Big Data Top Trends In 2016

We take our annual look at what we think the next 12 months will bring

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As we are coming towards the end of 2015 we have seen a considerable amount of change in big data and its perception. We believe that 2016 is going to throw even more up for the industry, so we are taking a look at what we think are going to be the top trends in the next 12 months.

Quantum Computing To Grow

The concept of quantum computing has been around for a long time, but has always been seen as something that we are going to see become a real possibility in some undefined future. However, 2016 may be when its use becomes more commonplace.

After recent work by Australian researchers at the University of NSW it has become possible to code the machines in a more cohesive and understandable way. They have managed to entangle a pair of qubits for the first time, allowing for more complex coding to be created and therefore the use of quantum computers to potentially become more widespread.

2016 will not see the use of quantum computing becoming common, but its presence within data will become far more pronounced and some of the more experimental and forward thinking tech giants may begin to use it more frequently.

AI & Machine Learning

As the IoT moves steadily along the Gartner Hype Cycle, one of its most powerful foundations is going to become increasingly important and companies are likely to adopt machine learning and AI within their own systems.

It will allow devices to automatically collect, store and analyze data, of which there will again be a huge increase in the next 12 months. Through the use of both AI and Machine learning, it becomes possible for these huge amounts of information to be processed, stored and mined without needing human interactions to do so. It creates the ultimate tool for modern data driven organizations and 2016 will see even more businesses realize this.

Improved Security Scrutiny

Data in 2015 has been in the media spotlight, but not for the ways that many would want. Unfortunately, the data hacks have become more common than many would have predicted, from the Ashley Madison hack to the TalkTalk hack, it has shown up that companies could do more to protect their data.

2016 will therefore see an increased scrutiny on how data is dealt with and protected. This will also come at a time when many countries around at the world are looking at implementing new data protection and data access laws, meaning that the waters are going to become increasingly muddied.

Within this, companies will need to increase their security spending, improve database safety and prepare for seismic changes in the way that hackers work. It is going to be a difficult year for data security, but it will build the foundation on which future stable and robust data security is created.

Big Data To Become Small

This is a two fold prediction.

Firstly the use of masses of data as an indicator of success will turn to the quality of the data being collected. This will mean that the variety for each company is likely to decrease, but the specific data that will be collected will become far more efficient, useful and plentiful. As companies realize that most of what they collect isn’t being used and just taking up storage space, this will become more apparent and the use of this data will come under increased scrutiny.

Secondly, the term big data is likely to become used more infrequently as a business function, instead this is likely to be broken down into the sum of its parts. Database management and data science technically fall under the same category at the moment, when the reality is that they are different. Companies are likely to realize this and use the term as a catch all rather than a function in itself.

Analytics To Be Simplified & Outsourced

We have seen the use of new data visualization and automation software breaking down the barriers between the data initiated and uninitiated. Through a continuation of this trend, we are going to see that conducting analysis on datasets become considerably simpler, we have already seen software that has a drag and drop analysis option available on tablets which is useable by almost anybody.

This comes not only from the needs of the untrained, but because we are still in the midst of a skills gap in the data scientist market, meaning that companies need to look at how they can leverage their data without necessarily having the skills in house to do so. Therefore we have these pieces of software that can do relatively simple analysis for companies, but for the more complex analysis needed we are likely to see this being outsourced to companies who have the expertise. This is likely to be a growth area in 2016 and we already have a number of companies leading the way in this regard.

Data In The Hands Of The Masses

Data is no longer just something being discussed in boardrooms and laboratories at the highest levels. Every day people get out of bed and look at the data collected on their sleep patterns,  investigate what they are spending money on through apps or even just looking at the possession and running stats from their favourite sports teams. Data is now everywhere in our society, which means that the general population is becoming increasingly clued up on using it.

It is not to say that the general population are going to suddenly become data scientists, but it means that the kind of data shared can become more complex as the understanding of it across a population increases. When discussing important matters, informed discussions can be had with data rather than conjecture. There will still be many who throw themselves at things with blind faith and gut instinct, but 2016 will see a growing segment of the population who can engage with matters through data in a way that they never could before, both through increased access and understanding of it. 

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