Hana and Hadoop can assist in making the next step in digitalisation. [shutterstock: 425663932, oatawa]
A current market research study by consulting firm Luenendonk highlights that many German companies - like in many countries - take a reserved view on the digitalisation. Yet to stay competitive there is no avoiding the need to develop new business models.
Technologies such as Hana and Hadoop open up new possibilities here. The current study – “Creating added-value through digital transformation” – shows that many firms are hesitant when it comes to digital transformation and innovative developments.
The studyꞌs authors perceive a danger in the trend that they detect. That trend classifies the development of new business models or the opening up of new markets as being less significant than “defensive goals”, such as strengthening the bond with the customer or making process improvements.
The study concludes that this view makes it harder to achieve bold and disruptive innovations in business models, products and services. But how can companies drive forward their digital transformation and test out new business models?
Traditional systems and architectures are not aimed at being able to flexibly master todayꞌs flood of data and data-sources. So Big Data can only become Big Business if the right technologies and organisational structures are used and established.
Traditional systems and architectures are not aimed at being able to flexibly master todayꞌs flood of data and data-sources.
To process large quantities of data, modern databases use high-calibre hardware components, and employ in-memory processing. These[GMO1] are extremely high-performance technologies but they are also expensive.
For the digital transformation a certain flexibility is needed. This is the flexibility to store large quantities of data over the short-term, without overstepping budget limits and thus raising the pressure on performance. Here is where the open-source platform comes into play, because it was created for precisely this purpose.
It must store, process and analyse very large volumes, ranging from hundreds of petabytes to zetabytes of data.
A key strength compared to other systems is that Hadoop is not based upon expensive proprietary hardware for its storage and data processing.
The advantage of the distributed file system also extends to the distributed processing of the data. It can scale-up, almost limitlessly, via cost-competitive standard servers.
New Paths for Big Data Analytics
However, in many cases Hadoop alone is not enough for Big Data Analyticsꞌ requirements.
An option available for assessing the unstructured or semi-structured data, combined with the most up-to-date business data, is in-memory processing, using modern analytical procedures.
Hana and Hadoop make a strong team for this. Combining a high-performance database and a solid mass-data platform can open up new paths for business analytics and the huge cost-savings make a compelling case.
Hana and Hadoop enable data from sensors, networks and machines to be assessed cost-efficiently and almost in real-time.
This opens up countless application scenarios, as an app from an international agricultural-productsꞌ company shows. Using this app via smartphone or tablet, farmers can recognise plant illnesses at an early stage and select the right treatment.
If the farmer sends a photo of the unhealthy plant, data-mining is used to compare this immediately with reference images for plant illnesses in the database. The given region’s latest weather-data also gets factored into the analysis.
A great advantage of Hadoop is data-streaming. Mass-data can be analysed directly in Hadoop, with statistical modelsꞌ help.
In the background, Hana draws up a recommendation in real-time, one that the farmer instantly receives on his mobile device. This includes the determination of what the illness is and also a plan for best treating it, taking into account the latest weather conditions.
The mass data needed for this, such as product data-sheets, videos or picture-reference data are located in a Hadoop Cluster. A great advantage of Hadoop is data-streaming. Mass-data can be analysed directly in Hadoop, with statistical modelsꞌ help.
Then it is only the essence of these assessments that is passed on to Hana. This approach enables vast data quantities of varying structures to be given high-performance assessment in real time.
Another plus is that combining Hana and Hadoop is also a suitable choice for smaller companies with rather limited IT resources.
This is because, using Predictive Analytics, SAP offers standard analyses that also enable firms with a low level of statistics know-how to produce models of this kind.
The key to success in this is courage to try out new things. Datavard offers innovation workshops enabling those responsible for IT to learn how to apply new technologies and simultaneously test out ideas and business models.
Datavard offers innovation workshops enabling those responsible for IT to learn how to apply new technologies and simultaneously test out ideas and business models.