IoT needs Big Data and vice versa

IoT needs Big Data and vice versa
28.05.2018 Kathrin Kempf
big data

IoT without Big Data is like a Christmas duck without filling. And Big Data without IoT is like termites without a hill. IoT connects all kinds of living and not living things with the Internet and with each other. Sensors accomplish this and are able to transmit all sorts of data that they measure. However, this data collection is only sensible when it is target-oriented and made for a specific purpose. For IoT Service design the input of Big Data is absolutely essential. Relevant Services that fulfill pressing customer needs have to be based on Data Analytics. 

Big Data and IoT

Big data is essential groundwork for IoT Services
Source: iq! Managementberatung

IoT and Big Data: Data collection & storage

The first step of strong Big Data competence sounds simple but it is not. Instead of collecting blindly and wildly all possible data, every IoT system has to be based on a systematic and incremental masterplan. Ideally, every data collected serves already a distinct purpose, a Predictive Maintenance environment, all variables that influence the maintenance date and interval are tracked and analysed. More often however, Big Data collection follows certain key questions at first, e.g. in order to identify the variables determining Maintenance requirements.

Data storage should follow the data protection necessities. IoT may be a little bit of a “grey zone” when it comes to data protection. However, in preparation of future, more strict laws and taking customer concern into consideration it is very important to take care of user opt-ins and other requirements.

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IoT and Big Data: Data analysis

The core part of Analytics is to draw the right conclusions out of the tons of data streams. Part of the task is fomulating the right questions in order to collect the adequate data. The other part is to recognize crucial patterns in order to optimize the IoT offer. If we stay with the Predictive Maintenance example, the combination and interdependencies of variables that determine the outage of e.g. a vehicle would be the pattern to find. IDC and EMC estimate that the share of this type of relevant data (which translates into valuable IoT Services or other Business Insights) is very low, between 1% and 2%. So the challenge is not to manage huge amounts of data, but to define the right data first.

IoT and Big Data: Data interpretation

Finally, the relevant data is used to optimize and enrich the IoT system. In the Predictive Maintenance example, Maintenance alerts and tour planning without outages would be meaningful services for clients. Transparency regarding use of data is very important in order to maintain and increase customer trust.


IoT and Big Data belong strongly together. IoT taps its full potential only if Big Data is applied in a sensible manner. For companies offering IoT Products and Services it is important to find the right people to do the job. Job profiles would include Business Analysts formulating the right framework on the one hand and IT specialists capable of conducting the Analytics on the other hand.




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