Unlock the power of your Data & AI with Databricks
- Trusted by over 20,000 customers worldwide
- Up to 60% cost reduction vs legacy infrastructure
- Average 482% ROI in three years
Databricks
Turn Your AI Vision Into Reality with Databricks
Databricks is the world leading platform for data & AI, enabling organisations to break down data silos and unlock analytics and AI-driven use cases. Powered by scalable, cost-effective compute, it provides organisations with the core functionality to acquire and cleanse disparate data sources and convert them into actionable insights.
This capability is underpinned by a suite of features designed to help organisations fully leverage their data and accelerate AI adoption. These include robust data governance, support for agentic AI applications, and seamless integrations with a wide range of third-party tools.
Our Databricks Solutions
As a Databricks partner, we have the expertise to support your data journey.
Platform Design & Build
If you’re just starting on your Databricks journey, we have the expertise to ensure that your platform is designed and built with the future in mind. Using our in-depth knowledge of cloud providers and the Databricks ecosystem, we’ll ensure you take the best first step possible on your data journey.
Lakehouse Transformation
Modern analytical needs are enabled through the lakehouse, pairing cost effective storage and scalable compute to provide organisational insights as they’re needed. We have the experience to guide your transformation from fragmented source systems and siloed data warehouses to a unified, conformed lakehouse that unlocks your highest-value use cases.
AI Applications
The organisational need for AI is only growing, and with our support you can start to unlock AI use cases where your data resides. We have the knowledge to utilise Databricks’ ecosystem of tools to build, release, and assess AI applications, helping you better leverage your data for key operational insights and automated decision making.
Recent Projects
ASDA
Nimble partnered with ASDA to enhance their existing Databricks implementation, focusing on maturing key processes and ways of working. Whilst a platform was in place, key data processes had become inefficient, no longer meeting the needs of key stakeholders and impacting future crucial data migrations. By integrating senior staff as technical leads within existing squads, Nimble introduced best practices that reduced deployment times, optimised data pipeline performance, lowered platform costs, and established the foundations for their ML capabilities. These operational improvements also unblocked time for key developers, allowing them to focus on migrating data from key systems rather than releasing code or waiting on pipelines.
Global Cybersecurity Vendor
After scaling through multiple acquisitions, a global cybersecurity vendor had a number of duplicate systems – each within organisational silos. To enable conformed data products for reporting and AI, we implemented a Databricks lakehouse migration.
A squad spanning engineering, delivery, and product was mobilised to architect and build the platform, enabling the development of a conformed data layer using a medallion architecture. Following two successful project phases, much of the organisation’s data was onboarded to the platform and developed into core reporting products based on user feedback.
UK Government Department
Following years of ad-hoc development, this UK Government department’s Regional Service Division were maintaining key reports through a legacy SQL platform with poor performance, slow and error-prone reporting, and increasing complexity. To modernise this, a joint team from Nimble and another consultancy were embedded within their analytics function to design and implement modern lakehouse architecture built around Databricks. Once the platform was built, data was acquired from the underlying SQL estate where it could be governed at all stages of the medallion architecture using Unity Catalogue. Automated data quality checks were put in place, whilst pyspark was introduced for more performant transformations to cleanse and conform the data into suitable data products. By undertaking this modernisation, this UK Government department can move away from a difficult-to-maintain system while establishing the data foundations required to support their AI ambitions.
