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DataPhoenix is an AWS data lake consultancy. We turn a flood of data from many sources into a single, navigable data lake that delivers business value.
Once, a single operational database or CRM system could serve as the source of truth for all your business information. Today, that single source is blind to many essential facts.
Real-time data from websites, social accounts, IoT devices, internal facility management and production systems are just some of the truths that can be added to your traditional business systems to create a broader, more nuanced and detailed picture of what is happening in your organisation.
How can you bring these diverse sources together and get value from the data?
A data lake holds structured and unstructured data, so you can pool data from all these sources, catalogue and optimise it, and query it for new insights.
A data lake does not replace your existing data warehouse. It is a new way of capturing data that lets you explore freely and find insights that can transform your business:
On Amazon Web Services (AWS), a data lake is not a specific product or set of products. AWS offers an architecture pattern and guidance that define what a data lake should be and do, and you build the functionality from existing AWS services.
As a result, there are many ways to approach a data lake project on AWS. This gives teams the freedom to configure a solution that closely matches their needs, but it can be a real challenge for those who have not built a data lake on AWS before. With so many options, building one can seem deceptively simple, yet a data lake that is functional, secure and easy to use is not straightforward to build. Expert help is vital.
Having delivered data lake projects for blue chip clients, DataPhoenix has developed a proven framework and methodology for architecting and delivering data lakes on AWS. The approach combines that methodology with tools that provide essential functionality and orchestration, and it can be extended with other services such as data or application cloud migration. The result is a solution tailored to your needs.
DataPhoenix begins with a detailed needs analysis and delivers an elastic deployment that can scale with your future needs. Getting it right the first time saves money, and building flexibility into the solution protects your investment. DataPhoenix delivers data lake projects using Scrum and DevOps, which maximises knowledge transfer and strengthens your own team of DevOps and data engineers. The aim is a single team, with everyone needed on board, driven to deliver business value and get an effective solution into use quickly.
Tools such as Atlantis and Terraform let DataPhoenix build a solution that is easy for your own team to manage. Security, continuous integration and continuous deployment are built into the data lake from the start, with automated self-service provisioning, simulation and approval steps that protect the integrity of your deployment long after handover. The framework behind it has been tried and tested in large-scale production environments.
DataPhoenix chooses technology for fit and cost-effectiveness. The result is a simpler, faster data lake that is sustainable and easy to manage, and that delivers business value through reduced risk, better collaboration and new insight.
Want to learn more? The definitive guide to data lakes on AWS explains the architecture we build, AWS data lake layers explained describes the zones, and lake house architecture on AWS covers the warehouse layer on top. For a worked example, see our secure data platform case study. For search and analytics on top of the lake, read OpenSearch and Elasticsearch for AWS data lakes.
DataPhoenix specialises in data lakes on AWS, from architecture to handover, with security and governance built in from the start.
The work is tied to a business case, so you know what the data lake should return before you commit budget, and your team is ready to run it when the work ends.
Ready to put AI to work on your data? Get in touch with the DataPhoenix team.