Advanced analytics enables innovative business models

Business emails, connected cars, online orderings in webshops, blog records of social media groups, tracking of location-based data, video recordings by surveillance cameras, predictive maintenance based on automated monitoring – an immense amount of data is created during the day. And as digitization continues to increase, so does the volume of data. Analysts from IDC predict that the overall amount of data generated worldwide will more than double every two years and will reach 44 zettabytes by 2020. To put this into perspective, a zettabyte – 1 followed by 21 zeros – is equivalent to the storage capacity of some 250 billion DVDs.

German chancellor Angela Merkel has described data as "the raw material of the future." By processing large amounts of data, German companies should therefore be able to develop new products and optimize business processes. The next five to ten years are crucial for the future of the German economy, and will show whether German businesses will be more than just the "workshops" of large US or Asian IT enterprises. Companies who want to remain successful in the future should therefore digitize their business models with a minimum of delay so that they can make the most of big data's enormous potential.

According to a 2014 study by PwC, companies see advanced analytics as an excellent approach of improving profitability, getting to know their markets better and optimizing their own organizations and processes. Data mining helps them identify relationships and patterns that allow them to make better decisions and more accurate forecasts. Changing market conditions can be recognized quickly and appropriate actions can be taken. Data mining can also provide new insights on trends and customer needs that can be used for the development of entirely new products and services. Advanced analytics thus forms the basis for innovative, data-driven business models – even for small to medium-sized companies.

There are three factors that differentiate advanced analytics from traditional data processing. Firstly, there are no restrictions on the amount of data that can be analyzed (volume). Secondly, data from different sources and in different formats or even without data structure can be processed (variety). Finally, data processing is performed at very high speed, often in real time (velocity). Big data can be used in nearly every operational area of a business in which large amounts of data occur.

Many companies are still struggling to take advantage of advanced analytics in an efficient way. The analysts at PwC know why: "So far, most industrial companies have lacked a strategic concept for the implementation of big data within their organizations. Not only that, but there is great uncertainty about how best to implement innovative big data solutions in order to remain competitive in the future. As a result, there is great demand for external expertise and support that can help minimizing risks and thus ensuring the successful transition of businesses into data-driven enterprises."

Companies who want to develop innovative products and services based on the digital raw material stored in their databases are thus dependent on comprehensive competency of an experienced IT partner. The ideal partner has the required infrastructure at its disposal in the form of big data platforms such as Hadoop or SAP HANA, as well as powerful analytics tools and the ability to use them to design, implement and run integral solutions tailored to the individual needs of every customer.