22.09.2014

Why SAP HANA?

Probably no one in the SAP business community has been able to avoid the tidings of HANA. Although many have already realized the opportunities that this technology has to offer, to my experience equally as many are still wondering: “Yes, it seems great! But why on earth would I want to buy one…?” Given that the license costs involved are not trivial, it is wise to step back for a moment and consider in what situations SAP HANA could actually make sense.

 

In my opinion, there are the three general use cases for SAP HANA:

  1. SAP HANA as an analytical appliance
  2. SAP HANA for real-time business
  3. SAP HANA as big data platform

Let’s discuss each in turn.

 

SAP HANA as an analytical appliance. The most common scenario and an entry point for first-time adaptation of HANA into an organization is to use in a BW accelerator scenario. This is quite natural as the whole HANA platform stems from SAP’s first encounters with in-memory technology that lead to a product known as BW Accelerator, an early predecessor to HANA at the time.

Yet, HANA has more to offer than mere BW acceleration. As a superfast in-memory database, native analytics built on HANA can speed up any process that requires massive analytical processing power. Also an increasing amount of analytical applications from SAP are using HANA as its database such as Infinite Insight, Predictive Analysis, and Lumira. Therefore, to anyone needing additional number-crunching power, HANA offers new interesting possibilities.

 

SAP HANA for real-time business. As a distinguishing factor compared to other analytical appliances such as IBM Netezza, Teradata Aster, HP Vertica, and the likes is that HANA is designed to act equally well as a business transaction database (OLTP). Although SAP’s Business Suite on HANA is still quite novel, down the road it is plain to see that an ever increasing amount of SAP’s business applications will be optimized to run on HANA.

Real-time business processes open a totally new window of opportunities for business. For example, real-time processing of POS or eCommerce transactions, real-time service and maintenance processes, or real-time call center functionalities enable an entirely new way of engaging with customers. Also the old marketing process of transaction recording > analysis > segmentation > advertisement will be shifted to real-time and fully customized product offers made on the fly – just go to eBay or Amazon to see what I’m talking about…! With HANA there is no reason why the same business logic could not be applied for example in a B2C point-of-sale or B2B eCommerce setting.

 

SAP HANA as a big data platform. This is probably the most misunderstood aspect of HANA. SAP has relied heavily on big data in its HANA marketing, and the typical counterargument goes that you could not even technically run a petabyte of data on HANA in-memory – let alone afford to do so from a licensing or hardware perspective!

However, what makes HANA a powerful big data platform is not the amount of data that it can store at each time, but how fast it can execute the job. Compared to Hadoop, by the time a Hadoop cluster has initiated a MapReduce job, HANA is already finished.

Obviously data management is a major consideration with HANA and a combination of a data repository for cold data (such as Hadoop or Sybase IQ from the SAP stack) together with an optimized HANA instance is necessary when it comes to really big data. Being able to decide whether a piece of data is assigned to disk or in-memory will most likely be one of the key next steps in HANA architecture going forward.

However, by far the most powerful feature of HANA as a big data platform is its ability to provide closed-loop analytics. This means that big data analysis can be seamlessly coupled with a business process (aka “Practical Big Data”). A great example of this is predictive maintenance: if designed as a full end-to-end process, one needs to crunch vast amounts of high-speed sensor data (your typical big data part), have a process that alerts from potential deviations from norm for decision making, integration with ERP to understand what spare parts are needed and available, what maintenance personnel are available and capable, etc. In essence, it’s the combination of an analytics appliance and a real-time business platform that turns HANA into a powerful big data engine!

 

So, going forward, it will be quite impossible to avoid HANA in the SAP ecosystem. Furthermore, real-time customer engagement and business processes of the future will not be possible without HANA in the first place. Thus, it is better to start dipping your toes in the water already now with a PoC or pilot study, and explore the opportunities of HANA of your own!

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Jani Puroranta

 Bilot-Alumni