Data Lake or Data Landfill?
by Jon Aldred
Director, Product Management at HBM Prenscia
The term big data is used in many ways and for many applications. The increased connectivity and availability of sensor data is driving new big data opportunities for both the design engineering and asset operations communities.
However, the reality of unleashing this potential is perhaps more challenging than is often portrayed by major information technology vendors. What is promoted as a data lake…
…often ends up being more like a data landfill.
Data of good quality is hard to find and only a small percentage of available data is actually used by engineering. But there is a huge amount of potential if the true value of all that data can actually be realized.
Product designers and OEMs, for instance, may be interested in understanding real product usage to take important design decisions that might affect durability and warranty returns globally. Meanwhile, operators responsible for a fleet of vehicles or plant equipment are typically looking to enhance product reliability.
One of the primary challenges is how to scale the data handling, data management and data analytics of measured sensor data to real world applications. A scalable framework capable of performing real-world engineering analysis is needed to handle and process the volume of time series data in order to make timely decisions on performance, reliability, and operations.