Use Case Intelligence RSS Search use cases Search
Databricks Manufacturing Latin America

Nexa Resources

Data Lake / Data Warehouse Modernization · Risk Management · Supply Chain Optimization

Nexa Resources, a global zinc mining leader, faced challenges with legacy data systems, siloed operations and limited scalability, hindering innovation and decision-making.

Read the original story Explore all use cases
$370,000 Annual savings from predictive models for zinc filtration and cadmium removal
90% Reduction in development time
9x Improvement in processing efficiency for IT supplier contract analysis
The addition of an ingestion framework improved productivity, standardization and data quality, reducing development cycles by 300% and providing the agility required for faster innovation.

Reported impact

Business outcome

Nexa Resources achieved measurable business impact on Databricks, including 90% Reduction in development time; 9x Improvement in processing efficiency for IT supplier contract analysis; $370,000 Annual savings from predictive models for zinc filtration and cadmium removal.

  • Cost Reduction
  • Productivity Improvement
  • Risk Reduction

Solution

Nexa Resources, a global zinc mining leader, faced challenges with legacy data systems, siloed operations and limited scalability, hindering innovation and decision-making. Databricks transformed Nexa’s infrastructure, enabling real-time insights, predictive models and AI-driven automation. This improved zinc filtration, reduced waste in material extraction and empowered teams to optimize equipment usage and workflows. Databricks has paved the way for smarter, AI-powered mining operations and sustainable growth. Nexa Resources is a global leader in the mining industry, specializing in the extraction and processing of non-ferrous metals, such as zinc and copper.

Data flow

IoT telemetry and operational data lands in Databricks and is transformed into curated datasets stored in Delta Lake under Unity Catalog governance before being served through Databricks SQL

Solution architecture

4 components · 4 layers
  1. Compute
    • Agent Bricks Supports agentic or GenAI applications that Nexa Resources uses to automate or accelerate work.
  2. Storage
    • Delta Lake Stores Nexa Resources's curated datasets for analytics, machine learning, and operational use cases.
  3. Serving
    • Databricks SQL Serves dashboards, interactive analysis, and governed SQL workloads for business users at Nexa Resources.
  4. Governance
    • Unity Catalog Provides access control, governance, and lineage across Nexa Resources's shared data products and AI workloads.

Architecture clues

  • Key product: Agent Bricks
  • Key product: Databricks SQL
  • Key product: Delta Lake
  • Key product: Unity Catalog
  • Medallion architecture
  • Real-time or streaming data processing

Evidence from the source

$370,000 Annual savings from predictive models for zinc filtration and cadmium removal
90% Reduction in development time
9x Improvement in processing efficiency for IT supplier contract analysis
Nexa Resources, a global zinc mining leader, faced challenges with legacy data systems, siloed operations and limited scalability, hindering innovation and decision-making.
The addition of an ingestion framework improved productivity, standardization and data quality, reducing development cycles by 300% and providing the agility required for faster innovation.
Transparency Evidence & methodology 95/100 reference value · 97% confidence · 2 sources

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value95/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    4 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence97%
  • Source authority25/25
    The deployment is described by the adopting organization or a government source.
  • Claim traceability23/25
    11 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency9/10
    2 source references document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Databricks

    Nexa Resources customer story

    First-party
    https://www.databricks.com/customers/nexa
    Source type
    Vendor-published customer story
    Published
    Mar 31, 2025
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date
  2. U.S. Securities and Exchange Commission

    Nexa Resources S.A. Form 20-F for the year ended December 31, 2025

    Government
    https://www.sec.gov/Archives/edgar/data/1713930/000129281426001787/nexaform20f_2025.htm

    The filing's detailed 'Number of Employees' table lists Brazil 3,532, Peru 2,065, and United States and Luxembourg 15, for a total of 5,612 employees as of December 31, 2025; 1,000+ employees maps to Enterprise.

    Source type
    Government regulatory filing
    Supports
    • Company size

Date evidence

  • Published on source page Mar 31, 2025 · Databricks · First-party
    Open date source
Not separately sourced Industry, Region. Treat these normalized attributes as lower-confidence until a dedicated source is added.

Related

Similar use cases

See all like this
Databricks Jan 22, 2026 Dongwon Group Manufacturing South Korea However, their legacy data systems were siloed by business units, limiting their ability to support company-wide AI-based operations. 96% Raw material price forecasting accuracy Data Lake / Data Warehouse ModernizationRisk Management Delta Lake · Unity Catalog Databricks Nov 6, 2023 Michelin Manufacturing global Michelin's centralized on-premises platform lacked the openness and flexibility needed for decentralized teams to access data, tools and technologies at scale and build their own analytics use cases. predict stock levels in 15 days' time Data Lake / Data Warehouse ModernizationSupply Chain Optimization Databricks Data + AI Platform · Databricks SQL · Delta Lake Databricks Aug 18, 2026 Sabesp Energy Brazil To support this transformation, Sabesp modernized its legacy Oracle Exadata-based data warehouse and adopted Databricks as the foundation for its data and AI strategy. Today, Databricks powers a Data Mesh architecture spanning more than 23 business domains, supports large-scale… Data Lake / Data Warehouse ModernizationFraud Detection AI/BI · Databricks SQL · Genie