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As organisations and SMEs become increasingly data-driven, there arises the need to make sense of all that data and convert it into meaningful insights. In a competitive environment, analytics becomes the driving force that facilitates decision making \u2013 to leverage the insight for innovative strategies as well as for an effective ROI on investment. Industries and departmentsare today unleashing the value of analytics in almost every domain (retail, production, HR,and so on) that calls for some degree domain knowledge. You will find analytics helping police departments reduce crime, credit card companies detect fraud, or facilitate selections during IPCL cricket auctions.<\/span><\/p>\n However, the issues faced by organisations or departments, are diverse. Which gives rise to questions like:<\/span><\/p>\n How can Analytics solutions for marketing and HR departments within the same organisation be delivered by similar analytic models?<\/span><\/i><\/p>\n Isn\u2019t the need of a financial service firm different from that of a chain of bakery outlets?<\/span><\/i><\/p>\n \u00a0Can the skill levels of analytics professionals serving within different departments of a large organisation be the same?<\/span><\/i><\/p>\n What is meant by \u2018anlaytics roles\u2019?<\/span><\/i><\/p>\n With data becoming\u00a0more easily accessible for different departments or industries, analytics functions have also become distributed and non-centralized. So the needs, role-playing, IT support, volume of data, tools and software applied are also diverse \u2013 together defining the role of an analyst.<\/span><\/p>\n While different hats are worn to tackle different \u00a0job roles in analytics (Human Resource analytics, Web analytics, Compensation analytics, and so on), some of the analytics functions may have areas that overlap \u2013 as in Compensation, HR, Marketing and Performance Analytics. All of these four analytics roles look into the workforce, analysing various metrics for compensating and retaining the best workers, offering incentives and benchmarking performance for bonuses. This is a mere example of how analytics roles are not always stand-alone, but distributed.<\/span><\/p>\n Niche or Specialised Analytics<\/span><\/b><\/p>\n The very diverse range of analytics functions mentioned above, that necessitate working with customised database management systems or suitable software, towrds differing goals and applications of insights, define the function of analytics. Each niche domain calls for specialised skills in analytics. So analytics applied in marketing is Marketing Analytics, while analytics used to drive profits in retail operations is Retail Analytics and analytics used for reviewing cost-effectiveness of salary plans is Compensation Analytics \u2013 collectively known as horizontal solutions in analytics. These are also the analytic roles, that cater to niche domain or specialised analytics.<\/span><\/p>\n An Overview of niche Analytics or specialised Analytics roles<\/span><\/b><\/p>\n In the light of the Indian Analytics industry shifting towards a trend of start-ups specializing in niche analytics roles with global giants looking to India for tie-ups<\/a>, we have started an exclusive IVY spotlight series. Each week, you can access information of varied and emerging analytics roles, which give you an overview of analytics specialised in niche segments of industries and functions. <\/span><\/p>\n As a student, you are trained on analytics in totality. Knowledge of various horizontal solutions in analytics \/ analytics roles give you that leg up needed during interviews or lateral shifts across departments or companies, or for that matter chalk out your career path.<\/span><\/p>\n Compensation Analytics<\/a><\/span><\/p>\n The science of scrutinising compensation data with a view to forecast, model and detect patterns; with the ultimate goal of designing methods for optimising the ratio between performance and compensation<\/span><\/i> and making suggestions thereon<\/i>. Read More \u2026<\/a><\/span><\/p>\n Marketing Analytics<\/a><\/span><\/p>\n The technique of measuring and analysing sales data, marketing programmes, customer data, queries and leads together with location information, demographics, market potential and competition, for maximum effectiveness of marketing models and an optimal return on investment (ROI).\u00a0 <\/span><\/i>Read more \u2026.<\/a><\/span><\/p>\n Fraud Analytics<\/a> <\/span><\/p>\n An integrated methodology that uses statistical methods, techniques of analysis and data mining, with sophisticated tools or dedicated software; for continuous monitoring, investigation, detection and prevention of fraudulent transactions. <\/span><\/i>Read more \u2026<\/a><\/span><\/p>\n Retail Analytics<\/a><\/span><\/p>\n The explosive market growth in the retail sector is fraught\u00a0with a cutting edge environment where footfalls \/sales per square foot hold sway as much as retaining customer loyalty. It is only the savvy retailer who sifts through terabytes of data for analysis, to cater to consumer requirements, who remains a step ahead. This employment of various mechanisms of analytics to create efficiencies, retailer profits, best services and enhanced consumer experience, is retail analytics<\/span><\/i>. Read more \u2026.<\/a><\/span><\/p>\n Updated 23\/2\/14<\/span><\/strong><\/p>\n \u00a0<\/span><\/i>HR (Human Resource) Analytics<\/a>\u00a0 <\/span><\/p>\n From Gartner<\/a>, \u201cWorkforce analytics is an advanced set of data analysis tools and metrics for comprehensive workforce performance measurement and improvement. It analyzes recruitment, staffing, training and development, personnel, and compensation and benefits, as well as standard ratios that consist of time to fill, cost per hire, accession rate, retention rate, add rate, replacement rate, time to start and offer acceptance rate\u201d.<\/i><\/span><\/p>\n Updated 14\/2\/14<\/strong><\/p>\n Business Analytics<\/a><\/p>\n Business analytics<\/strong>\u00a0is comprised of solutions used to build analysis models and simulations to create scenarios, understand realities and predict future states. Business analytics includes data mining, predictive analytics, applied analytics and statistics, and is delivered as an application suitable for a business user. These analytics solutions often come with prebuilt industry content that is targeted at an industry business process, for example, claims, underwriting or a specific regulatory requirement.<\/em> (\u00a0Gartner<\/a>)<\/p>\n Healthcare Analytics<\/a><\/p>\n Healthcare analytics or health analytics is the application of analytics and modelling to gain insights into the massive and complex data; unlock and apply such insights to drive clinical and operational improvements. This includes traditional transaction monitoring together with embedded real-time predictive analytics models to enable organisations to create dynamic and personalised healthcare, fraud detection and predict patient behavior for a business edge.<\/em><\/p>\n Social Media Analytics<\/a><\/p>\n Social Media Analytics or Social Analytics is the technique applied to collection of unstructured data from social media sites and blogs and evaluating such data for business decisions, in a real-time environment to develop an in-depth idea of the social consumer, to apply such insights for business decisions.<\/i><\/p>\n