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Walk on the Beach

Data Analytics

DRIVING    GROWTH THROUGH     DATA

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OUR  APPROACH

4-Stage Data Analytics Model - DDGM

1. Define Enterprise Business Intelligence Strategy

  • Align analytics roadmap with business strategy

  • Define use cases across departments

  • Establish data-driven culture and sponsorship

2. Design Modern Data Platform

  • Design Data Warehouse

  • Select BI Tools (e.g., Power BI, SSRS)

  • Build ETL pipelines (e.g.,  Python, SQL)

  • Ensure data profiling and quality checks

  • Perform EDA & modelling, Deployment  (Pandas, Scikit-learn,API-Postman)​

 

  •  Stakeholder interviews

  •  BI maturity assessment

  •  Business process analysis

  •  Establish data-driven culture and leadership sponsorship

  • Azure/SQL Server/MS Fabric (Data Lake, DWH)

  • Power BI for dashboards

  • Python EDA and Profiling (Pandas, NumPy, Seaborn, Scikit-learn)

  • SQL-based profiling tools and ETL

3. Apply Data Governance on Data Assets

  • Define data ownership & stewardship

  • Set up data access policies & security

  • Ensure regulatory compliance (Australian Privacy Act, GDPR, ISO)

  • Implement data catalog and lineage tracking

  • Define KPI's and Balanced Scorecard to monitor overview of the Program​

4. Continuous Monitoring & apply AI-Driven Enhancements

  • Monitor KPIs and usage metrics.

  • Use AI/ML for predictive alerts & optimization.

  • Manage people & changes effectively.

  • Continuous feedback loops with users.

  • Introduce and Train staff for self service BI Functionalities.​

  • Data quality & validation scripts.

  • Role-based access control.

  • Policies and Procedures to govern the data assets.

  • Audit logs and encryption.

  • Data Lineage ( Azure Purview )

  • Power BI AI analytics.

  • Change management frameworks (ADKAR).

  • Scikit Learning Models and Flask API/Postman to analyse data requests.

  • MLOps for ongoing model tuning.

  • Incorporate modern AI technologies.

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