It’s been more than a decade since the phrase Big Data exploded into business news magazines and websites, with forecasters predicting that user data collected from computers, smartphones, IoT and other devices would drastically change business as well as everyday life. Processing and understanding all that information required advanced data skill sets, which in turn necessitated new and expanded university programs focused on data processing and analysis and the emerging code languages surrounding it, such as R, Python, and SQL. Fast forward several years and today companies across nearly every industry are seeking to capitalize on data to improve their sales, services, products, supply chain, digital marketing, and more. As a result, master’s programs related to Business Analytics, Data Science, Information Systems and industry-specific analytics like Marketing Analytics and Fintech are some of the most in-demand programs for MS applicants.
Companies with obvious data pipelines, such as e-commerce websites and search engines, were some of the earliest adopters to benefit from huge sets of user data. Perhaps the most well-known examples are Amazon’s many innovations that have been informed by user data, including product recommendations, dynamic pricing, and sales page design. However, fewer people know that Amazon also uses data to improve its operations, such as reducing shipping time and cost by selecting the warehouse closest to the customer, frequently saving 10-40% on shipping. Today, many diverse industries and companies are also harnessing data and competing to hire professionals with data skills. Coca-Cola has surprised some people by using data to inform its product development in recent years. One specific example was the decision to launch Cherry Sprite as a new flavor, which was influenced by user data from the brand’s self-serve soda fountains in hundreds of restaurants.
Which industries are driving demand for data analysis?
It’s not just the world’s biggest tech companies that are making innovations and creating jobs. In the healthcare industry, quality of treatment, error prevention, improved diagnosis, and preventative care are just some of the areas benefiting from better data analysis. Here in Taiwan, the world’s most competitive scooter sharing economy relies heavily on data to understand rider behavior, traffic status, road safety conditions, and where riders borrow and return scooters.
According to Career Foundry, which offers courses in data analysis and UX/UI, the top five industries hiring data analysts as of December 2021 were:
- Business Intelligence – “BI combines data gathering, data storage, knowledge management, and data analysis to evaluate and transform big data into actionable insights that can be used to inform business strategies, operational optimizations, and other important decision-making.”
- Finance – “Finance companies like investment banks, venture capital firms, and consumer banks use data analytics to conduct risk assessments, inform investment decisions, spot trends, and make predictions.”
- Sharing Economy – “Data is used in sharing economy services to sort tasks for workers, set prices, grow their user base, drive advertising, catalog data, and recommend services.”
- Healthcare – “Data in this context can drive insights on systemic wastes of resources, track practitioner performance, determine drug makeups, sort clinical data, identify diseases present in images, analyze patient behavior, and much more.”
- Entertainment – “Streaming services are taking over this market and they’re using big data to drive that growth.”
Looking beyond this list, a quick search revealed clear demand in wide-ranging industries, including railways, pharmaceuticals, and higher education.
What kinds of jobs does this demand create?
As data analysis matures, more clearly-defined job titles and roles are emerging. Here’s a list of some of the most common data-related roles and what they actually do.
- Data Analyst – Gathers and organizes large sets of data, analyzing that data and reporting insights and findings to inform decision making on product pricing, cost management, manufacturing efficiency or thousands of other aspects of a business.
- Data Scientist – Creates the framework for analysis by implementing statistical models and algorithms, running tests and experiments, developing data products, and continually optimizing for better analyses.
- Business Intelligence Analyst – Evaluates and transforms data to improve an organization by identifying trends, patterns, or potential issues and then translating the analysis to inform strategy, operational optimization, and other important decision making.
- Financial Analyst – Conducts risk assessments, informs investment decisions, monitors trends, and makes predictions, often by creating algorithm-based fraud protection systems or custom-built customer databases.
- Logistics Analyst – Responsible for using data to optimize supply chain processes to identify inefficiencies within the supply chain and develop cost-saving solutions to make production, distribution, and delivery more efficient.
- Data Architect – Designs the structures an organization needs to acquire, organize, analyze, manage, and utilize data, including translating business objectives into a data management framework, defining how data will flow through the framework, and working with other teams to implement it across the organization.
- Business Systems Analyst – Analyzes and leverages data to improve systems and processes – particularly within information technology (IT) – by analyzing the company’s current systems and identifying ways to optimize systems, cut costs, and make IT more effective.
- Marketing Analyst – Helps companies better understand their customers and market by analyzing data related to a company’s target demographic and developing strategies to help connect with new customers and market more effectively to their existing customers.
[Conclusion]
Data analysis has moved from being a trend into being an essential aspect of business evaluation and strategy. Companies that have achieved some level of data competency are hungry to improve on what they have, and many companies and industries are still only beginning to implement these practices, meaning the potential for this job market appears to have room for growth in the years to come. If you’re considering a career in data analysis and want to better understand school selection, the skills you will need, or how Transcend Admissions can assist you in the application process to a related graduate program, click here to sign up for a free 20-minute consultation with one of our professional consultants.