The business analytics market size was valued at USD 81.46 billion in the previous year and is expected to reach USD 130.95 billion in the next five years, registering a CAGR of 8.07% according to a report published by Mordor Intelligence. The growth in the data science market is deeply entangled with this which is estimated at USD 10.15 billion in 2024 and is expected to reach USD 29.98 billion by 2029, growing at a CAGR of 23.5% until 2029. The growing adoption of advanced technologies for the purpose of data collection and analytics across business sectors has fuelled the demand for skilled manpower in the areas of business analytics and data science. The US Bureau of Labor Statistics has recently reported a 16 percent growth in jobs related to data science alone which stands testimony to Harvard Business Review’s claim of it being the “sexiest job of the 21st century” more than eight years ago.
"The ability to take data – to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it – that’s going to be a hugely important skill in the next decades." - Hal Varian, Chief Economist, Google.
Aspiring professionals who undertake data science programs become well-equipped in analytical strategies and can provide improved business intelligence considering the dynamically changing market scenario.
Here, the knowledge about the various prospects for building a career on data science and business analytics is critical to determine the scope for individual growth according to areas of interest.
ML Engineering
The role of an ML Engineer is that of a specialist, the market for which is in a growth phase. The work of an ML engineer is to collaborate with the data science department of the organization and provide support in the creation of algorithms and various other data-driven products. These Ml algorithms and products enable technology systems to make automated decisions and amplify user experience with zero human interference. Tech giants like Apple, Microsoft, Accenture, and a few others have been successfully offering various advanced data-based services and ML skills are a growing need for them right now.
To give an example, the Massachusetts Institute of Technology’s (MIT) introductory Deep Learning course provides candidates with a strong foundation of deep learning principles and methodologies. The program emphasizes hands-on projects and industry applications. It is one of the valuable courses for those looking to delve into the depths of neural networks.
Data Architecture
The role of a data architect is functional in managing large-scale electronic databases for organizations. It requires the expertise and implementation of an extended number of programming tools in order to secure the data frameworks. The kinds of data that an architect works on are financial records, marketing information, and other valuable information related to the organization. A data architect executes highly technical tasks that include ensuring the relevance of all secured data and its accuracy. It must be an accurate structure and should be accessible to all the required departments. Sophisticated design skills, an eye for detail, and advanced analytical skills are required in a data architect to fulfill the requirements of big organizations.
In this regard, Carnegie Mellon's School of Computer Science offers programs on data management and storage systems that address the fundamental principles of data architecture. Students can avail education on database design, distributed systems, and data modeling.
Application Architecture
In the dynamically changing world of technology, application architects must be equipped with excellent technical visions that can be insightful in software development and advanced analytical skills in order to execute problem-solving operations with critical thinking skills. In this regard, knowledge about business analytics plays a major role in addition to programming language expertise. Only with the combination of both skills can a person deliver accurate performance in this department. With the usage of advanced data analytics procedures and programming language experience, an individual will be able to handle the role of an application architect for businesses.
To give an example, Oxford University provides courses on software engineering and architecture, covering topics such as architectural patterns and design principles. Students can engage in projects that apply the concepts to real-world scenarios as the program puts emphasis on critical thinking and problem-solving skills. They are encouraged to analyze challenges, evaluate alternative solutions, and make informed decisions in the design and development of new-age software systems.
Data Analysis
Individuals working as data analysts must have strong knowledge of mathematics should be highly analytical, and should be inquisitive in nature. Every business has the requirement for data that gets generated from transportation, market research, logistics, and sales. Here, the duty of a data analyst will be to secure all actionable data and evaluate them in order to provide valued reports on the improvement of business strategies and drive better business decisions.
In this regard, ETH Zurich provides courses in data analysis and visualization that integrate theoretical foundations with practical implementations. Through this course, students are able to engage in projects that involve analyzing real-world datasets and deriving insights.
As business operations grow more on a global scale, opportunities for business analysts and data scientists also continue to grow internationally. These skills are becoming integral parts of organizations and are creating global career prospects for all aspirants.
