Technology
Data and BI
Big data, business intelligence, machine learning, RPA and advanced analytics: we turn data into smart decisions.
What we do
We turn data into business assets that create value
From scalable big data architectures and integrated BI platforms to machine learning models and intelligent process automation: extract value from your data, automate complex decisions and anticipate outcomes with precision. Clean data, reliable pipelines, actionable insights.
Big Data and Scalable Data Platforms
High-volume, high-velocity, high-variety data architectures.
- Distributed processing platforms: Apache Hadoop, Spark, Flink; cluster management and auto-scaling
- Data lakes and data warehouses: Design, governance, metadata management, lineage tracking
- Data ingestion: Kafka, AWS Kinesis, Azure Event Hubs; real-time and batch processing
- Distributed storage: HDFS, S3, Azure Data Lake Storage, partitioning and compression
- Real-time processing: Stream analytics, event windowing, stateful processing
- Data management: Data quality, cleansing, deduplication, validation rules
Business Intelligence: Dashboards and Analytics
Data visualisation, KPIs and integrated reporting for executive decision-making.
- Leading BI platforms: Power BI, Tableau, Qlik, Looker; real-time data integration
- Dashboard development: KPI design, semantic layers, drill-down capabilities, mobile dashboards
- Executive dashboards: Scorecard design, balanced scorecards, trend analysis
- Reporting and self-service BI: Ad hoc reporting, automated report generation, scheduled distribution
- Data storytelling: Visual narrative, contextualised insights, data-driven recommendations
- Analytical modelling: Star schema, dimensional modelling, aggregation design
Machine Learning: Predictive Models and AI
Machine learning algorithms for prediction, classification and optimisation.
MLOps: Model Operationalisation
Model pipelines, monitoring, versioning and ML governance in production.
- ML Pipelines: Automated data processing, feature engineering, model training and validation
- Model versioning: Model registry, experiment tracking, reproducibility, version rollback
- Deployment and serving: Model containerisation, REST/gRPC APIs, batch prediction services
- Model monitoring: Data drift detection, model performance tracking, feature importance analysis
- Automated retraining: Scheduled retraining, trigger-based updates, feedback loops
- Governance and interpretability: Model explainability (SHAP, LIME), auditing, compliance tracking
RPA: Robotic Process Automation
Intelligent bots that automate high-volume, low-cognitive-value processes.
- Process mapping and analysis: Opportunity identification, ROI analysis, benefit simulation
- Bot development: UiPath, Power Automate, Blue Prism; attended and unattended robots
- Multi-application integration: Web scraping, API integration, legacy system automation, database access
- Process orchestration: Multi-bot workflows, error handling, escalation rules, exception management
- Monitoring and optimisation: Bot performance dashboards, capacity planning, cost per automation
- Governance and CoE: Bot standardisation, best practices, enterprise-wide scalability
Advanced Analytics: Descriptive, Predictive and PrescriptiveALDIA differentiator
Advanced statistical and mathematical techniques for strategic decision-making.
- Descriptive analytics: Aggregations, segmentation, correlation, exploratory data analysis (EDA)
- Predictive analytics: Predictive models, scenario simulation, stress testing, what-if analysis
- Prescriptive analytics: Mathematical optimisation, optimal planning, resource allocation, automated decision-making
- Causal analysis and inference: Causal inference, advanced A/B testing, user matching, attribution modelling
- Behavioural analytics: Customer journey analysis, cohort analysis, churn prediction, lifetime value modelling
- Advanced statistical methods: Bayesian inference, time series analysis, anomaly detection, outlier handling
Data Governance: Quality, Privacy and Compliance
Comprehensive data management, quality and security strategies.
Our approach
We combine solid data engineering (big data, pipelines, quality) with advanced analytical intelligence (ML, statistics, prescriptive analytics) and corporate governance (compliance, privacy, stewardship). We don’t deliver isolated data: we turn datasets into business assets that drive decisions, automate processes and predict outcomes. Every analysis reproducible, every model monitored, every insight actionable.
Technology
Other disciplines
Cybersecurity
SOC and XDR, cloud security, pentesting, OT/ICS and compliance.
Software development
Web and mobile applications, low code, APIs, architecture and QA.
Infrastructure
Systems, storage, networks and monitoring.
Enterprise platforms
SAP, Oracle, Salesforce, Workday, Pega and Murex.
Do you have a data or analytics project?
Tell us what data you have, which decisions you want to anticipate and which processes you need to automate. We’ll tell you how we would approach it, with which team and on what timescale.