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Excerpt from First Steps in SAP Predictive Analytics.
SAP introduced version 1.0 to the market in Q2 of 2012. It is important to note that it was not referred to as predictive analytics but rather predictive analysis and it was different than the current application. Predictive analysis was an application meant for analysts and data scientists. Although there was some visual/graphical content in the application that simplified the heavy lifting, it was not an application that regular/casual business users could use to any degree of usefulness.
SAP Predictive Analytics was first released in 2015. The motivation for building this product was twofold for regular business users (not just data scientists).
1. The ability to use it in a meaningful way, given that the marketplace was already being dominated by such applications.
2. The ability to transform and enrich a data set in an easy manner before being fed to the predictive algorithms. It is worthwhile to note that prior to SAP PA, this was being done by writing scripts/code. This made the transformation/enrichment of data a highly technical activity. Also, it was not transparent and was prone to errors.
So, SAP PA combined the original application, predictive analysis, with an application called Infinite Insight to deliver SAP PA.
So what is Infinite Insight? It is the flagship application from KXEN, a company SAP acquired in 2013. Infinite Insight takes away a lot of the heavy lifting that data scientists were best suited to do in the past and pushed this to the predictive engine. It helps the analysts do what they are supposed to do best: analyze, and not worry about preparing and modeling the data.
Back to SAP PA. The combination of these two products ensures that it caters to both major constituencies: data scientists and regular business users. You will have the option to use whichever embedded product best suits your needs and capabilities. The erstwhile predictive analysis component shows up as Expert Analytics and the incorporated Infinite Insight component appears as Automated Analytics. You might ask this: what are the similarities and differences? The answer to this question will unfold as I get into the details in subsequent chapters, but there are some similarities (more in the nature of functional overlaps) and some differences. You do not face a binary choice—you can use both flavors if you so desire.
Curious about how to leverage SAP Predictive Analytics (SAP PA) to effectively mine data and unearth trends, patterns, and relationships? In this book written for users and analysts, readers will explore the foundations of SAP Predictive Analytics. Review the architectural underpinnings and technical components that make up SAP PA. Explore how SAP PA works with SAP HANA. Walk through the installation steps and learn the differences between the desktop and enterprise versions. Explore SAP PA modules and components, including the predictive analytical library (PAL), the application function library (AFL), and the SAP HANA automated predictive library (APL). Leverage the data manager and learn how to create an event log aggregation. Get tips for performing text analysis and take an in depth look at automated analytics, including Expert Analytics. Dive into a sales and pipeline forecasting example using specific SAP PA functions and algorithms.
By using practical examples, tips, and screenshots, this book explores:
– SAP PA architecture and technical components
– How SAP PA works with SAP HANA
– Core SAP PA modules and components
– Detailed sales/pipeline forecasting example
Author Anurag Barua is an SAP expert and currently works in the Business Transformation Services (BTS) group at SAP. He has 25 years of experience in conceiving, designing, managing, and implementing complex software solutions, including more than 20 years of experience with SAP applications. He has led enterprise-wide business and digital transformation programs using SAP across nearly 30 enterprises globally and a broad swathe of industry verticals including Public Sector, Media, Manufacturing, Utilities, Financial Services, and Pharmaceuticals. In the last couple of years, Anurag has been heavily involved in advising and leading SAP S/4HANA digital transformation programs for his global clients. His core SAP competencies include FI and controlling; logistics; SAP BW; SAP BusinessObjects; enterprise performance management (EPM); SAP Solution Manager; SAP Fiori; governance, risk, and compliance (GRC); and project management. He is a frequent speaker at SAP conferences globally and contributes to several publications. He has written three books on SAP, including First Steps in SAP Fiori for Espresso Tutorials. He holds a Bachelor of Science in Computer Science and an MBA in Finance. He is a PMI-certified PMP, a Certified Scrum Master (CSM), and is ITIL V3F certified. You may contact Anurag via email at Anurag.firstname.lastname@example.org.