How bookkeeping turned from necessary expenditure to significant revenue stream
Big Data has become a buzzword like no other, but it is more than that. In its core is the idea that the large data sets companies have to keep anyway to function, can lead to valuable insights. But these insights are often difficult to find by traditional means. This is mostly because the data sets involved are too big for traditional analysis. Many traditional databases cannot keep up with the unregulated flow of data.
Big Data covers a wide area and is largely dependent on your use case. For some companies dealing with data in the above terabyte range is actually day to day business.
But for most, facing the task of curating, effectively storing, combining and analyzing data in the above gigabyte range is already a challenge.
For an SAP project on processing sensor data, we helped with that step. Originally the project required the storage and analysis of less than a million data points per day. With new and improved sensors this rate exploded to 90 to 300 million data points per day!
We work on an ongoing project, to improve storage and analysis of that data. Advanced queuing and an efficient in-memory server work hand in hand with SAP HANA technology to make this run as efficiently as before. And future proof it for tomorrows sensors with even higher demands.
The IoT is not necessarily a part of Big Data, but can enable it. Not all of big data is built on the above mentioned bookkeeping. Other cases are built from the ground up. Especially the emerging industry 4.0 has often needs for sensor data that is not traditionally available. And new sensor data needs new ways to reach the data bases. Not only transmitting the amount of data involved in this can become difficult, but also doing so in a reliable manner.
Because all the sensor data from a smart factory is useless, if it’s not available in every second of every day.
For the above mentioned SAP project, we are also working on delivering all that new data reliably. Traditional wireless technology can either not keep up with the amount of data or deliver reliably the necessary range. Cutting edge, self-healing, ad-hoc mesh networks are needed to reach the necessary level of reliability.
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