As the name suggests big data can be simply defined as extremely large data sets that can be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. This is especially significant when volume of data is huge and needs to be managed in a better way. Traditional, approached to handle such huge amount of data delivers a poor performance which led to invention of more scientific ways to handle such data. Nowadays, big data is part of our daily life. Any sponsored ad that you see on Facebook or any other app is nothing but a result of analytics on some big data stored at one place or at different places. Big data has opened a new world of opportunities to define patterns in data and get optimal solution from it.
Advantages of Big data
Volume: The biggest advantage of big data is to cater huge volume of data. This is a very common case when sources of data include a lot of variety. With big data, scopes have only widened for analysis of such huge chunk of data.
Velocity: A challenge that comes along with huge chunk of data is the speed with which data needs to be processed. With big data, the performance has increased to a much better result set.
Variety: Usually data comes from different sources and each source delivers data in specific format that need not be like other sources in most of the cases usually seen. The challenge becomes complex when this raw data comes in an unstructured way like that of an audio file or a video file or a word file. Along with big data, the standardization is now possible with better results for end users of any organization.
Power industry mainly comprises of two sectors. Renewable and Non-Renewable sources together form the backbone of this industry. Both sectors have seen a major technological boon in terms of innovation as well as analysis. For both sectors, any reduction in cost or increase in efficiency directly influences a major gain in market in terms of usage. If the current effectiveness of any power source say solar energy is increased because of any new advancement in technology or adaptability of better manufacturing practices, then you will see a direct benefit in market share even within a year. That shows how much important efficiency is for this sector.
Power Industry and Big data
The number of IOT devices has increased in the current decade to a scale which was never thought of. With introduction of IOT devices the data gathering process has also seen an upward lift. Each smart sensor that you see on a machine collects data and store it on cloud or private server. The quantity of this data is huge and ever growing. This is where Big data comes into picture. Big data offers a way to store huge chunks of data and then provide solutions to analyze it for increase in overall efficiency. Let us try to understand why this data so important to store. Let us assume that any machine used in power industry is connected to various sensors that continuously monitors its performance on various parameters like friction resistance, speed, hours before breakage, etc. All these parameters are stored at a cloud along with data of similar machines used by same company or different companies. With advancement in technology it is possible to predict the major reasons behind bad performances of these heavy machines. This is done by observing a trend from various sources. Data from just one company or one outlet cannot be relied upon as it can be biased towards one parameter because of inefficiency of employees. Hence data needs to be collected from different sources and the volume of this will be extremely huge because of obvious reasons.
Challenges for Big data
With the knowledge of requirements of power industry and capacity of Big data, it can easily be understood that the road ahead is not easy. The constant need to improve and outperform itself is the key to success of big data in power industry which itself has created more challenges to meet the rising demand along with better efficiencies. Based on above observations, we can sum up the challenges discussed above in following points:
Data will keep on increasing with time. The data from previous years cannot be ignored because it will only reduce the efficiency of analysis. So, there is no way that the amount of data will become constant at any point of time. But this comes with challenge to innovate new methods to store and analyze data.
Going all cloud can never be a solution as it increases latency. But cloud is unavoidable as well because maintaining private server is very costly as well as unsecure.
Another challenge is to share this data. The sharing needs to efficient as well as fast because otherwise it won’t be useful. Suppose your analysis has found out that any particular machine is going to break looking at its trend then the same needs to be shared with the corresponding company so that proper steps can be taken.
With ever growing technologies, sources of data are only going to be diverse. IoT can also be taken over by some new technology which may prove to be better than this one. Then the transformation at Big data level needs to be done. The key is survival of the fittest. Hence Big data needs to grow at market advancement rate so that it can keep up with the raised standards.
Security is very important because companies involved in power sector are big time players of market and hence big data security should not be compromised even at the cost of low performance. So, the balance needs to be maintained between the two factors for business to grow smoothly in this sector.
To conclude, we all can agree that innovation has led to birth of this technology and only innovation can ensure its existence in coming years. Especially in power industry where demands are very high for better efficiency, the challenge is quite complex. But along with complexity, it opens up a new world of possibilities for big data to grow and provide better performing solutions. If it keeps on delivering on what it promises, then these challenges will only empower this industry to outshine itself among other players. But keeping security in mind is also very important because when such huge amount of data is dealt with, then any lapses in security can prove to be fatal for entire technology. Hence growing but keeping your roots solid should be the thumb rule for the future implementations.