Data Strategy & Roadmapping
We begin with understanding your business goals, current data maturity, and key challenges. From there we develop a data/BI strategy and roadmap—identifying priority use-cases, defining key performance indicators (KPIs), and establishing a path for adoption and growth.
Data Collection, Integration & Architecture
- Aggregate data from multiple sources (e.g. accounting systems, CRM, ERP, marketing, operations).
- Cleanse, validate and standardize the data to ensure quality and consistency.
- Build a coherent data architecture (data warehouses, data lakes, or hybrid/cloud setups) so that data is stored securely, scaled, and accessible.
- Set up semantic/metamodel layers to enable meaningful relationships and “single source of truth.”
Analytics & Modelling
- Perform descriptive analytics: what has happened.
- Diagnostic analytics: why did it happen (correlations, root causes).
- Predictive analytics: forecasts, trends, scenario modelling (“what-if” analysis).
- Where appropriate, begin introducing machine learning or AI tools for more advanced forecasting, anomaly detection, clustering, etc.
Visualization & Reporting
- Design and build interactive dashboards, visual reports, and KPI-monitoring tools.
- Enable real-time or near-real-time dashboards so that decision-makers can see data refreshes, alerts, and key metrics dynamically.
- Ensure reports are intuitive, clear, and tailored to the audience (executives, operations, marketing, etc.).
Self-Service BI & User Empowerment
- Provide user-friendly tools and interfaces that allow non-technical users to explore data, generate their own reports, and extract insights without heavy reliance on IT.
- Train staff, build data literacy, and embed culture of data-driven decision making.
Governance, Security & Compliance
- Define policies around data access, data privacy, data retention, and security.
- Ensure compliance with relevant regulations (e.g. GDPR) when handling personal or sensitive data.
- Implement data governance frameworks to monitor data quality, lineage, accountability.
Ongoing Support & Optimization
- Monitor BI systems for performance; ensure dashboards and architecture scale with your data volume and complexity.
- Update models, add new data sources, optimize ETL pipelines (extract, transform, load).
- Periodic review: Are KPIs still relevant? Are new business questions emerging? What improvements can be made?