In recent years, the demand for unified data and AI platforms has grown exponentially. We’re in the middle of a technology revolution and data is at the heart of it. With the volume of data increasing, businesses are struggling to keep up with it. Fragmented data systems result in siloed, inconsistent data with the introduction of generative AI only amplifying the issue.
Businesses need a solution that unifies data, empowers data engineers to make better decisions while embedding AI across every function - that solution is Databricks.
What is Databricks?
According to Databricks, it’s a “unified, open analytics platform for building, deploying, sharing, and maintaining enterprise-grade data, analytics, and AI solutions at scale.” In simple terms, it’s one central location for all of your data and analysis. Its primary function is to aid in the deciphering of complex data processing to enable data scientists and engineers to build AI applications and analyse at scale.
The creators, who also developed Apache Spark, have prioritised cross-platform integration across the three major cloud service providers - Google Cloud Platform, Microsoft Azure and Amazon Web Services. It can also link to a large number of data sources, including on-site SQL servers, CSV and JSON.
Using a lakehouse architecture, Databricks combines the best of data lakes and data warehouses. This model provides users with scalability, cost-efficiency and flexibility, enabling organisations to unlock the full potential of their data.
It comprises four core components that come together to provide the tools, workflows and infrastructure to manage data. The components are:
- Data engineering
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Analytics
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Machine learning
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Governance
These components allow data to be stored but also prepped, interrogated and cleansed to allow for training models and monitoring performance.
Why businesses are investing in Databricks in 2026
Businesses are sitting on mountains of data; the challenge they face is bringing it all together and rationalising it in a way that’s productive for them. The rate of data exchange means there is often duplication or errors. Databricks allows multiple data streams to be brought together in one place, offering real-time analysis, providing a pivotal piece of software for any business undertaking a digital transformation.
Alongside the real-time data processing, Databricks empowers data engineers to utilise AI and machine learning with inbuilt workflows and testing platforms, future-proofing systems while embedding AI at the heart of operations.
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With Databricks |
Without Databricks |
|
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Platform Integration |
Unified platform for data engineering, ML, and analytics |
Multiple separate tools requiring integration |
|
Data Governance |
Unity Catalog for centralised governance and lineage |
Multiple governance tools, often disconnected |
|
Collaboration |
Built-in collaborative notebooks with real-time sharing |
Separate tools, fragmented version control |
|
Performance |
Delta Engine optimisations, 3-10x faster queries |
Standard performance, manual optimisation needed |
|
Setup & Maintenance |
Managed service, quick deployment |
Extensive setup time, manual maintenance required |
|
Cost Management |
Built-in monitoring, auto-termination, better resource utilisation |
Manual cost tracking across multiple services |
Databricks benefits firms of all sizes and industries. International firm KPMG modernised their audit, tax and advisory services using Databricks as a core pillar of their LLP cloud data strategy. Its existing system struggled with the speed-to-market requirements and the associated costs had spiralled due to the volume of data KPMG processed. KPMG recognised that to remain a leading global accounting firm they needed to look to new technology. Switching to Databricks allowed them to unify its data and AI across the firm, increasing productivity, creating a faster time to market and optimised scale and performance.
While Retailer Columbia was using legacy analytics systems, which were costly and slow, negatively impacting their reporting and forecasting abilities. They brought in Databricks to build high-performance pipelines, reducing processing time and empowering them to make smarter decisions. Databricks achieved a 70% reduction in ETL pipeline creation time while reducing the time to process ETL workloads from 4 hours to only 5 minutes.
“One of the benefits of this platform is how fast people can come up to speed on it. All that data is coming in, and more business units are using it across the enterprise in a self-service manner that was not possible before,” stated Lara Minor, a senior enterprise data manager at Columbia Sportswear. “I can’t say enough about the positive impact that Databricks has had on Columbia.”
How recruitment businesses can support Databricks adoption
To maximise the impact of Databricks on your business, it’s essential to hire data engineers who fully understand and can deploy the software. When you consider that the success of your data transformation projects rests on the quality of skills and knowledge you have access to and combine that with the specialised nature of Databricks, building the right team becomes a challenge.
That means when you’re looking for data engineers, machine learning engineers, and platform architects with Databricks expertise, it’s not as simple as posting on a job board. Recruitment partners have wide networks and can use those to find expert candidates. Working with a recruitment partner can help businesses upskill for AI adoption, recruit for data transformation, and ultimately make the right hiring decisions.
Future-proofing your team
One of the key benefits of Databricks is its scalability. It’s looking at the capabilities of Databricks and ensuring you have the right infrastructure to develop it in the future, but that relies on having the right team. Investing in software and technology is only half of the solution. Investing in people is crucial when it comes to future-proofing your business, and a recruitment partner can make sure that your investment is spent wisely.
It’s not only about the skills you have right now, it’s about ensuring that in 5 years' time, you still have the skills you need. Recruitment partners can advise on training pathways, recruitment strategies and workforce planning to build in-house capabilities. This can upskill existing employees but can also improve retention rates by establishing career paths.
Unified data and AI is the key to unlocking the power of your data, but you can only do that with a highly-skilled data team with Databricks expertise. Working with a recruitment partner helps you to find the right talent, to upskill your existing team with clear training pathways and to maximise your tech investment - setting you on track for success.
