Business team reviewing Power BI analytics dashboards and KPIs built on a Microsoft Fabric and Databricks Lakehouse platform

Data & Analytics

Turn Fragmented Data Into a Single Source of Truth

From public sector data lakes to retail analytics platforms, Qrestik's Data & Analytics practice builds governed, AI-ready intelligence on Microsoft Fabric and Databricks.

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Overview

Our Data & Analytics practice has delivered unified data lake platforms for public sector clients managing 20+ departments, and retail analytics platforms consolidating five or more point-of-sale systems into a single governed reporting layer — work that established our Data & AI Centre of Excellence. We combine deep platform expertise with business domain knowledge to ensure the analytics solutions we build are genuinely used and valued by the business.

Most enterprises do not have a data problem — they have a fragmentation problem. ERP, CRM, POS, IoT, and external data sources each hold pieces of the truth, but no single platform governs how that data is ingested, refined, secured, and consumed. The result is duplicated reporting effort, inconsistent KPIs across departments, and leadership decisions based on spreadsheets that are already out of date when they reach the boardroom.

Qrestik's Data & Analytics practice builds Lakehouse platforms on Microsoft Fabric and Databricks that solve this at the architecture level — not with another dashboard on top of broken pipelines. We apply Medallion Architecture (Bronze, Silver, Gold) to progressively refine raw data into business-ready datasets, implement governed semantic layers in Power BI, and establish role-based access and lineage tracking through Unity Catalog and Microsoft Purview. Our reference delivery patterns include public sector data lakes consolidating 20+ departments and retail analytics platforms unifying five or more POS systems — both delivered as production platforms, not proofs of concept.

We combine platform engineering depth with business domain knowledge. A data platform only creates value when business users trust it and use it daily — so every engagement includes semantic layer design, executive and operational dashboards, and AI-augmented analytics (Power BI Copilot, AI Visuals) that turn static reports into conversational interfaces for users who do not write SQL or DAX.

Capabilities

Data Lakehouse Architecture

Lakehouse platforms on Microsoft Fabric and Databricks, applying Medallion Architecture (Bronze, Silver, Gold) to progressively refine raw data into business-ready, analysis-grade datasets.

Data Pipeline Engineering

Automated ingestion using Fabric Data Factory, Dataflows Gen2, and Databricks Autoloader — supporting both API-based and flat-file integration depending on source system maturity.

Power BI Semantic Layer & Dashboards

Governed semantic layer design plus interactive Power BI dashboards with drill-down, row-level security, incremental refresh, and responsive layouts for desktop, tablet, and mobile.

AI-Augmented Analytics

Power BI Copilot, AI Visuals (Decomposition Tree, Key Influencers, Smart Narrative), and LLM-powered visualization — turning dashboards into natural-language interfaces for business users.

Data Governance & Security

Centralised metadata management, RBAC, and audit logging via Databricks Unity Catalog and Microsoft Purview, ensuring analytics outputs are accurate, consistent, and auditable.

Data Strategy & Roadmap

We work with CIOs and CDOs to assess the current data landscape, define a future-state architecture, and build a prioritised roadmap for data maturity improvement.

Who We Serve

Industries & Client Profiles

We work with CIOs, CDOs, and heads of analytics in organisations where data fragmentation is limiting operational visibility, regulatory reporting, or executive decision-making.

Public Sector — multi-department data consolidation and governed citizen service analytics
Retail & CPG — POS consolidation, store performance, and supply chain visibility
BFSI — regulatory reporting, customer analytics, and fraud monitoring platforms
Manufacturing — production, quality, and supply chain KPI dashboards
EPC & Construction — project cost, procurement, and field operations reporting

Delivery Approach

How We Deliver

Our data platform engagements follow a maturity-based roadmap — establishing governed ingestion and quality first, then semantic layers and dashboards, then AI-augmented analytics.

Data Discovery Workshop

Source system inventory, stakeholder interviews, KPI definition, and current-state architecture assessment — producing a prioritised data maturity roadmap.

Lakehouse Foundation

Platform setup on Microsoft Fabric or Databricks, Medallion Architecture implementation, ingestion pipeline build, and governance framework (Unity Catalog / Purview).

Semantic Layer & Dashboards

Power BI semantic model design with row-level security, executive and operational dashboards, and responsive layouts for desktop, tablet, and mobile.

AI-Augmented Analytics

Power BI Copilot, AI Visuals, and natural-language querying — enabling business users to explore data without depending on the analytics team for every question.

Handover & Managed Support

Documentation, admin training, and optional managed services retainer for ongoing pipeline monitoring, enhancements, and quarterly business reviews.

Why Qrestik

Qrestik has delivered production Lakehouse platforms for public sector authorities managing 20+ departments and retail groups consolidating five POS systems — work that established our Data & AI Centre of Excellence. We are platform-agnostic between Microsoft Fabric and Databricks, selecting based on your existing Microsoft investment, data residency requirements, and team skills — not vendor preference. Our delivery teams span the USA, UAE, UK, India, and Saudi Arabia.

Frequently Asked Questions

Should we use Microsoft Fabric or Databricks for our data platform?

The choice depends on your existing technology estate, team skills, and licensing position. Microsoft Fabric is the natural choice for organisations already invested in Microsoft 365, Azure, and Power BI — providing an integrated Lakehouse, pipeline, and reporting experience in one platform. Databricks is preferred when you need advanced Spark-based processing, multi-cloud portability, or have existing Databricks expertise. Qrestik delivers both and recommends based on a structured assessment, not a default stack.

What is Medallion Architecture and why does it matter?

Medallion Architecture organises data into three refinement layers: Bronze (raw ingestion), Silver (cleansed and conformed), and Gold (business-ready analytics datasets). This pattern ensures data quality improves progressively, lineage is traceable, and business users consume Gold-layer datasets that are governed, documented, and fit for purpose — rather than querying raw source extracts directly.

How does Qrestik handle data governance and security?

We implement centralised metadata management, role-based access control, and audit logging via Databricks Unity Catalog and Microsoft Purview. Row-level and object-level security in Power BI ensures users see only the data they are authorised to access. For public sector and BFSI clients, we design platforms to satisfy data residency, regulatory reporting, and audit requirements from the architecture phase — not as a retrofit.

Can Qrestik consolidate multiple POS or ERP data sources?

Yes. We have delivered retail analytics platforms consolidating five cloud-based POS systems into a single Microsoft Fabric Lakehouse, and public sector platforms unifying 20+ departmental data sources on AWS Databricks. Integration methodology is matched to each source system — API-based where available, structured flat-file export as a fallback — with automated, scheduled ingestion pipelines.