A future career in analytics What is a career in analytics about? In the information age in which we live, almost all of us consume and produce digital data, either for business, community or private uses. We access data, we manipulate it, we store it and we create more and more of it. The field of analytics provides the expertise to navigate and make sense of this ever-increasing sea of information. Analytics focuses on the linkages between mathematics, statistics and computing. Data is analysed over a wide range of contexts using statistical, mathematical and computational techniques. However analytics goes beyond simple analysis and computation; its primary goal is to enable business decisions based on appropriate data. Accordingly, we have seen the rapid rise of organisational structures and career fields such as business intelligence and business analytics. Are you a problem solver? Do you like puzzles and games involving logical thinking, and working with people to help solve their problems? Are you generally curious and driven toward making an impact through your work? Then analytics could be a great career choice for you. Outlook and trends Those considering careers in analytics can explore the following growth areas: 1. Data visualisation allows businesses to ask interactive questions of their prepared data sets and get immediate, engaging visual responses. 2. Increasing importance of mobile data enables companies to define useful mobile metrics, understand mobile technology and the data creation process, and collect and analyse mobile data. 3. Cloud-based analytics platforms such as Amazon Web Services and Microsoft Azure allow businesses to save on infrastructure design, set up and management costs, to focus on key issues and to gain business insights. 4. Growth of predictive analytics it has become essential for businesses to predict and anticipate trends, in order to make proactive decisions and better shape their outcomes. 5. Wearable computing revolution as more people start using wearable technologies such as Google Glass and smart watches, companies can increasingly monetize the data collected through these devices. Source: http://tdwi.org/articles/2014/01/28/5-data-analytics-trends-2014.aspx
Big data Big data is hot! McKinsey Global Institute s report on big data predicts by 2018 there will be a shortage of 1.5 million analysts/managers who can make data-driven decisions and 140,000-190,000 positions open for data scientists. What are the differences between these two roles? Data scientists need advanced analytics skills in statistics, computational mathematics or predictive analytics. They spend more time on computer algorithms, working with data, software and systems, rather than working with people. Business analysts/managers need a basic understanding of analytical techniques but spend more time interfacing with people than computers. They often work on broader business questions that can be solved using simpler analytics techniques. Source: http://www.sas.com/en_us/insights/articles/analytics/amplify-your-data-career-withanalytics.html Work settings Work opportunities can be found in a wide array of sectors and industries in New Zealand, including financial and business management, engineering and industrial, building and construction, government departments and agencies, and research and education. Analytics qualifications tend to be gained through mathematical sciences or computer information sciences pathways. Although there is not necessarily a fixed delineation, career options tend to vary depending on the pathway. A mathematical science pathway is more likely to lead to roles that are focused on analysing data, drawing conclusions, providing feedback to clients/stakeholders, and proposing solutions and recommendations. A computer information science qualification will more likely result in roles centred on gathering, manipulating, processing and storing data, as well as managing IT strategy, security, system management and database design. In large organisations there are opportunities for considerable advancement. In the past, graduates started in a technical role and worked up to management. Now it is possible to enter graduate programmes and then advance to senior or management positions. The big financial services firms provide excellent opportunities. For example, KPMG in New Zealand has a data analytics team providing services for clients such as identification of fraud, waste or abuse, assessment and enhancement of financial and data models, spend analysis, data migration planning and revenue leakage analysis.
