Название: Practical Data Science with SAP: Machine Learning Techniques for Enterprise Data, First Edition Автор: Greg Foss, Paul Modderman
Издательство: O'Reilly Media
Год: 2019
Страниц: 332
Язык: английский
Формат: epub, pdf (conv)
Размер: 27.0 MB
Learn how to fuse today's data science tools and techniques with your SAP enterprise resource planning (ERP) system. With this practical guide, SAP veterans Greg Foss and Paul Modderman demonstrate how to use several data analysis tools to solve interesting problems with your SAP data.
The future of Data Science and Artificial Intelligence (AI) has never looked brighter. AI now beats humans at games ranging from twitchy, reflexive Pong to deep, contemplative Go. Deep Learning (DL) models recognize objects nearly as well as humans. Some even say self-driving cars perform better than their distracted human counterparts. The past decade’s massive gains in data volume, storage capacity, and computing power have enabled rapid advances in data science.
And of course technology has spread into every facet of your business (from finance and sales to production and logistics). However, is each part of your business turbocharged by data science and AI? Likely not. As wonderful as they might be, if you are not designing a self-driving car or predicting customer behavior, you are probably not using these technologies.
Many organizations may have access to business data from an enterprise resource planning (ERP) system such as SAP, and yours is likely no different. Data coming from a business system such as SAP is largely perfect as often validations and checks are in place before it is allowed to save to the database (and, one of the most essential and least rewarding tasks of a data scientist is cleaning the data). This means ERP data in SAP is ripe for the picking, and data science is here to do the harvesting!
Data engineers and scientists will explore ways to add SAP data to their analysis processes, while SAP business analysts will learn practical methods for answering questions about the business. By focusing on grounded explanations of both SAP processes and data science tools, this book gives data scientists and business analysts powerful methods for discovering deep data truths.
You'll explore:
Examples of how data analysis can help you solve several SAP challenges
Natural language processing for unlocking the secrets in text
Data science techniques for data clustering and segmentation
Methods for detecting anomalies in your SAP data
Data visualization techniques for making your data come to life
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