Discover the challenges and consequences of the companies that are underestimating the complexity of a modern data platform.
Digazu’s Low-code platforms will help you address all your data and data processes challenges in a sustainable and future-proof way. Easy-to-use and highly intuitive, Digazu combines the power of automated data engineering, a data lake and a smart data-science platform.
A feature-rich data science platform can help you navigate through data silos and bring holistic data management into your organization and leverage the highest possible value out of it.
Surviving as a mainstream business today means being data-driven. Yet, becoming a data-driven organization does not happen overnight, it takes a lot more than a few resolutions and a well-articulated data strategy.
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.
Companies need solutions that help real-time data management platforms designed in such a way that extracting data sets is quick, easy and reduces the work of IT teams.
Download the white paper to discover how to successfully introduce organizational GDPR changes and its requirements to install an effective data governance tool to help you embed privacy into your everyday work.
Companies need solutions that aggregate many sources of on- and off-line information, extract data sets quickly, and ease the deployment of models to compute real-time compelling recommendations.
Discover how Digazu’s platforms help the banking sector dealing with real-time banking transactions and streamlining data between data producers and data consumers.
Generate, trough data, additional revenues by automating recommendations with intermediaries, making targeted interactions with customers possible.
Match your business with the everlasting changes in customers’ preferences and expectations.
Discover how to add value to your retail business and to personalize each customer engagement trough by integrating a multichannel data approach across your real-time reporting and your data science models.
Today’s business are trying to become more data centric or to develop their data culture. To do so they have to start leveraging insights from their data. Therefore, ETLs (extract, transform, and load) are essential in data integration strategies.