Although ABAP develops in an evolutionary way, SAP’s solution for InMemory technology will affect your daily work as ABAP developer.
In this blog entry I will continue my blog series about analytical applications in ABAP for HANA and will share my ideas according to the second and third bullet point in the list above and discuss which skills you will need in the future.
Some of you will still remember the times when SAP started to introduce Enjoy SAP Controls like ALV grid which allowed a better user experience on the one hand but had some remarkable features for business users like Excel integration. Lots of SAP consultants made lots of money only with the reuse functions modules that display a selected set of database rows in an ALV grid. This method is now common folklore but shows that making data accessible can make a business application much more valuable for business user. ABAP for HANA offers new possibilities that every ABAP developer has to know:
So I recommend that you learn about these new features to keep your knowledge up to date.
In my last blog I gave an example how dashboards can support the user to make better decisions. In fact you don’t have to use libraries like D3 and you can also use SAP tools that make the creation of dashboards very easy. SAP offers various tools that allow fast visualization, f.e.:
In fact you can use any tool that allows you to perform queries on HANA data and expose them as web application. You can integrate these web applications in the following ways:
In the latter case you can “wire” the CHIPs so that information between the SAP Business Suite resp. your custom developed application is interchanged. For you as ABAP developer working in SAP HANA environment mashups will be more and more important and you should learn how to develop them.
At SAP TechEd there was a lesson TEC160 “SAP Technology Highlights – Putting them all together” that shows the interplay between SAP Business Suite, SAP NetWeaver Business Client, HANA and Business Object-Tools. I definitely recommend this session.
In the past as well as today ABAP developers use a treasure chest of reuse tools for rapid development of business solutions. These are huge frameworks as well as libraries like FIMA package that contains functions modules and classes for financial mathematics. In the future more and libraries inside HANA will come like the Business Functions Library.
There will be various applications of above mentioned libraries and techniques. For example you can use fuzzy and multi columns search to look for duplicates of business partners and other business objects.
Mashups are the most important feature of next generation apps because visualization of operational data. Using them the user will make faster and better decisions when doing his or her work.
Next Generation analytical applications for ABAP introduce the aspect of quantitative approaches in decision making to enterprise resource planning. Let me give so examples to sketch this in detail:
SAP is very strong in the area of business processes and business intelligence so they have tools that allow real-time monitoring, real-time situation detection and real-time dashboards for different user roles. So the inside to action paradigm, that is very well explained as example SAP CRM Competitor Analysis, will become ubiquitous in your applications.
In my opinion most SAP users are well prepared for this step because we all know about the basicsof descriptive statistics: we can read different chart types and most have at least an intuitive idea of statistical parameters like arithmetic mean, median, standard deviation, variance, range and absolute deviation. When it comes to more predictive models the situation becomes a little but difficult because from experience those concepts are not told at school and there are only used by some experts in distinguished industries like production, production planning, financial services and insurance to mention a few.
HANA is offering various methods for statistics and data mining because of integrated statistical functions: We can set up and R server on the HANA system and can call R from SQLScript and HANA has an integrated library for predictive analysis. What is more useful? In fact this is up to your requirements: If you are familiar with R then you can choose many libraries and create even your own. Since R is a separate server on an HANA system the call can become a bottleneck where PAL can benefit directly from HANAs multicore architecture.
The most interesting question is how this can help us to create Next Generation ABAP applications. Before I come back to that question I would like to discuss how quantitative (= mathematical) approaches are used in commercial sphere.
With automated decision support we introduce the aspect of descriptive and inferential statistics to SAP Business Suite. Statistics and Econometrics already have a plethora of different models, methods and algorithms and many of these techniques are now supported directly within SAP HANA.
Unfortunately tool support is a necessary but not sufficient precondition because from experience inferential statistics is limited to certain industries and lines of businesses. I think this has many reasons:
Please let me summary: quantitative methods approaches in management science are well developed in certain lines of business like finance and insurance and in others not. IMHO there are good and bad reasons for the dislike of mathematics:
I will try to answer the last question and therefore I will try to describe what statistics is about.
Lets discuss an example: a series of values (think of account balances) can be seen as series of data points measured at successive time instants (perhaps the first of every month). The result is a curve of the payment history of a customer. So how can we do a prediction of future data. SAP Mentor Alvaro Tejada explained a possible solution months ago in one entry of his visionary blog series about HANA and R: http://scn.sap.com/people/alvaro.tejadagalindo/blog/2012/01/13/prediction-model-with-hana-and-r As mathematician I like this approach and I hope that many people will start to get experience with this approach. Nevertheless I have to do explain the limitations of this approach by listing its implicit assumption:
So let me summarize: Using methods from inferential statistics doesn’t simply produce correct results because without further analysis we can’t be sure that our model is sound. In fact the statistical model is the holy grail of every statistician and he’s always looking for the truth of model and does a lot of work the discuss strengths and weaknesses of the model. When I was at university statistics was a very conservative science and was proud to the right tool to discover laws of nature as well as economics – and this some something different than decision support in enterprises.
Unfortunately often there are no simple laws as “nature” of huge data sets in enterprise data. Moreover, there are serious problems: We have misrecorded entries in the database, moreover the data is dispersed in different database systems and may be time dependent. This can be a nightmare for statisticians who know all about the possible pitfalls: structures that appear in an ad hoc-analysis may occur by pure chance and don’t indicate an underlying law.
So many practitioners choose a different approach for analyzing huge datasets: instead of looking for a perfect model they use algorithms instead of models and they got very creative and choose methods computational geometry as well as machine learning and even semantic technologies to tackle large datasets. And so it’s not surprising that SAP’s Predictive Analysis Library for HANA offers lots of techniques of data mining. So what’s inside SAP’s Predictive Analysis Library for HANA? Besides above mentioned algorithm for linear regression and common folklore like ABC analysis there are implementations of Data Mining-algorithms:
Data Mining offers techniques to analyze huge datasets and uses statistical methods in a very pragmatic way and sometimes leaves “hard statistical science”.
Even if our mathematical models may not accurate to accurate to deal with large data sets (seen from the perspective of pure science), we can’t afford to ignore them because they are strategic assets for business decisions.
HANA will enable us to better understand data. SAP Mentor Thorsten Franz explained this in his blog about the true value of BW for HANA: HANA will bring us agility and the possibility of deeper insight into our business. If we want to go a step further we will use methods of Data Mining and sometimes inferential statistics to analyze transactional data. For you as ABAP developer this will have the following consequences:
ABAP developers won’t become statisticians but in the future data miners and statisticians will perform analysis of operational data. Since mostly ABAP developers are experts for the data model of SAP Business Suite you will work closely together with statisticians and data mining experts.
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