Discover our latest case study: Grounded Innovation at Bridgestone Aircraft Tire
In the previous piece, we uncovered the different characteristics of a well-designed data product. In this second blog, we will illustrate a real case scenario that tells the story of a data analyst, “Fred”, trying to navigate the complexities of his data landscape using our data product platform.
The data mesh architecture is built around four fundamental concepts, the second of which is “data-as-a-product” often just called data products.
IT-powered innovations, the Internet of Things and new generation customer demands are fueling real-time data creation. In this new data landscape, businesses from all industries are quickly shifting from batch processing to real-time data streams to match the new imperatives. In this blog, our marketing analyst, Selima Triki, unpacks the concept of real time and real-time data, some of its benefits and applications.
In this blog, we uncover the multiple facets of data engineering, what it is and how complex it can be. Digazu’s product manager, Luc Berrewaerts walks us through the new technologies to navigate the complexities of data engineering.
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
Pushing the limits of your data doesn’t have to be a difficult task. Still, if left alone, data has little to no value. Read this article and bring your data to life by taking proactive actions towards understanding how to overcome the challenges that data collection can pose. Sometimes simple solutions can solve complex problems.
Discover how you can take your data engineering to a whole new dimension with Digazu. Specifically designed to simplify the work of your data engineers, Digazu was built to work at scale and to integrate with your IT landscape for sustainable and scalable data engineering.
Implementing your business cases comes with a price tag of high expectations and inevitable costs. Read this article and discover how you can drastically control the cost of implementation of your use cases and reduce your projects’ time to market.
Discover the building blocks of a modern and scalable data platform. Get insights on how to power your data projects and unlock the value of your data assets.
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.
