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Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Datawarehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.
Leveraging third-party data : Incorporating external data sources, such as weather, social media trends, and market reports, enriches your analysis, providing a more comprehensive understanding of customer behavior and market dynamics. AI and augmentedanalytics assist users in navigating complex data sets, offering valuable insights.
Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Datawarehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.
Data intelligence has thus evolved to answer these questions, and today supports a range of use cases. Examples of Data Intelligence use cases include: Data governance. Cloud Transformation. CloudData Migration. Let’s take a closer look at the role of DI in the use case of data governance.
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