Читать книгу Using Predictive Analytics to Improve Healthcare Outcomes - Группа авторов - Страница 28

For this step, it is important to engage a professional who is trained in analytics so the data can be interpreted accurately. There are several options in today's analytic software, such as SPSS, SAS or R, to aid in the examination of data flaws that are not obvious by merely looking at the dataset or its associated graphic representations. Your organization may have software, such as Tableau, which generates graphs automatically and is dependable for graphic visualization. In this step, it is important to engage an analyst or data scientist who can take advantage of the tools and tests contained in analytic software.