Technology and Partners

Oracle's cloud and database ecosystem gives enterprise teams a single, integrated environment for managing customer data, running AI-powered analytics, and scaling infrastructure on demand. We apply Oracle where organisations need proven reliability at enterprise scale, with the governance and performance to match.

Snowflake makes it straightforward to share and analyse data securely across cloud environments. With Cortex Intelligence built in, teams get AI-powered insights without managing separate ML infrastructure, so analysts spend less time wrangling data and more time acting on it.

Databricks brings data engineering, analytics, and machine learning onto one platform, so your teams stop duplicating work across siloed tools. We use Databricks where organisations need to build and scale ML pipelines quickly, with Agentbricks enabling intelligent automation across complex workflows.

Azure gives organisations a proven cloud foundation for data storage, processing, and analytics at scale. Combined with SQL Server and Synapse Analytics, it's a strong fit for enterprises already invested in the Microsoft ecosystem who want to modernise without starting from scratch.

AWS is the backbone for organisations that need flexibility across storage, compute, databases, and AI services. We apply AWS where scale, global reach, or specific managed services make it the right fit, and we build architectures designed to perform without runaway cost.

Google Cloud is a strong choice for organisations prioritising AI and machine learning at scale. Its managed infrastructure removes much of the operational overhead, so teams can focus on building models and generating insights rather than maintaining platforms.

BigQuery lets analysts run SQL queries across massive datasets in seconds, with no infrastructure to manage. It's ideal for organisations that need fast, cost-effective analytics on large volumes of data without the overhead of traditional data warehouses.

Google Analytics gives teams a clear picture of how users interact with their website and apps, from traffic sources to conversion paths. We integrate it into broader data platforms so behavioural insights sit alongside your operational and commercial data.

dbt (data build tool) brings software engineering discipline to data transformation, making pipelines modular, testable, and version-controlled. For data teams, that means fewer silent failures, faster debugging, and analytics code that can be trusted and maintained over time.

Apache Airflow keeps your data pipelines running reliably, scheduling, monitoring, and managing dependencies automatically. When something fails, it's visible and recoverable. We use Airflow to give data engineering teams confidence that their platforms are working, even when no one is watching.

Power Platform, including Power Apps, Power Automate, and Copilot Studio, gives business teams the ability to build workflows, automate repetitive tasks, and create custom apps without waiting on development backlogs. It's how organisations start realising value from automation quickly.

Copilot Studio and Azure AI Foundry make it practical to build AI agents that work inside the tools your teams already use, from Microsoft 365 to internal business systems. The result is AI that augments how people work, rather than adding another tool to manage.

Power BI turns complex data into clear, interactive dashboards that business users can explore without analyst support. We build Power BI environments on reliable data foundations — so the numbers your teams make decisions from are ones they can trust.

Looker's governed data model means everyone in the organisation is working from the same definitions and the same source of truth. We use Looker where consistency and data governance matter as much as the visualisations themselves.

Tableau is a powerful choice for teams that need flexible, visually rich analytics across a wide range of data sources. It's particularly effective where non-technical users need to explore data independently, without relying on a central analytics team for every question.

Candela Data uses Figma to design and prototype data products, dashboards, and client-facing tools before a line of code is written. It keeps stakeholders aligned early, reducing rework and ensuring the end product reflects what users actually need.

Many organisations run critical operations on legacy platforms. Candela Data helps you get more from existing infrastructure by integrating it with modern data ecosystems, migrating data safely to cloud-native environments, and bridging the gap between old systems and new capabilities without disrupting what already works.