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Deciphering The Seldom Discussed Differences Between Data Mining and Data Science

Smart Data Collective

We decided to cover some of the most important differences between Data Mining vs Data Science in order to finally understand which is which. What is Data Science? Data Science is an activity that focuses on data analysis and finding the best solutions based on it. Definition: Data Mining vs Data Science.

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How AI is fundamentally disrupting stock market analysis for everyday traders

Dataconomy

Want to know more about the revolution in stock market forecasting by Artificial Intelligence (AI)? And well see how it plays out in the technology, in the data-mining and for investors. #1 Good data is the main factor in AI prediction. That will make your data do bad on new unvisible data.

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Data Mesh Architecture on Cloud for BI, Data Science and Process Mining

Data Science Blog

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. Each applications has its own data model.

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Object-centric Process Mining on Data Mesh Architectures

Data Science Blog

New big data architectures and, above all, data sharing concepts such as Data Mesh are ideal for creating a common database for many data products and applications. The Event Log Data Model for Process Mining Process Mining as an analytical system can very well be imagined as an iceberg.

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Python for Business: Optimize Pre-Processing Data for Decision-Making

Smart Data Collective

The rise of machine learning and the use of Artificial Intelligence gradually increases the requirement of data processing. That’s because the machine learning projects go through and process a lot of data, and that data should come in the specified format to make it easier for the AI to catch and process.

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Predictive Analytics: 4 Primary Aspects of Predictive Analytics

Smart Data Collective

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

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Essential types of data analysis methods and processes for business success

Data Science Dojo

Every individual analysis the data obtained via their experience to generate a final decision. Put more concretely, data analysis involves sifting through data, modeling it, and transforming it to yield information that guides strategic decision-making.