
What happened?
- Sales reports
- Website traffic
- Customer demographics
Diagnostic
Why did it happen?
- Root-cause analysis
- Performance issues
- Customer churn reasons
Predictive
What is likely to happen?
- Sales forecasting
- Risk assessment
- Market predictions
Prescriptive
What should we do about it?
- Optimisation recommendations
- Action plans
- Strategic guidance
Key benefits
Data-driven decisions
Decisions based on evidence rather than intuition.
Improved efficiency
Find bottlenecks and optimise processes.
Competitive advantage
Predictive insights and market intelligence.
Cost reduction
Identify savings and eliminate wasteful spending.
How Gigarta helps
Data analysis solutions tailored to your organisation.
Analytics solutions
Custom analytics that turn raw data into actionable insights.
- Real-time dashboards
- Interactive visualisations
- Automated reporting
- Custom KPI tracking
Statistical analysis & modelling
Statistical methods and machine learning models for deeper insight.
- Regression analysis
- Classification models
- Time-series forecasting
- Clustering
Business intelligence
BI platforms for strategic decision-making.
- Executive dashboards
- Performance metrics
- Trend analysis
- Comparative analytics
Data visualisation & reporting
Clear visuals that tell your data’s story.
- Interactive charts
- Custom reports
- Data storytelling
- Mobile-friendly dashboards
Predictive analytics
Machine-learning predictions for future planning.
- Demand forecasting
- Risk prediction
- Customer-behaviour analysis
- Market-trend analysis
Data strategy consulting
Guidance on data governance and your analytics roadmap.
- Data assessment
- Analytics strategy
- Implementation planning
- ROI optimisation
Frequently asked questions
What is the difference between data analysis and data engineering?
Data engineering builds and maintains the pipelines and storage that collect and prepare data. Data analysis uses that prepared data to answer questions, build dashboards and make predictions. Gigarta offers both.
What are the four types of analytics?
Descriptive analytics explains what happened, diagnostic analytics explains why, predictive analytics estimates what is likely to happen, and prescriptive analytics recommends what to do about it.