What is Machine Learning and why is it important?
Well, first of all it is nowadays a hype. So, it is important to at least to know what the rest of the world is talking about.
And the reason why it is a hype, is because machine learning is bringing huge advances in various fields. It gives computers the possibility not only to perform certain tasks, but it also enables a computer to first learn the rules of performing a given task (learn from experience, from historical data).
Let us take the healthcare field for example, machine learning algorithms are successfully used to spot signs of various sever illnesses (breast cancer for example) as early as possible and reduce the risk on the patients.
Financial institutions also use machine learning algorithms for fraud detection and to combat money laundering. These algorithms are able to analyse millions of transactions and point out those that indicate suspicious patterns.
In the online security field, machine learning algorithms are used to track suspicious behaviour and detect privacy intrusions.
And also, we should not forget that we all use machine learning in our daily lives. Whether it is Siri we summon on our Apple device or Alexa on our home pod, whether we use Social Networks in the internet, or the Google Maps in our car, the core of these systems is powered by machine learning algorithms.
And in the daily operating business of companies, machine learning algorithms are automating basic tasks that would otherwise be done manually, like analysing invoices to detect duplicates, orders, etc. …
In the field of BI, one of the reasons why machine learning is important is because it is a part of the techniques used in predictive analytics. This gives employees the possibilities to predict certain results in the future. Sales people for example can make predictions of their sales volume, managers can evaluate multiple predictions of how certain decisions might impact future results, and make their decision based on these.
How does it work?
Let’s take a look at this quiz:
- 2 → 4
- 3 → 9
- 5 → 25
- 6 → ?
Now why have you been able to figure out that 36 is the right answer? Because you have recognized a pattern. And that is exactly what machine algorithms are doing. They are trained on sets of sample data where they are learning to recognize patterns and match these patterns to the correct responses (they are Learning from Experience). After the training we can query the algorithm for a response by providing it with a new set of data and what we get is (hopefully) an accurate response.
The machine learning algorithms are designed to work on problems much more complex than the quiz presented above, with a great number of input dimensions. This enables them to perform complex task like image or speak recognition, or forecasting some potential sales results based on complex historical market data.
Machine Learning with SAP Hana and Fiori
Since Machine Learning is such a hot topic, it generates a lot of curiosity and desire to experiment, and that was also the case for us. We at Inspiricon became curios how this new field could bring added values to area we are already working in, which includes BI, SAP Fiori and SAP Hana.
Well, it turns out SAP Hana has already a pretty robust support for Machine Learning. SAP provides the SAP Hana Predictive Analytics Library which offers the possibility to use machine learning algorithms and even build neural networks. Combining the power of this with SAP Fiori, it is possible to build some interesting applications in the field of Predictive Analytics. For example, we were able to build a small Fiori Application to predict the daily and monthly Sales figures for individual stores within a supermarket chain. Following illustration shows a rough overview of an architecture for this application:
The Fiori Application we have developed would be targeted to managers, and they would be able to explore the forecast until the end of the year from within the Fiori Application. Even more, we are experimenting further with this scenario and investigate how to extend it with other features like the integration of What-If Scenarios, such that one can investigate how certain management or marketing decisions (like promotions) can influence the predicted sales:
Machine learning can already be tackled with a simple Hana backend!
While there are powerful big tools out there like Tensorflow for neural networks or SAP Predictive Analytics, what is important to know is, that these are not necessarily mandatory in order to approach the topic. As explained above, SAP Hana already provides the means to build such approaches and with SAP Fiori it is possible to build an UI Application tailored for the specific scenario that is implemented. And the preliminary data analysis can be performed with powerful data analytics tools that are available for free for Python (Pandas) or R. So, with no additional cost in licensing or infrastructure this is can be a very attractive approach, especially for smaller problems that do not require intensive data processing.
Which approach is finally chosen however, depends on the specific use-case and shall be properly be evaluated by the development team. The maintenance of the solution and the license cost will also be an important factor for the owner of the solution and must be taken into account when making a decision.
Image sources: Inspiricon