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Databricks Services Malta

Databricks consulting and development in Malta. Lakehouse implementation, Spark optimisation, Unity Catalog governance.

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/ the solution /

Databricks Services built around your business.

Every solution we deliver is built on three pillars: your data, your context, and continuous improvement. Each capability is traceable and measurable.

  • Databricks Lakehouse Implementation

    Design and deploy Databricks Lakehouse architectures with Delta Lake, Unity Catalog, and o…

  • Spark Performance Optimisation

    Tune Apache Spark jobs for maximum performance and minimum cost on Databricks. Our optimis…

  • Unity Catalog & Data Governance

    Implement Databricks Unity Catalog for centralised data governance across workspaces and c…

  • MLflow & Model Lifecycle Management

    Deploy MLflow for comprehensive ML lifecycle management including experiment tracking, mod…

/ how it works /

Live in weeks, not months.

We evaluate your current data stack, workload patterns, team skills, and cloud infrastructure to design the optimal Databricks architecture. For existing Databricks users, we assess current usage patterns and identify optimisation opportunities.

We design the Databricks workspace architecture including cluster policies, Unity Catalog hierarchy, Delta Lake schema, and integration patterns. Architecture decisions balance performance, cost, governance, and team productivity.

We deploy Databricks with infrastructure-as-code, configure networking, security, and cloud integrations. Unity Catalog, cluster policies, and workspace permissions are configured according to your governance requirements.

We migrate existing data workloads from legacy platforms to Databricks with validation and parallel running. SQL workloads, Spark jobs, and ML pipelines are converted and optimised for the Databricks environment.

We tune Spark jobs, cluster configurations, and Delta Lake tables for optimal performance and cost. Continuous monitoring identifies further optimisation opportunities as workload patterns evolve.

We train your data team on Databricks capabilities, best practices, and operational procedures. Hands-on workshops cover notebook development, SQL analytics, Delta Lake operations, and MLflow usage.

/ what you get /

Everything you need. Nothing you don't.

Databricks Lakehouse
Implementation
Spark Performance
Optimisation
Unity Catalog &
Data Governance
MLflow & Model
Lifecycle Management
/ built for your situation /

Sounds familiar?

Head of Data, retail group
"Our sales data lives in three different systems — Shopify, our ERP, and a warehouse management tool — and we can't get a single view of inventory performance"

We build a unified data pipeline that ingests from all three sources, applies consistent business logic, and loads into a data warehouse your BI team can query in real time.

How Neural AI helps

We build a unified data pipeline that ingests from all three sources, applies consistent business logic, and loads into a data warehouse your BI team can query in real time.

/ proof /

Real deployments. Real results.

Business Intelligence

Compre Group Dashboard

Power BI dashboard providing comprehensive visibility into payables, costs, and financial operations for Compre Group's insurance business.

Databricks lakehouse unifying 12+ data sources for analytics

Read case study →
Data Engineering & AI

GPT Cloud Migration

Complete migration of Malta Tourism Authority legacy licensing data to cloud using GPT-powered NLP for error detection, achieving over 90% reduction in migration errors.

40% cost reduction through Databricks architecture optimisation

Read case study → Data Engineering & ML

Tipico AML

We migrated Tipico's AML data science workflows from KNIME to Python-based big data analytics with AWS Airflow automation, achieving up to 70% faster ETL pipeline execution and improved risk-ranking accuracy.

Spark-powered real-time transaction processing for compliance

Read case study →
/ questions /

Databricks Services FAQ

What is a Databricks Lakehouse?
A Databricks Lakehouse combines the best of data lakes and data warehouses on a single platform. Delta Lake provides ACID transactions, schema enforcement, and fast SQL queries on data stored in cost-effective cloud object storage. This eliminates the need to maintain separate lake and warehouse systems while supporting all analytical workloads from BI to ML.
How does Databricks compare to Snowflake?
Databricks excels at data engineering, streaming, and ML workloads with Spark as its processing engine. Snowflake excels at analytical SQL queries and data sharing with its optimised query engine. Many organisations use both, with Databricks for data processing and ML, and Snowflake for analytical querying. We help you choose the right architecture.
Can you optimise our existing Databricks costs?
Yes, Databricks cost optimisation is one of our most requested services. We typically find 30-50% savings through cluster right-sizing, autoscaling policy tuning, job scheduling optimisation, Delta Lake compaction and Z-ordering, and instance type selection. We also implement cost allocation tagging for chargeback visibility.
What is Unity Catalog and do we need it?
Unity Catalog provides centralised governance for all data and AI assets across Databricks workspaces. It manages access controls, audit logs, data lineage, and sharing policies. For Malta organisations with regulatory requirements or multiple data teams, Unity Catalog is essential for maintaining governance without limiting productivity.
Can Databricks replace our existing BI tools?
Databricks SQL provides SQL analytics and dashboarding capabilities, but for most organisations it complements rather than replaces dedicated BI tools. Power BI, Tableau, and Looker Studio connect directly to Databricks SQL warehouses, combining Databricks data processing power with specialised BI visualisation capabilities.
How do you handle Databricks in regulated industries?
We configure Unity Catalog governance, encryption, network isolation, and audit logging to satisfy GDPR, MGA, MFSA, and other regulatory requirements. Access controls, data classification, and lineage tracking provide the compliance infrastructure that Malta regulated industries require.
Should we deploy Databricks on AWS or Azure?
Both platforms offer mature Databricks integrations. Azure Databricks integrates with the Microsoft ecosystem including Azure Active Directory, Synapse, and Power BI. AWS Databricks integrates with S3, Glue, and the broader AWS service catalogue. Choose based on your existing cloud investments and team familiarity.
Can you migrate our Spark workloads to Databricks?
Yes, we migrate Spark workloads from EMR, HDInsight, self-managed clusters, and other platforms to Databricks. Migration includes code conversion, cluster configuration, scheduling setup, and validation. Most migrations achieve performance improvements alongside simplified operations and reduced management overhead.
/ get started /

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