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The 13 Best Data Analytics Certifications Online for 2022

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The editors at Solutions Review have compiled this list of the best data analytics certifications online to consider acquiring. Data analytics is a data science. The purpose of data analytics is to generate insights from data by connecting patterns and trends with organizational goals. Comparing data assets against organizational hypotheses is a common use case of data analytics, and the practice tends to be focused on business and strategy. With this in mind, we've compiled this list of the best data analytics certifications from leading online professional education platforms and notable universities.


BI without AI is like corn flakes without the milk

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One that would quickly highlight any recent changes or key findings." SAS report summary helps to describe the report in a few sentences to replicate a speech-template. The functionality provides a dynamic description of the report: Conditional text, Dynamic values and Natural Language Generation ... a key requirement if you are going to claim this as AI-enhanced business intelligence. Further examples and details of how to utilize this feature can be found within this article written by Xavier Bizoux. Report summaries are also particularly useful if your audience includes individuals with visual impairments. The report summary can easily be read by screen readers. But wait, there's more ...


Play with classification of Iris data using gradient boosting

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Gradient boosting is one of the most widely used machine learning models in practice, with more and more people like to use it in Kaggle competitions. Are you interested in seeing how to use gradient boosting model for classification in SAS Visual Data Mining and Machine Learning? Here I play with the classification of Fisher's Iris flower dataset using gradient boosting, and this may serve as a start point to those interested in trying the classification models in SAS Visual Data Mining and Machine Learning product. Fisher's Iris data is a well-known dataset in data mining. Per Wikipedia, Fisher developed a linear discriminant model to distinguish the species from each other by the features provided in the dataset.