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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 business intelligence , process mining and data science. CloudData Platform for shopfloor management and data sources such like MES, ERP, PLM and machine data.
This data is then processed, transformed, and consumed to make it easier for users to access it through SQL clients, spreadsheets and Business Intelligence tools. Data warehousing also facilitates easier datamining, which is the identification of patterns within the data which can then be used to drive higher profits and sales.
The Data Race to the Cloud. This recent cloud migration applies to all who use data. We have seen the COVID-19 pandemic accelerate the timetable of clouddata migration , as companies evolve from the traditional data warehouse to a datacloud, which can host a cloud computing environment.
In addition to Business Intelligence (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 Snowflake DataCloud is a leading clouddata platform that provides various features and services for data storage, processing, and analysis. A new feature that Snowflake offers is called Snowpark, which provides an intuitive library for querying and processing data at scale in Snowflake.
Companies use Business Intelligence (BI), Data Science , and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. Process Mining offers process transparency, compliance insights, and process optimization.
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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