In an increasingly competitive economy and marketplace, companies and organisations are increasingly looking at Big Data in order to work smarter and improve their goods and services.
Analytics and data science help with the understanding of complex behaviours and trends, giving insight that can help companies to make smarter business decisions. For example, Netflix uses data mining to analyse movie viewing patterns to understand what drives user interest and to thus inform what kind of series Netflix should produce to respond to viewers’ interests.
Analytics focuses mostly on the movement and interpretation of data, typically with a focus on past or present trends and behaviours. Data Science then moves towards summarising this data so that it can be used to provide forecasting, or an insight into future trends and behaviours based on the patterns identified from past and current data. Data visualisation skills using tools such as Tableau are central to Analytics, whilst machine learning is more central to data science. Knowledge of programming languages such as Python, R and Java are crucial in both fields. This useful article explains the differences between analytics and data science and the different skills required in each discipline.
Data science and analytics have risen in popularity rapidly as a career option over the past ten years. The analytical, problem-solving and data interpretation skills of postgraduate researchers from quantitative disciplines are in high demand in the sector. Data scientists also act as consultants, guiding client businesses on how to act on their findings, meaning communication skills and the ability to convey complex information and concepts to non-expert users are also crucial skills. Opportunities for this kind of work including working ‘in-house’ for a private sector company (web-based retailers like ASOS, Expedia and Amazon are common recruiters of data scientists) or working for a consultancy firm on projects for different client companies. Consulting firms with specialisms in Analytics and Data Consulting include BCG and Faculty. Opportunities outside the private sector include research institutes like the Alan Turing Institute and the Government Operational Research Service.
The rise of Data Science has seen an increasing number of data science ‘boot camps’ promising opportunities to train in the area and access opportunities, but many of these carry a charge. One example is the Pivigo S2DS programme: which focuses on training you in the commercial awareness side of data science. See links below for free courses. ASI data science offer a fellowship for top PhD graduates to train as data scientists.
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