CIO Business Intelligence
JUNE 7, 2022
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. Diagnostic analytics uses data (often generated via descriptive analytics) to discover the factors or reasons for past performance.
Smart Data Collective
OCTOBER 13, 2021
Over time, it is true that artificial intelligence and deep learning models will be help process these massive amounts of data (in fact, this is already being done in some fields). Prescriptive analytics. However, there will always be a decisive human factor, at least for a few decades yet. In forecasting future events.
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BizAcuity
MARCH 31, 2022
Predictive Analytics: Predictive analytics is the most talked about topic of the decade in the field of data science. The aim of predictive analytics is, as the name suggests, to predict and forecast outcomes. Prescriptive Analytics: Prescriptive analytics is the most complex form of analytics.
Jedox
JULY 31, 2018
Now, we will take a deeper look into AI, Machine learning and other trending technologies and the evolution of data analytics from descriptive to prescriptive. Analytic Evolution in Enterprise Performance Management. Advanced analytics responds to next-generation requirements. Simply put, it is extremely(!)
IBM Big Data Hub
JULY 6, 2023
One ride-hailing transportation company uses big data analytics to predict supply and demand, so they can have drivers at the most popular locations in real time. An e-commerce conglomeration uses predictive analytics in its recommendation engine. Python is the most common programming language used in machine learning.
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