Loading...
Overview

A global mining enterprise managing high-volume procurement, supplier, policy, and market intelligence documentation across multiple geographies. With rapid digital transformation and expansion, the organization required a modern data platform leveraging Databricks Lakehouse architecture to unify data, enable advanced analytics, and power intelligent decision-making.

“ As enterprise data volumes exceeded 5–10 TB, critical business data remained siloed across SharePoint, shared drives, and legacy repositories. The absence of a unified Data Lakehouse platform limited scalability, governance, and real-time insights. ”

Industry

Mining

Timeline

Ongoing

Services

Data Services

Achievements
10+ Terabyte
Data Growth Support
3–5x
Faster procurement data access
85% Reduction in document search time
100% Centralized lakehouse repository
90% Improvement in document traceability and lineage
  • Slider
  • Slider
  • Slider
Project Challenges
changes
Lack of a centralized Lakehouse
architecture
changes
Unstructured, decentralized, and siloed datasets
changes
Inefficient document discovery without AI/ML-driven search
changes
Manual workflows slowing procurement operations
changes
Inconsistent governance across
geographies
changes
Limited real-time analytics and data engineering pipelines
How We Helped

Databricks-Powered Lakehouse with AI-Driven Knowledge Discovery

Our Approach

A two-phase enterprise data modernization strategy was implemented using Databricks Lakehouse Platform on Azure, combining data engineering, machine learning, and AI-powered search.

Phase 1
Enterprise Document Lakehouse Implementation

A scalable Delta Lake-powered data lakehouse was deployed to unify structured and unstructured data.

Phase 2
AI-Powered Knowledge Discovery with Databricks AI Stack

An intelligent AI layer was built leveraging Databricks Machine Learning and NLP capabilities.

Technologies Used

AzureAI GCPDataflow rest-api rest-api rest-api
70%
Reduction in compliance risks
100%
Faster reporting
Slider
Tangible Results, Real Business Value

Transforming fragmented enterprise data into a unified, intelligent, and scalable Lakehouse platform

Adoption of Lakehouse architecture combining data lake + data warehouse
Improved data engineering, data science, and BI collaboration
Enabled real-time data analytics and AI-driven insights
Strengthened data governance with Unity Catalog
Accelerated AI/ML innovation and enterprise-wide data democratization
60%
Productivity gains
30–40%
Better AI model accuracy
Success Stories

Discover how leading companies achieved remarkable results with our AI solutions

AI Case Studies

When Agile POD Teams Transform Digital Banking

Challenges

Our mobile apps and online channels lag behind customer expectations. Releases are slow, the user experience is outdated...

Solutions

Instead of applying a one-size-fits-all consulting model, we introduced an Agile POD delivery approach...

Learn More
AI Case Studies

When Automation Transforms Cargo Claims

Challenges

We process thousands of cargo claims every month. Manual handling slows us down, costs are rising, and errors are...

Solutions

The process was complex — involving multiple teams, paper trails, and manual validation steps. The client needed a...

Learn More
AI Case Studies

When Compliance Becomes Effortless with Automation

Challenges

Regulations keep changing. Manual compliance checks take too long, errors creep in, and clearance delays are...

Solutions

Instead of incremental fixes, we built an intelligent compliance automation framework powered by UiPath RPA...

Learn More