Sven Löffler
30. March 2016 0
Digitization

Predictive Analytics – all companies can benefit

Today, many decisions are still made by feeling. But those decisions are often not well-founded and can lead to unforeseen consequences quickly. Predictive Analytics can help eliminating this factor. Thanks to Predictive Analytics, large companies are able to analyze large amounts of data and make predictions which help them in making reasonable decisions. The market for predictive analytics is growing strongly, according to Technavio the revenue for Predictive Analytics is going to increase by 25% annually until 2019.

Predictive Analytics – What is it about?

The main requirement for predictive analytics is a vast collection of – partially unstructured – data from different sources. The combination of different data sources like weather-, traffic-  and social media data with internal company data is especially important. With Predictive Analytics data can be analyzed with various statistical methods like extrapolation, regression, neuronal networks and machine learning to find a pattern in the data sets and to develop a suitable algorithm. This algorithm is then tested and optimized on the basis of test data. Needless to say, the larger the data set, the better the quality of the algorithm. After the optimization process is mature, the algorithm can be applied on data whose classification is unknown.

Use Cases

A promising way to implement Predictive Analytics is Microsoft Azure Machine Learning. It provides an easy-to-use drag-and-drop interface for creating machine learning models which can then be published as a web service. This allows for real-time scenarios to be implemented with streaming data to make predictions in real time. Strategically relevant domains for Predictive Analytics are predictive maintenance, marketing, fraud detection and route optimization.
To add on Predictive Analytics there also is prescriptive analytics. While Predictive Analytics for maintenance may use weather – and sensor data from machines to predict the probability of failure, prescriptive maintenance could also message an engineer if there was an extraordinary event so that he is able to take appropriate action in time to minimize the downtime of a machine.

Seize opportunities to gain a competitive advantage

Most organizations often do not possess the essential skills to implement these types of complex analyses and workflows. We as T-Systems offer companies the opportunity to perform fast and easy proof-of-concepts or offer advice on the implementation of projects. We thereby facilitate the entry into  the analysis of customer, product or company data. This analysis provides deeper insights and gives companies a distinct competitive advantage, as opportunities and risks can be better identified. With our services in cloud and on-premise areas, different infrastructure and analysis services can be booked without having to invest in complex systems. T-Systems also takes care of the management of the platform enabling organizations to focus on their core competencies.

Big Data Greetings,
Sven Löffler

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