Get more value out of your data starting with a good architecture. A real project using a Cloud Data Lakehouse Platform

In this session we'll discuss the challenges faced while solving the problems of one of our customer’s old analytics architectures: multiple data silos, poor performance and lack of governance. Creating a Data Lakehouse and selecting the proper tools for the project have been key to success.

While Data Lakehouse is a new name for the combination of well-known data architectures, Data Lake and Data Warehouse, the real power lies in the existence of new data platforms that make it easier for both end-users and applications to access data, regardless of whether it is in a Data Warehouse or in the Data Lake, whether it is stored in a database table or as files in an object storage.

A Data Warehouse is still the best architecture for storing corporate data once the different systems are integrated, the quality rules are applied, and the most complex calculations are summarized.

A Data Lake is still the best architecture for incorporating new data quickly, flexibly and at a controlled cost, without the rigidity of a Data Warehouse schema but with minimum quality controls.

Cloud environments allow companies to focus on processing their data and forget about infrastructure, allowing unlimited scalability and always adjusting costs to what is really being used.

We’ll show you how we used Oracle Autonomous Database service, a database whose maintenance, security and updating is managed by Oracle. It is scalable on-line and totally flexible from the smallest environments to large installations.