Data produced and consumed by the many Internet of Things (IoT) devices is constantly growing at an ever-expanding rate. It is predicted that there will be nearly 31 billion IoT connected devices by 2020. This interesting topic came to us from the RFID Journal in their article, “Finding Value in IoT Data.”
Volume is great, but the data generated from IoT devices is only valuable if you can analyze it, and that presents its own set of challenges.
Sensor and machine data is highly unstructured, which makes it difficult to use with traditional analytics and business intelligence (BI) tools that are designed to process structured data. Added to that challenge: object storage – generally used for storing this data because of its flexibility, scalability and low cost – isn’t easy to connect to analytics and BI tools in the first place.
IoT data sets are generated by a huge number of devices, and these devices record a broad array of data, enabling a broad set of use cases– including maintenance, operations optimization, and supply chains. But the value of this information can be increased when combined with existing enterprise data sources, such as sales, customer, and product information.
There are many challenges, but also many benefits of finding methods to analyze the data from IoT.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.