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The fusion of data in a central platform enables smooth analysis to optimize processes and increase business efficiency in the world of Industry 4.0 using methods from businessintelligence , process mining and data science. Are you interested in scalable data architectures for your shopfloor management ?
Companies use BusinessIntelligence (BI), Data Science , and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. Data Mesh on Azure Cloud with Databricks and Delta Lake for Applications of BusinessIntelligence, Data Science and Process Mining.
In addition to BusinessIntelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. The measured timestamps (and duration times in case of Task Mining) are enhanced with a time-dimension for BI applications.
The data collected in the system may in the form of unstructured, semi-structured, or structured data. This data is then processed, transformed, and consumed to make it easier for users to access it through SQL clients, spreadsheets and BusinessIntelligence tools. Big data and data warehousing.
Dataintelligence has thus evolved to answer these questions, and today supports a range of use cases. Examples of DataIntelligence 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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