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Optimize business models with Big Data and IoT processes

Innovative and data-driven

Using Big Data and IoT processes to automate and build data-driven business models

Seeing the bigger picture and making forecasts for the future. With the Internet of Things (IoT) and Big Data Analytics, this is no longer a vision for the distant future. Use of this type of data analysis has been propelled by process digitization and the development of innovative, data-driven business and service models. These include, for example, the prediction of maintenance requirements for production plants and more reliable seasonal planning. The huge amounts of data processed for applications are no longer provided solely by software but are also obtained from devices or things. Big Data is complemented by the Internet of Things.

What does Big Data Analytics mean?

Big Data Analytics is the real-time analysis of large amounts of data of various types to uncover patterns, correlations and other value-added information.

Classic use cases for Big Data & IoT

  • Predictive Maintenance

    Microphone-equipped production equipment allows operations to be performed by analyzing sound features. This allows anomalies to be detected and predictions to be made about maintenance requirements and failures - regardless of the system manufacturer.

  • Smartification

    Big Data Analytics enables comprehensive smartification in many differend areas. From a business point of view, planning processes, for example, can be designed more efficiently to enable more reliable seasonal planning. The Internet of Things makes the "Smart City" concept feasible, with such elements as networked parking spaces, offering private individuals the ability to search for a free parking space - and so benefit from digitalization.

  • Fleet Telematics

    Telematics integrated into vehicles makes various data available digitally enabling a more efficitent, transparent and safe fleet of vehicles, by early detection of anomalies, for example in routes or vehicle maintenance.

  • Projections

    Use historical data to forecast the development of energy prices in regulated markets or enrich the order management for retailers with branch-specific target figures taking a range of factors, such as holiday periods or social media trends, into account.

  • Advanced Analytics

    Advanced Analytics enables the targeted analysis of large amounts of data (big data) for the targeted and efficient control of technical systems and assets. Targeted analyses on the basis of collected data make it possible to forecast energy consumption and supply as well as the condition of your installations.

Which skills are important for success in using Big Data & IoT?

Integrational know how

For existing traditional IT as well as for various data sources such as sensors and machines.

Data engineering know how

For data integration within standard environments (e.g. "Data Lakes").

Data science know how

For mathematical models and simulation methods.

Cloud-native software design

For application development.

Your Contact for Big Data & IoT

Martin Weitzel
Expert for Innovation Topics