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What does the future of data science look like?

The data science sector can provide a myriad of career opportunities for skilled, savvy professionals with an interest in data and analytics. This profession can often be determined by technology and trends, making for a dynamic, rapidly-developing industry that is growing at an unprecedented rate. We don’t see the market slowing down for data science jobs any time soon, and the following predictions on the state of the industry should only further stimulate interest in this field. Here’s what’s expected for data science in the near future:

Artificial intelligence takes hold

Artificial Intelligence (AI) has been a buzzword in many technical and non-technical industries for the past few years, and it’s making waves in the data science industry due to its ability to improve efficiency and provide new insights from existing sets of data.

Data science professionals who have struggled with the idea of completing monotonous repetitive tasks will welcome the introduction of AI to automate these processes using simple algorithms. High-volume repetitive tasks can be transformed thanks to AI’s ability to do things like clustering, which can help to predict consumer behaviour and tailor suggestions to other consumers accordingly. Reasoning, learning, planning and natural language processing can all be employed by AI to do everything from quickly learning more about large groups of data through to building and sending automated messages.

As most AI processes require a significant volume of data to train and hone, the use of such technology within data science will continue to evolve as the industry does.

Security gets stronger

Every year sees significant data breaches across major international firms, and 2016 was no exception. According to the Data Breach QuickView report, 4,149 data breaches exposed more than 4.3 billion records last year. No industry is immune to data loss, but such breaches can not only lead to financial loss, but also, reputational damage and security issues. And while some attacks are unavoidable, the Online Trust Alliance reports that more than 90% of cyber incidents could have been prevented. This suggests data security will continue to step up over the coming years, with response and recovery becoming an increasingly important component of any data security programme. With many organisations hesitant to invest heavily in cloud computing due to perceived issues surrounding data security, awareness will need to be increased on the safety of cloud computing and the treatment of user data. Identity management, access control, data leakage and virtual machine protection will continue to be security issues organisations will need to assure consumers of in order to build trust and confidence.

Machine learning shapes up

Machine learning has traditionally been used in complex problems that would otherwise be handled by humans. Machine learning is when AI acquires self-learning capabilities, using example and experience data to predict or describe. Machine learning has been time-consuming and expensive in the past, however with new applications leveraging Big Data, new versions of machine learning will work more effectively to understand the context of newly streamed data, therefore ‘learning’ more quickly. As more organisations make better use of Big Data and investigation into machine learning continues, expect to see static and dynamic data used to improve performance. AI and machine learning will combine to deliver systems that not only understand, but also learn, predict and adapt, potentially even working autonomously.

Are you interested in data science?

The above trends are just a few of the developments we can expect to see in Big Data over the coming years. As the industry continues to advance and demand for skilled professionals grows, there will be plenty of opportunity for you to make your mark. Take a look at our latest data science jobs here.

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