Automate data engineering to make data usable and accessible for everyone
Deploy your end-to-end data engineering platform to integrate, automate, orchestrate your data and to create more added-value with your business partners.
Standardise your data science practices. Automate the packaging and deployment of your data science models to secure the POC to PROD migration.
Combine your end-to-end data engineering platform with an MLOps platform to create a holistic data management system that includes data and models.
Save time and costs on your journey towards data centricity.
Companies have to become data-centric to remain competitive and please their customers. Building a data platform takes time and is not without risk. Many companies failed in this area, despite the effort of costly data architects and data engineers.
With Digazu, you have your end-to-end platform from day one with a lower total cost of ownership. This gives you more time and money to work on creating value.
Increase productivity and create business value faster.
Data projects are complex. To implement and maintain robust data pipelines, engineers and scientists have to master an increasing number of technologies. As a consequence, data projects take time, and business teams are often frustrated by the slowness of IT processes.
Digazu automates and standardise most of the data engineering work. It drastically reduces the time it takes to get value out of your data, it reduces the time to market of your new cases.
Minimise the time spent on cutting edge technologies integration.
The tremendous growth in the big data sector has led to a multitude of technologies. It is difficult for data engineers to create an environment where so many technologies are properly integrated.
With Digazu’s platforms, this challenge is lifted and the integration of your data with data tools has never been that easy.
Let data engineers focus on the customisation and not on standard tasks.
To do their work, data engineers need to focus on customisation tasks and mastering a combination of programming languages, database skills, and data processing tools.
Digazu’s platforms automates and standardises data engineering tasks. It lifts off the pressure from your data engineer’s shoulders. It enables them to focus on the customisation of their tasks to increase their productivity and effectiveness.
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To help you drive a successful data lake project you have to discover what are the challenges in a data lake project, and how you can minimise the failure risk.