Databricks Implementation & Data Engineering Services

We build robust data foundations with Databricks that enable real-time analytics, machine learning, and AI initiatives, ensuring your data is clean, governed, and ready to drive business decisions.
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Build the data foundation your AI initiatives need

AI success depends on reliable data infrastructure. Data engineering is the center of next-generation data architectures, the connective tissue between enterprise data and decision-making. As a proven Databricks solutions partner, we enable organizations to run complex analysis and machine learning on real-time data. From acquisition and storage to processing and analysis, we ensure data is clean, relevant, and ready for machine learning models while maintaining governance practices that keep everything secure, compliant, and aligned with business objectives.

What we deliver

Data lakehouse architecture

Build modern data lakehouse architectures that combine the best of data lakes and data warehouses for effective data management, governance, and analysis at scale.

Multi-cloud integration

Integrate Databricks across AWS, Azure, and Google Cloud environments with seamless data flow, maximum security, and optimized cloud-native performance.

Real-time data processing

Enable complex analysis and machine learning with real-time data through properly configured Databricks instances connected to all your data sources.

Advanced analytics & machine learning

Solve complex business and technical challenges with advanced analytics and ML services built on Databricks by certified engineers.

Industry-specific solutions

Implement Databricks solutions tailored to finance, healthcare, retail, manufacturing, and other industries through predictive analytics and real-time processing.

Data governance & quality

Optimize AWS usage according to Well-Architected Framework principles to improve security, resiliency, and reliability while reducing costs.

Why partner with Forte Group

Databricks-certified engineers

Team of certified engineers with deep platform expertise to optimize data architectures, accelerate innovation, and streamline operations.

Strategic outcomes focus

Go beyond implementation to focus on strategic outcomes that drive measurable business value, not just technical deliverables.

Custom software integration

Integrate Databricks' unified analytics platform with custom software expertise to deliver scalable, sophisticated solutions.

Knowledge transfer

Collaborative approach that works closely with your team, transferring knowledge and skills for long-term success in the evolving data landscape.

Multi-cloud expertise

Leverage cloud technologies across AWS, Azure, and Google Cloud to ensure scalability, flexibility, and optimal performance.

Cost optimization

Reduce costs while enhancing security and performance through optimized data architectures and streamlined operations.

Featured case studies

50% savings in infrastructure costs for Interfirst Mortgage Company

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Relativity accelerates release frequency with 83% faster regression testingaccelerated the launch of a new credit platform

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Enhanced operations through process automation and modernization for Redwood Logistics

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Let's build the data foundation your business needs

What our experts say

Only 1% of companies call their generative AI rollouts mature and more than 80% say they aren't seeing earnings impact at enterprise level according to McKinsey.

Gartner projects 40% of agentic AI projects will be canceled by 2027. Experienced AI implementation partners help manufacturing navigate safety rules and regulatory demands - delivering production-ready systems that survive on plant floors where consumer AI shortcuts fail.
Sergey Ilin
VP of AI

What our experts say

Most manufacturers operate with fragmented data ecosystems including legacy MES and SCADA systems, siloed PLC data, and inconsistent sensor quality. The average organization utilizes only 23% of available data for AI applications.

Strategic data engineering partners with formal governance programs deliver 3.2 times higher success rates, building unified data platforms that precede meaningful AI deployment and Industry 4.0 transformation.
Lucas Hendrich
CTO

What our experts say

The US manufacturing sector could need 3.8 million new employees by 2033 yet without significant changes more than half these positions - 1.9 million jobs - could go unfilled.

92% of hiring managers expect challenges with 45% citing difficulty finding qualified candidates. Expert development partners accelerate digital transformation initiatives while internal teams focus on production operations rather than custom software development for emerging technologies.
Egor Goryachkin
CDO

What our experts say

By 2030, all manufacturing industries will accumulate 92 exabytes of data from multiple internal and external sources, underscoring the importance of unified data platforms.

AI adoption remains cautious yet accelerating as it sits atop CIO and Chief AI Officer agendas. Specialized analytics partners treat AI as a core element of digital transformation; integrating cloud platforms, big data analytics, and emerging technologies while overwhelmed internal teams lack bandwidth for comprehensive modernization.
Alex Lukashevich
Chief AI Officer