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Analytics with SAP | SAP HANA 2.0 – An Introduction

dvankempen
Product and Topic Expert
Product and Topic Expert
‎2020 Feb 19 12:31 PM
14,776

Business Intelligence Suite(s)











In this blog series you will find quotes, backgrounds, suggested further readings and other information related to my latest book SAP HANA 2.0, An Introduction published by SAP Press.

As the goal of the book is to provide an introduction, we could not spend as much time and pages on each and every topic as we wished at times. Although SAP HANA modeling and SAP HANA advanced analytics topics are extensively covered (see the "quotes" blogs about Development and Advanced Analytics), an overall discussion of reporting and analysis, business intelligence, data mining, and analytics with SAP was omitted. In this blog, I will cover these topics in a bit more detail and include references where to find more information. As the topic is rather broad, we will do it in two parts. This is part 1 about the products (on premise). Part two will be about the services (cloud-based).




About Analytics


In the previous post about Data Warehousing with SAP we focused on the single source of truth quest that started some 30 years ago. In this post, our concern is what to do with it: reporting, analysis, analytics, data mining, and machine learning.

As with data warehousing, companies who pioneered these technologies and who were once listed as leaders on Gartner's Magic Quadrant have for the most part been acquired. The Canadian reporting giant Crystal Reports merged with the French business intelligence specialist Business Objects in 2003 and a little later folded into SAP (2008). For data mining and statistics technologies, SAP acquired KXEN in 2013. Similar purchases were made by IBM with Cognos in 2008 and SPSS one year later, both software veterans: Statistical Package for the Social Sciences was founded in 1968 and Cognos in 1969 (again from Canada).


Analysis and Analytics


Although often used interchangeably, the terms analysis and analytics have different meanings. For some analytics references systematic analysis, i.e. a scientific approach to analysis. Others define analysis as looking backward, explaining the past, whereas analytics looks ahead and explores potential future events. See What is the Difference Between Analysis and Analytics? for an argument. See also the Gartner Glossary on Analytics for a definition of the term as used in the industry today.

Although in the SAP product portfolio we encounter both SAP Predictive Analytics and the SAP HANA Predictive Analysis Library (PAL) and SAP HANA Text Analysis as part of the SAP HANA advanced analytics solutions, in this blog we will follow the above-mentioned distinction: analysis explains, analytics predicts.

Keep in mind that both terms are tightly related as is the concept of BI and we find Gartner to bundle them in a single Magic Quadrant for Analytics and Business Intelligence Platforms. The latest version had SAP places in a sweet spot amongst the visionaries.


Glorified Statistics


When you’re fundraising, it’s AI. When you’re hiring, it’s ML. When you’re implementing, it’s logistic regression. - quoted from Introduction to Data Science.

Reporting about past results is important (SAP just presented its 2019 numbers) but a little dull compared to the magic of predicting the future. Which is why technologies related to this objective often get a lot of media attention.


Data Mining was listed prominently in the early 2000s. Today, we encounter technologies related to Machine Learning and Data Science (usage of uppercase is usually an indicator). Again, the different terms have a lot in common, hence the quote and disdained remarks about machine learning as glorified statistics (like data mining before). For a discussion on this topics, see

Whatever side you take, both data mining and machine learning have been around for some time, overlap, intertwine, and rely heavily on statistics. According to Stephan Kolassa, data scientist at SAP Switzerland, the perfect data scientist combines communication and programming skills, business knowledge and statistics (see his post on Stack Exchange for the R code so you role your own Venn).

new data science Venn diagram


SAP Business Analytics


Analytics is one of the four pillars of SAP's Business Technology Platform that brings together operational (O) data and experience (X) data (see the white paper for the vision). Key topics are

  • Augmented BI

  • Collaborative planning

  • Predictive analytics

  • Data warehousing




Product-wise, SAP Business Analytics comprises

  • SAP Analytics Cloud

  • SAP Integrated Business Planning

  • SAP BusinessObjects Business Intelligence suite

  • SAP data warehousing solutions


We already described Data Warehousing with SAP in the previous blog and will address SAP Analytics Cloud in part 2. Business planning we will put on a back-burner for now; let me know in the comments section if this has your interest.


SAP Business Explorer Business Intelligence Suite


For reporting and analysis with the SAP Business Warehouse (BW), SAP developed the SAP Business Explorer Business Intelligence suite, BEx in short, as in BEx Query Designer and BEx Analyzer Microsoft Excel Add-In. Like BW, this product goes back twenty years or more. It is now part of SAP NetWeaver technology platform and included with the latest 7.5 release so supported for some time to come.

BEx contained all the "classic" components of a BI suite: reporting tools, data discovery (analysis), dashboards (portal), and, most importantly, an Excel add-in.

For an overview of SAP BW, see my previous post about Data Warehousing with SAP.



