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The Future of Data Architecture
Has the Data Warehouse Had its Day?
This BARC Study research focus on Data Lakehouses, Data Fabric, Data Mesh. Which remedies help overcoming data silos and making data architecture future-proof?
Data warehouse, data lake, data lakehouse:
Which data architecture is best for the data-driven enterprise is a subject of ongoing debate.
In principle, the approaches follow a similar basic idea: they physically move data to one location to store and prepare it there. In the face of growing data volumes, this large-scale data movement is not a viable concept.
Data-driven companies need a modern, future-proof data architecture that meets flexibility requirements. While it must take into account the actual complexity of the existing data landscape, it must do so without further complicating it.
Which approaches are currently seen as promising?
Do I need a data fabric or data mesh? An integrated data hub or data as a network?
Are classic data architecture concepts such as data warehouse, data lake, data lakehouse viable for the future? What will work for today’s needs? What will we need in the future?
Are broader data architecture concepts being pursued for the future, what are they and what benefits are expected?
Does data fabric play a role in future planning? What is new about data fabric compared to existing concepts, architectural approaches and technologies?
Can a data fabric be successful without a data mesh?
When redesigning the data architecture, the majority still relies on tried-and-tested concepts.
respondents rely on the data warehouse architecture approach for their future data &analytics landscape.
In contrast, the data lakehouse is the most preferred data architecture approach by best-in-class companies (40%).
of executives and 40% of managers/developers in IT are convinced that centralized data architecture cannot prevent data silos.