Data Analytics and Big Data
Accelerating results with Analytics
Data is everything, everything is data. At the heart of every business transformation is data. In this era of GenAI, being data-ready gives you a competitive advantage. We partner with clients from strategy through implementation, building modern data platforms on AWS, Azure, and Google Cloud. We design scalable architectures and data pipelines that integrate diverse sources, ensuring quality and consistency. Our data engineers leverage the help of analytics, BI, and AI tools to unlock value, which involves making use of predictive analysis models and ML to help forecast trends and optimize operations in real time.
How do we help
We help organizations maximize their potential from data, helping them turn it into value, and actively manage/automate data for scale to make the right decisions.
We take a pragmatic approach and emphasize transparent planning and measurable outcomes. We won’t oversell — instead, we outline clear milestones.
We follow a governance-first methodology
01
Strategy & Assessment
We begin by understanding your business goals, data maturity, and regulatory requirements. We map data sources and processes to identify gaps and opportunities, ensuring GDPR/data-protection controls are considered from the outset.
02
Design & Architecture
Whether it’s a data lake on cloud storage or a modern data warehouse, we apply best practices so raw data can flow into analytics-ready datasets. We plan for data cataloging, metadata, and lineage to support governance and data quality.
03
Cloud & Integration
We build reliable data pipelines and ETL/ELT processes, backed by our Cloud Center of Excellence for resilient, multi-cloud deployments—ensuring your workloads run efficiently, wherever it makes the most sense.
04
Iterative Delivery
We build in agile sprints, releasing analytics and dashboards in phases—ensuring data models, reports, and AI prototypes are continuously validated and refined based on real user feedback.
Our Data Analytics Service Pillars
Data Lakehouse Architecture
Data Visualization
Predictive Analysis
From data to decisions — unlock value at every step.
Our data services bridge the gap between complexity and clarity—so your business can move with confidence.
FAQ
How do you ensure data privacy and GDPR compliance?
We incorporate privacy by design. This means classifying sensitive data, encrypting it, and enforcing access controls from day one. We also build in consent management and data subject rights workflows. As regulators note, under GDPR “stricter rules will apply to the collection and use of personal data” and organizations must remain transparent and accountable. Our governance framework explicitly addresses these requirements, with documented policies and audit trails.
Which cloud platforms do you support?
We work across all major public clouds (AWS, Microsoft Azure, Google Cloud). Each has robust data services, and we are certified on all three. You can run workloads on one or multiple clouds for resilience and cost efficiency. Leading cloud vendors promote interoperability; for example, AWS explicitly supports open standards to enable seamless integration with other clouds. We tailor the architecture to your strategy, whether that means a single cloud or a hybrid/multicloud setup.
What industries have you served?
Our work spans healthcare (hospitals, pharma), retail (e-commerce, FMCG) and finance (banking, insurance), among others. In healthcare, we helped a hospital chain build an analytics platform for patient outcomes and compliance reporting. In retail, we integrated POS, inventory, and CRM data for smarter demand forecasting. In finance, we created a secure data warehouse for real-time risk analysis. Cross-industry experience means we can apply domain-specific best practices while focusing on your unique challenges.
How do you leverage AI in data projects?
We use AI to amplify insights, not just as a buzzword. For example, we build predictive models (using regression, trees or neural networks) to forecast sales or detect fraud. We also experiment with generative AI: linking language models to your data through RAG techniques so that users can ask natural-language questions of the data. All AI is rigorously validated and integrated with your dashboards and reports. By combining modern AI with established BI tools, we deliver enriched analytics, like ML-infused dashboards that surface anomalies or recommendations in real time.
