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More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.
Selling the value of datatransformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.
Built on 100% open source technology, CDF helps you deliver a better customer experience, boost your operational efficiency and stay ahead of the competition across all your strategic digital initiatives. CDF, as an end-to-end streaming data platform, emerges as a clear solution for managing data from the edge all the way to the enterprise.
This capability will provide data users with visibility into origin, transformations, and destination of data as it is used to build products. The result is more useful data for decision-making, less hassle and better compliance. Dataintegration. Start a trial. Start a trial. AI governance.
Part one of our blog series explored how people are the driving force behind the digitaltransformation and how it is fueled by artificial intelligence and machine learning. Now, we will take a deeper look into AI, Machine learning and other trending technologies and the evolution of dataanalytics from descriptive to prescriptive.
The message we’ve heard from attendees, loud and clear, is that the COVID-19 pandemic has enabled organizations to rapidly accelerate digitaltransformation and that there’s a strong mandate to maintain momentum. The push to predictive and prescriptiveanalytics requires strategy and C-Suite ownership.
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