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Defination
SAP Predictive Analytics is a statistical analysis and data mining solution that enables you to build predictive models to discover hidden insights and relationships in your data, from which you can make predictions about future events.
SAP Predictive Analytics Overview
Predictive Factory leverages the business value of the predictive models, ensuring the link with in production databases that feed operational systems. This user-friendly interface allows users, from business analysts to data scientists, to create, operationalize and monitor the predictive models, in a secured and productive workflow, through:
- All in one management of predictive models associated to a business context: creation of models; importation of existing models created in Automated Analytics or Expert Analytics; direct authoring of time series forecasting models; management of models versioning; monitoring of the models all along their lifecycle,
- Precise scheduling of main industrialization tasks: application of the models on new data, retraining of the models to insure their performance level and accuracy, detection of the models deviations.
SAP Predictive Analytics is a data mining and predictive modeling solution that enables you to discover hidden insights and relationships in your data and to build predictive models from which you can make predictions about future events.
Automated Analytics includes the following modules:
- Data Manager is used to facilitate the preparation of the data to be used in the analytics project.
- Modeler enables the analyst to create in a homogenous and easy-handling workflow models such as classification, regression, clustering, time series, and association rules. Models can be exported in different formats so that you can easily apply them in your production environment.
- Social extracts and uses implicit structural relational information stored in different kinds of datasets, improving the decision and prediction capacities of the models. It can represent data in the form of graphs that show how the different data are linked. Dedicated workflows help you create colocation and frequent path analyses based on geo-referenced data.
- Recommendation generates product recommendations for your customers based on a link analysis provided by Social.
Refer to Automated Analytics online help.
Expert Analytics enables you to do the following:
- Produce deep analysis of the data using different visualization techniques, such as scatter matrix charts, parallel coordinates, cluster charts, and decision trees.
- Perform various analyses and build models on the data, including time series forecasting, outlier detection, trend analysis, classification analysis, segmentation analysis, and affinity analysis.
- Use a range of predictive algorithms, the R open-source statistical analysis language, and in-memory data mining capabilities for handling large volume data analysis efficiently.
Components of SAP Predictive Analytics
SAP Predictive Analytics was first released in 2015 and combines the features of two previously separate analytics products. The first of these is SAP Predictive Analysis (note: not Predictive Analytics) which SAP released in 2012. It is an advanced analysis tool primarily for data scientists that automated manual analysis. With Predictive Analysis, users can analyze and visualize data via pre-built algorithms written in the open-source statistical programming language, and then chain the models graphically to perform complex analysis.
The second part of SAP Predictive Analytics is SAP InfiniteInsight, a product SAP absorbed when it acquired the company KXEN in 2013. InfiniteInsight automates data preparation, predictive modeling, and scoring, which can help business users analyze data without manual modeling. InfiniteInsight algorithms take care of the data preparation and modelling work usually done by data scientists.
Conclusion
In conclusion, SAP Predictive Analytics emerges as not just a tool but a catalyst for data-driven success. Its diverse applications, coupled with ongoing advancements, position it as a cornerstone for businesses navigating the complexities of the digital era.
