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In today's business landscape, data insights are crucial for informed decision-making and staying competitive.  Businesses have benefited greatly from the ability to unify data from their cloud applications as well as on-premise systems.However, dealing with data scattered across multiple clouds, systems and applications introduces complexities. 

Traditional approaches to Data Management rely on physically replicating data from various systems into a central repository, such as a data warehouse or a data lake. These approaches, both in definition and practice, do not inherently support distributed data.  Moving and merging data to a central location can be expensive and time-consuming, and then still needs further preparation for each analytical and operational use case, slowing down the business's ability to innovate and respond to market changes. 

To address contemporary data management challenges, organisations must adopt strategies specifically crafted to accommodate distributed data, and accelerate delivering data the business needs, in the form and at the time it is needed.   In this CIONET roundtable, we will explore the approaches and difficulties associated with implementing Logical Data Management.