Big data is a term that is in a constant process of becoming more and more popular and important to all kinds of business sectors and industries in the last couple of years, especially in the Clinical Trials and Pharma, as any trials keeps close track of large amounts of data, in terms of results, documentation, etc. The term is used to describe a huge volume of data that is both structured and unstructured. Usually, such overflow of information is too large and becomes difficult to be processed by using traditional database and software techniques. Therefore, it equires new forms of integration in order to reveal voluminous amount of concealed values from a range of compex and diverse datasets. But why is it so crucial to business? The answer is simple. Big data enables different companies to reinforce, improve and develop even further their operations as well as functions – something that is crucial in the proper conduct of clinical trials. What is more, it also has the exponential capacity to help companies come up with faster, more efficient, intelligent and operative decisions that lead to more accurate analysis regarding a given question. This, of course, will contribute to the growth of the firm and its development.
In order to clarify even more the idea behind what big data actually is, let’s take petabytes (1,024 terabytes) or exabites (1,024 petabytes) as examples. The consistent information included in billions to trillions of files of people is extracted from a variety of sources. Such sources could be Web, sales, customer contact center, social media, mobile data and so on. Typically loosely structured, the recorded data amounts to endless records which are hard to be synthesized. But being able to synthesize and analyse the data you have is crucial in many ways.
In a research report from 2001, industry analyst Doug Laney who is currently with Gartner explained data growth challenges and opportunities as being three-dimensional. He determined the characteristics of big data through a perception of the three Vs: volume, velocity and variety.
Volume – There are many factors which add to the increasing quantity of data: unstructured information arriving from social media, transaction-based specifics, trial documentation preserved through years and many more. Yet, it is precisely the size of the data which defines its value and significance and which characterizes it as either big data or not.
Velocity – This refers to how fast the data is being produced and processed in order to not only meet the necessary requirements but also overcome a number of challenges so that there could be a positive outcome.
Variety – Nowadays data can be found in all types of formats. For instance, there is structured numeric data in traditional databases and unstructured presented as emails, videos, audios etc. Managing these varieties of information in a proper manner is hard to be done but is very crucial especially when companies seek progress.
Recently, 2 other characteristics of Big Data have emerged and are becoming more important every day.
Variability – In addition to the growing velocities of data, there appears to be a sort of inconsistency with periodic peaks. This might turn into an obstacle when it comes to managing and governing data effectively.
Complexity – Since data derives from multiple sources, its management becomes very tricky. Thus, such rich flow of information needs to be linked, matched, joined and correlated across systems so that it can be easy to comprehend at the end.
In 2015 people are required to carefully watch out and calculate each and every step of the analytics process, thus establishing what data is available, how it can be used, how it should be regulated, how it should be connected, how it should be stored and, finally, how it should be analyzed. The massive and continuous gathering of data throughout the time brings on intriguing trends which we should be looking out for. Datafication might not be a new trend but is accelerating now and is metamorphosing into an even more efficient real-time operational analytics system. In other words, datafication is when technology unveils previously hidden processes. When this happens, such processes can be tracked and optimized. Multipolar Analytics enables data to be collected and analyzed in multiple places, in relation to the required sort of data and analysis. Finally, the latest analytics technologies clear the path for the so called fluid analytics which can keep up more easily with the shifting needs of one organization and can manage more effectively the analytics lifecycle. All of these can be vital in improving the decision-making in any clinical trial orientated organisation and are sure to gain popularity.
In conclusion, Big Data is becoming more and more relevant in all industries, especially clinical trials and research, as its proper management can be extremely beneficial, cost-reducing and healthy for any organisation.
Our team at Astra Nova is now working on creating trainings on all of these characteristics on Big Data, in order to be able to help you keep up with all the useful trends and keep your company top level. Follow us here – https://crotraining.co.uk/blog/ or contact us for more information: +44 208 123 3324 (info@astranovatraining.co.uk)
Photos credit: http://www.forbes.com/sites/emc/2014/02/27/how-nasa-answers-big-questions-with-big-data/
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