Big data is one of the industry buzz words at the moment. Big data can be very useful and it can bring some significant insights into many areas of the electronics industry.
With the faster processing, ease of collecting data and the falling cost of storage, it is tempting to collect as much data as possible thinking that it may come in useful at some stage, but this can be a fallacy.
Remote sensors are now becoming more sophisticated and can output vast amounts of data relatively easily. Also big data collection systems are also developing and enabling much more data to be collected more easily.
However it is the big data analysis that is the key to success. What is the point of collecting it if you don’t use it for analysis? However, it is often much easier to collect the data than to work out the analysis. It can be tempting to get started without placing sufficient thought into how it will be analysed and used.
Typically much of the collected big data remains unused. There are many statistics for this and they vary slightly dependent upon the industry.
When planning to use big data there are a few pointers. Getting the right data is the first key. To do this it is necessary to look at the problem that needs solving. This will help focus on collecting the right data which can then be analysed later. Sometimes it may be helpful to collect data from the input and output of a process, but other times data from the use of the system may be more appropriate.
One successful example of the use of big data is that of Amazon, where the habits of each user are tracked and suggestions made for further purchases. In other systems it may be that the performance of a large system can be analysed and tell-tale signs noted that might indicate when preventative maintenance is required. In this way the right part can be ordered in advance of the system undergoing maintenance, thereby considerably reducing downtime.
Another major aspect of big data analysis is that of ensuring the data is correctly tagged. One obvious example may be the timing of data. If the time is not correctly added as part of the meta data, then it may be of little use.
To effectively analyse the big data it is necessary to put some thought into what meta data needs to be attached to the big data being collected.
Big data can provide some major advantages to any business, but the real key is not the data itself, but the big data analysis and the implementation of the results. Planning and preparation into the collection and tagging of the data is key, so that the data can be analysed intelligently to provide the real insights into what it can reveal. If this can be accomplished, then big data can be a big deal.