Data & Analytics
Data Analytics
Define the direction. Build the foundation. Turn data into decisions: one capability that runs from the first strategy conversation to the insight somebody acts on.
Most organisations do not have a data problem so much as a sequencing problem. We work strategy, engineering and analytics in that order.
What we deliver
What Data & Analytics covers
Four capabilities that run in sequence, from the first strategy conversation to the platform we operate for you.
1. Data & AI Strategy
Start from the decision, not the platform. What business decision is this data supposed to support? That question shapes everything that follows.
- Data & AI Strategy Roadmaps: Clear transition plans focused on high-ROI business outcomes.
- Architecture & FinOps Advisory: Platform choice and capacity sizing across Fabric, Azure, Databricks and Snowflake, balancing performance and spend.
- Governance by Design: Catalog, lineage, access policies and privacy controls built into pipelines and deployment (Purview, Unity Catalog).
- AI & GenAI Readiness: Unifying and structuring unstructured and structured data for RAG and LLM integration.
2. Lakehouse & Modern Data Engineering
Foundations that don't depend on heroics to keep running. A modern platform for analytics and AI, built around your team rather than a template.
- Unified Lakehouse Engineering: Medallion architecture setup across Microsoft Fabric, Databricks and cloud warehouses.
- Modern ELT & Real-Time Ingestion: Low-latency streaming pipelines and automated data ingestion workflows.
- DataOps & Quality Observability: Automated pipeline testing, drift detection and proactive data validation.
- AI-Assisted Modernization: Moving Synapse, SQL Server and Oracle estates to Fabric and the cloud, with LLM-assisted code conversion and lineage mapping reviewed by engineers.
- Unstructured Data Pipelines: Document parsing, embeddings and vector indexes for RAG.
3. Decision Intelligence & Advanced Analytics
One definition of every metric, for people and agents. Reporting people trust, self-service that doesn't fragment, and models that reach the workflow.
- Enterprise Semantic Models & Metric Layer: Governed KPIs in Power BI and Fabric, with Direct Lake performance.
- Self-Service & Embedded Analytics: Secure, friction-free reporting integrated directly into daily operational software.
- Predictive Analytics & Applied Machine Learning: Forecasting, anomaly detection and risk models built into operational workflows. See AI & ML
- Conversational Analytics: Fabric data agents and Copilot, grounded on your semantic model.
- Agent-Ready Data: Your governed data and business context exposed to AI agents through MCP and APIs, with the same security as your reports.
4. Managed Data Operations
We run what we build. The platform keeps getting faster, cheaper and cleaner after go-live, not slowly worse.
- Platform Operations: Monitoring, SLAs and incident response for pipelines and capacity.
- FinOps & Performance Tuning: Cost audits, capacity right-sizing and query optimization across Fabric and Snowflake, with spend tracked per workload.
- BI Lifecycle Management: Release control, usage tracking and retiring reports nobody uses.
- Build-Operate-Transfer: We hand the platform to your team when you're ready.
Building agents, RAG or GraphRAG on top of this data?
Data agents, MCP integration, retrieval pipelines and agent governance live with our AI & ML Engineering practice.
Where to start
Fixed-scope entry points
Start where the work is blocked. Each engagement is scoped up front and ends with a plan you can act on, whether or not we do the build.
- 01
AI Readiness Assessment
Score your data on quality, access and context, and get a ranked list of the gaps to close before funding an AI use case.
Scope this with us: AI Readiness Assessment - 02
Fabric Migration Assessment
Inventory, effort and sequencing for moving Synapse, SQL Server or Oracle estates to Microsoft Fabric.
Scope this with us: Fabric Migration Assessment - 03
Power BI Health Check & Rationalization
Find duplicate models, unused reports and slow queries, then consolidate onto governed semantic models.
Scope this with us: Power BI Health Check & Rationalization - 04
Platform Cost & Capacity Review
See what drives your Fabric or Snowflake spend, what to right-size, and where to save without losing performance.
Scope this with us: Platform Cost & Capacity Review
How we engage
Engagement models
- Advisory services
- Data platform build
- Managed services
Related
Related work
3 of 3 shown
Microsoft & Azure
Azure consulting, migration, managed services and governance, plus the Microsoft data and low-code estate: Fabric, Power BI and Power Platform.
ServiceAI & Machine Learning
Predictive, classification and computer-vision models built on your own data, each with a measured baseline and an honest read on where it breaks.
ServiceML Ops & Governance
The layer between a model that works and a model that keeps working: deployment pipelines, feature parity, drift monitoring, retraining gates and rollback.
Questions
Common questions
- Do we have to start with strategy?
- No. Start where the work is blocked. If the platform is the constraint we start there and formalise the strategy alongside it. What we will not do is build for eighteen months before anyone sees a number.
- Do you start from the platform or from the reporting?
- From the decision. What business question is this data supposed to answer? That determines the architecture, not the other way round.
- Can you work with the platform we already have?
- Usually, yes. Replacing a warehouse is a decision with its own business case; it is not a precondition for getting value out of the data already in it.
Why Praval
How we work with you.
Industry expertise
Seasoned professionals with deep industry knowledge and hands-on experience driving digital acceleration across sectors.
Client-centric approach
We prioritise understanding your challenges, goals and culture, and deliver solutions tailored to them rather than to a template.
Proven methodologies
Industry-leading frameworks and best practice, giving a structured and repeatable route to the outcome you asked for.
Collaborative partnership
We work as an extension of your organisation: transparency and agility during the engagement, and a handoff that holds after it.
- 01
Initial consultation
We evaluate your current systems and identify where the value is.
- 02
Customized plan
We design a solution scoped to your business, not to a template.
- 03
Design & development
We build and transition with minimal disruption to live operations.
- 04
Monitoring & support
Continuous oversight and support keep the estate healthy afterwards.