The real-time data
engineering platform
Simplicity through technology
Get straight to value with your data science and analytics projects
SIMPLICITY
A turn-key solution with a low-code approach that provides results very fast without compromising on any technical aspect.
BEST PRACTICES
IN A BOX
A packaged implementation of the best data architectures to cover all your present and future needs.
INDUSTRIALISATION
A platform designed to work at scale and to integrate into your enterprise landscape.
Simplicity
We have taken every unnecessary step away from the process to make data engineering as straightforward and accessible as possible.
Simplicity
Low-code
no-code
Automated
deployment
to production
Unified approach to data
Ready-to-use from day one
Best practices in a box
The technological heart of Digazu is based on modern data architecture and powerful technologies deployed by market leaders worldwide.
Best practices in a box
Streaming & real-time
Combined power of Kafka and Flink
Data-hub native, data-mesh ready
Integrated governance and privacy
Industrialisation
The platform handles the largest volumes at low latency and makes data engineering sustainable in the long term.
Industrialisation
Scalable infrastructure
Multi-cloud-ready
Sustainable through time
Enterprise-wide management
Articles
The 4 Most Common Mistakes of Digital Transformation Programs
Read our latest White Paper on the most common mistakes of digital transformation programs, the dos and don'ts of the data journey.
Come take a closer look at some of the most challenging pitfalls businesses regardless of their space face in their pursuit of digital and capture the best practices and lessons learned to to drive successful data projects.
Implement the right data storage architecture, build your business for the future
Learn the various ways in which you can store your data and choose the one that best suits your needs. This article will underline the difference between data warehouse, data lake and data mesh while exposing the benefits and drawbacks that you could encounter. Find the best solution no matter how mature your data is.
Data processing: simplified integration of your data
In this article we are focusing on a crucial step in adapting better data practices: data processing. Use your data to its fullest by properly managing how you store the data so that it is readily available any time you need to make a decision.