Career role examples Data Insights Analyst An insights role with a core statistical and analytic focus. Works mainly in SQL and Excel, but also with exposure to a range of other tools including R and SPSS. Works directly with the marketing, IT and business intelligence teams and presents to a variety of stakeholders on a regular basis. Prepares a variety of ad hoc reports on a regular basis. Implementation Analyst Supports data synchronisation service line, supporting existing users and implementing the system with future clients. Involves the support and roll out of additional service lines. Performs data analysis, prepares reports and carries out training and general coordination activities as required. IT Graduate Business Analyst Supports reporting and analytics functions, and contributes to the ongoing improvement of business processes in the organisation. Determines appropriate solutions that meet end users specific requirements, while also ensuring the security and integrity of business data and engaging in other change projects as required. Supply Chain Analyst Develops and tests plans to ensure product availability while utilising the most cost effective methods. Undertakes data mining, analysis and data manipulation to assess current operational situations and propose new strategies and methods. Carries out troubleshooting and contributes to the completion of organisational projects and goals. Range of skills and knowledge People and communication skills Exceptional interpersonal skills for cross-team collaboration. Communicate with personnel at all levels and provide exceptional customer service. Understand the gaps in a business and use this knowledge as a guide to manipulate data, derive useful insights, and make recommendations. Strong presentation skills and able to talk 'business' from technical reports. Analysis and problem solving skills Apply sophisticated predictive modelling and quantitative and statistical analysis Technical and software knowledge
Statistics, algorithms, quantitative methods, data mining, predictive analytics, data reporting, logistic regression and decision trees Database applications including mining, data import, table creation, query creation and macros SAS (Statistical Analysis System), SAP, SQL, SPSS, Angoss, R and Excel. Personal qualities Personable and intelligent and comfortable being in a client-facing role Able to rapidly adopt and adapt to working with new technology/platforms Logical, analytical and methodical Quick to learn new tasks Highly accurate with a knack for knowing when to drill down to detail Motivated, proactive and able to manage time to meet deadlines Salaries Salaries vary substantially depending on experience and the type of industry. Graduates: start around $50,000. Intermediate to senior roles (3 5 years experience): $70,000 $100,000. Salary range is indicative of the New Zealand job market at the time of publication and should only be used as a guideline. Professional registration This is not a requirement but membership of professional bodies and associations can be of huge benefit for professional and career development. Relevant local organisations include the Institute of IT Professionals (IITP) NZ, the New Zealand Analytics Forum and the New Zealand Statistical Association. The AUT advantage AUT graduates benefit from a stronger emphasis on practical skills, producing graduates who, in their third year, have had the experience of working on a range of computing or analytical projects with companies such as Fisher & Paykel Healthcare, Eagle Technology and FutureTech.
Further study options Further study in mathematical sciences is available at postgraduate level, including the Bachelor of Science (Honours), Postgraduate Certificate in Science, Postgraduate Diploma in Science, Master of Analytics, Master of Health Informatics, Master of Science, Master of Philosophy, and Doctor of Philosophy. Useful websites NZ Mathematical Society http://nzmathsoc.org.nz Statistics New Zealand www.stats.govt.nz Analytics Section of INFORMS https://www.informs.org/community/analytics American Society of Quality Statistics Division http://asq.org/statistics/ Graduate profile Catherine Mansell Sales Analyst, NZME (New Zealand Media and Entertainment) Bachelor of Mathematical Sciences in Analytics and Astronomy I originally chose to do a maths degree for the astronomy major but was really inspired by a lecturer in my second year and decided to do the analytics major as well. By the time I was halfway through the major, I knew I wanted to solely do analytics for my career. Being able to convert "messy" data into something people understand using programming tools and Excel is really interesting to me. In this role I am responsible for analysing the sales and supply of commercial newspapers. This includes forecasting, automatic supply using SQL scripts and analysing subscription and retail sales. I love getting to do what I enjoy every day. I love making a positive impact to the overall business and seeing how the changes I make using data, help to make other peoples jobs easier.
For the future, I plan to stay with NZME and to continue learning and growing my knowledge of analytics. Longer term, I would really like to work for a company who develops statistical tools such as SAS or perhaps work on analysing for a large international company. Employer comment Andrew Niven Commercial Manager, NZME Auckland Beyond the technical skills expected of appropriate graduates, we look for genuine enthusiasm for the job someone who is willing to learn, will fit well with the existing team and can solve problems by adapting existing tools to new uses. In her interview, Catherine was really passionate about analysis and statistics. Her enthusiasm was infectious and we could see straight away she would fit well in our team. The newspaper industry has changed a lot in the last 20 years. As we move increasingly onto digital and mobile platforms, there is a lot more data to make sense of and use in the development of the business. Consequently, there is a rapidly growing need for people with data analytics skills and expertise.