These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site. All information these cookies collect is aggregated and therefore anonymous. If you do not allow these cookies we will not know when you have visited our site, and will not be able to monitor its performance.
Please be informed that Hubspot, in its capacity of service provider, collects your data on an anonymized basis. If you however submit a form via Hubspot, you acknowledge and agree that your personal data will be used for marketing purposes.
These cookies may be set through our site by our advertising partners. They may be used by those companies to build a profile of your interests and show you relevant adverts on other sites. They do not store directly personal information, but are based on uniquely identifying your browser and internet device. If you do not allow these cookies, you will experience less targeted advertising.
Please be informed that Hubspot, in its capacity of service provider, collects your data on an anonymized basis. If you however submit a form via Hubspot, you acknowledge and agree that your personal data will be used for marketing purposes.
Don’t panic. The purpose of this blog post is not to explain how, let’s say, column storage is different from row storage. This will not be a presentation of all technical details of SAP HANA. Instead, you will discover what HANA can mean to you.
As not all of you might have the same level of understanding of HANA, let’s just start with a small recap of what it is all about.
H(igh – Performance) AN (alytic) A(ppliance) is an in-memory, column-oriented, relational database management system developed and marketed by SAP.
It all started when Hasso Plattner and his SAP colleagues realized that, over time, more and more information and data is generated and gathered. Information that, up till some years, could not be used in the best possible way. The data was too massive to analyze and the information technology didn’t allow fast ‘ad hoc/real-time’ processing. This resulted in suboptimal “business critical” decision making.
The first HANA version was officially released in 2010. It continues to evolve in the sense that SAP products are, one by one, being ‘HANA optimized’. It is not just a replacement of the current database platform: more and more functionality is added.
Some – and let’s be honest, most customers and consultants – have the idea that HANA is a costly hype that is not ready for productive use yet. But as a true HANA believer, I am convinced we should not be blind to what the future will bring and is already bringing.
HANA is becoming an affordable platform in terms of license and hardware. In-memory solutions are becoming a commodity. On top of that, SAP opened its certification program to multiple hardware vendors, which has definitely played an important role in pushing the appliance prices down.
SAP already showed a strong focus and commitment to deliver. New functionalities and tools are becoming HANA based only, such as self-service tools (e.g. Lumira) and Fiori Apps. HANA is no longer only seen as a database platform to replace e.g. Oracle. It has become THE development platform of the future and therefore brings added value to our customers. HANA is delivered with detailed migration paths and tools (such as Rapid Deployment Solutions). This simplifies the migration to this new technology which is an extra win for both customers and consultants.
Bottom line, what is important for you, our customers, and where do they see the added value HANA can bring? In short:
“The right information @ anytime, anywhere”
End customer focus is key in the “fast changing” market we live in. If a company fails to deliver on the promise it has made, it will struggle to survive. Here are some ‘retail’ examples of the processes that require such agility:
So far, the above mentioned examples only address how to analyze data available at the moment for ad hoc analysis purposes. But what about predictive analytics that takes things a step further: making predictions based on available data?
Imagine integrating the weather forecast to make sure that e.g. an apparel or footwear company can optimize its store replenishment process of ski boots or bathing suits according to such a forecast in a specific region. Or think about using predictive analysis to perform ‘upfront’ maintenance activities avoiding costly repairs, etc… We could even imagine new business models and services originating from these new ‘data capabilities’.
Interested in hearing more? Feel free to contact me.
Enjoy HANA!
Author: Bart Van Peteghem. You can connect with Bart on LinkedIn