Image source: How to view Business Explorer (BEx) reports in SAP Cloud Platform Portal business sites

For the documentation, see

For training about SAP BW query design and analysis, see the learning journeys




SAP BusinessObjects Business Intelligence Suite


Unlike the brands of most companies it has required, SAP has kept BusinessObjects and Crystal Reports (including crystalreports.com) in the product names for its on-premise business intelligence and reporting solutions.

As mentioned, SAP acquired Business Objects (with space) in 2008. Its main BI platform product had evolved from version 2.0 to 6.5 with Crystal Reports at version 10. Both were combined into BusinessObjects XI (eXtreme Insight, nothing less), followed by XI release 2. Under SAP, this became XI 3.1 (2008), 4.0 (2010), 4.1 (2012), and 4.2 (2015). Although future updates looked uncertain for some time, at SAP TechEd 2019 version 4.3 was announced.

For more information and to subscribe for updates, see



For more information and additional resources, see


For the learning journeys, training courses, and certifications, see

SAP Press has published a number of books about SAP BusinessObjects (although some titles are getting a little stale)

If Google Trends is any indicator, we see public interest for SAP Analytics Cloud overtaking BusinessObjects around 2017. SAP Analytics Cloud will be covered in the next blog.




SAP Lumira


SAP Lumira was first launched in 2012 as SAP Visual Intelligence but later changed into SAP Lumira (2014). The cloud version of SAP VI evolved into SAP Analytics Cloud, by the way, as we will see in the next blog.

SAP Lumira contains two client tools

  • SAP Lumira Designer - dashboard design

  • SAP Lumira Discovery - data discovery


In addition, a server component provides the integration with the SAP BusinessObjects BI platform. The SAP Lumira clients merged functionality from several predecessors like SAP BusinessObjects Explorer (end-of-life due to reliance on Adobe Flash), SAP BusinessObjects Analysis for OLAP, SAP BusinessObjects Dashboards, SAP BEx Web Application Designer, SAP Design Studio, and some others.



Although development focus for SAP Analytics is cloud-first, SAP Lumira is still under development with new versions scheduled for release. For more information about the journey, see

For more information and additional resources, see

  • SAP Lumira - product home page on sap.com

  • SAP Lumira - documentation on the SAP Help Portal

  • SAP Lumira - Learning Journey with SAP training and certification

  • SAP Lumira - Community page, including video tutorials


SAP Press has published two titles about SAP Lumira



SAP Predictive Analytics


SAP Predictive Analytics started as SAP BusinessObjects Predictive Workbench in 2008 as an SPSS OEM (licensed technology). After IBM acquired SPSS, this was discontinued. The follow-up was SAP BusinessObjects Predictive Analysis, built on the same code-line as SAP Lumira but with predictive capabilities added, first released in 2011.

SAP acquired KXEN in 2013 (SAP News announcement). Like Business Objects, the company had its roots in France, founded in 1998. The Knowledge eXtraction ENgine provided predictive analytics technology (complex maths and statistics, that is) to the business user. It was marketed as a suite of products under the banner InfiniteInsight.

KXEN InfiniteInsight products were merged with SAP BusinessObjects Predictive Analytics at the time of release 2.0 in 2015. Version 3.0 was released the next year but no longer marketed under the BusinessObjects brand.

For the lovers of alphabet soup; the algorithms of SAP Predictive Analytics are bundled for SAP HANA in the Automated Predictive Library (APL), not to be confused with the Predictive Analysis Library, PAL in short, a native built-in application function library (AFL) although both can be used for linear regression and other common algorithms.

SAP Predictive Analytics integrates with SAP HANA and the SAP Cloud Platform for machine learning (data mining) capabilities (see below).






For more information and additional resources, see



SAP Press also has published a book on this product




Illustration from the SAP Predictive Analytics Developer Guide.



Data Science and Intelligent Technologies


As mentioned, statistics, data mining, and data science (machine learning) are closely related. Interest for the latter took off in the last decade together with the switch to cloud computing and the availability of processors specific to machine learning: GPU and even TPUs (tensor processing units). For an overview, see

SAP started to market the technology first as SAP Leonardo Machine Learning Foundation under the  SAP Leonardo umbrella. Today, we find them listed as another pillar of the Business Technology Platform (see illustration above) as Intelligent Technologies.

Product-wise, SAP Artificial Intelligence comprises

  • SAP Data Intelligence (SAP Data Hub)

  • SAP Intelligent Robotic Process Automation

  • SAP Conversational AI


The Data Science Learning Journey includes SAP training courses (DSC100-300), SAP HANA courses, plus courses about SAP Predictive Analytics, SAP BusinessObjects, and SAP Lumira, so it nicely wraps up our discussion. If you are interested to start this journey with this course, go to

 
















SAP HANA 2.0 - An Introduction


Just getting started with SAP HANA? Or do have a migration to SAP HANA 2.0 coming up? Need a quick update covering business benefits and technology overview. Understand the role of the system administrator, developer, data integrator, security officer, data scientist, data modeler, project manager, and other SAP HANA stakeholders? My latest book about SAP HANA 2.0 covers everything you need to know.

Get it from SAP Press or Amazon:















For the others posts, see


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