We live in a data-driven world, where the volume of information and data at our exposal is growing exponentially and will continue to do so. Data is involved in almost every interaction with technology: e-commerce purchases, Facebook feeds, Amazon Prime recommendations, and even the facial recognition needed to log into our smartphones. Data science is widely being used by computer professionals with the skills to collect, shape, store, manage, and analyze data as a critical resource for enabling organizations to make data-driven decisions. Nearly every industry today, from research institutes to dating applications, requires data science professionals. Data science and Big data are, in fact, the need of the hour for the success and improved customer service of millions of organizations and government agencies.
One of the most trending courses, Data Science, is a bridge connecting us to the world of automation. It has spread its wings far and wide and is today applied in all organizations ranging from the top MNCs to start-ups and unicorns. This domain of study encompasses and teaches how to deal with vast volumes of unorganized data to derive meaningful information. Pursuing an MBA in data science is expected to acquaint you with analytics, data mining, machine learning, automation, etc., equipping you with handling heterogeneous data sets. A variety of courses falling under the ambit of data science roles, such as artificial learning, statistics, data engineering, etc., combined with real-world projects and classroom activities, has slowly turned into one of the most sought-after career choices for future aspirants.
A career in data science is in high demand, and this trend will likely continue. Crunching big data for businesses involves rigorous analysis through various tools. If Google Maps, Robots, Chatbots, and Tesla’s self-driving cars spark interest, then choosing a career in data science is the right thing. A data scientist engulfs computational skills and helps set up business models by identifying problems and resolving them through intensive data-driven insights.
As data becomes increasingly ubiquitous, the need for experts handling it for transformative usage has escalated. Millions of gigabytes of data are generated every day, just waiting to be put to better use for the benefit of the organization using it as well as society at large. This is enough to highlight the importance of making a career in data science and the umpteen prospects it offers. Businesses are increasingly looking for professionals skilled at creating, managing, and using informational data sets for drawing meaningful conclusions, thereby helping companies gain an upper edge and maintain competitive advantage.
A fruitful career in data science has tremendous opportunities, and apart from the perks, the industry offers high salaries. And as with most in-demand jobs, the salaries are competitive amongst organizations to get their hands on the best pool of candidates. Candidates can expect to make six-figure salaries if they are serious about their careers and choose them wisely.
Data Scientist has also been ranked among the most promising career choice by LinkedIn*. Down the line, data science roles will enjoy a comfortable position with high-earning income capacities. Moving towards automation and digitization, trends and analysis reveal that the requirement for skilled labor will soar. The primary reason for the heightened demand for data scientists is that every company wants to earn profits today. As data plays a vital role in every industry, data scientists derive information from this data to maximize profits, increasing the profession’s popularity. As a result, jobs in data science are one of the fastest growing today. According to the US Bureau of Labor Statistics, they are expected to increase by 27.9% in 2026*. The fact that companies that use data for their decision-making are seen to be more profitable and productive than their peers is also significant for all those who wish to pursue a career in data science.
The role of a data scientist does not end here; the scope is ceaseless. Once you have the proper knowledge garnered through courses from a reputed college, you become eligible for several data science roles. These include Machine Learning Engineer, Applications Architect, Data Scientist, Enterprise Architect, Business Intelligence Developer, Statistician, Functional Consultant, Product Analyst, etc.
The opportunities and pay scale that come along the data scientist career path are no less. You not only have a challenging environment to work in, but also no boundaries exist when applying your skills in any industry. A bright future full of seamless opportunities awaits students who want to pursue data science roles and master the art of playing with data. Both nationally and internationally, there is an abundance of jobs that require the skills and expertise of data scientists. These well-paid jobs offer job security that will only multiply in the future.
An MBA in Data Science is designed around a curriculum emphasizing all the data management and analytical tools that can apply across varied disciplines such as healthcare, finance, hospitality, retail, banking, etc. An MBA in data science usually is a full-time course spanning one to two years. It may also include internships, dissertations, industry visits, hands-on training in analytics laboratories, live case studies, and professional certifications, among many other valuable experiences. It involves studying big data, data mining, database management, data science, and data warehousing.
Data science is a multidisciplinary field involving different concepts in its learning path. The data science course syllabus typically includes concepts around machine learning, Python/R programming, data interpretation, data science lifecycle, statistics, decision trees, linear and logistic regression, data visualization, recommendation engines, and more. It also covers a complete overview of widely used data science tools like Tableau, TensorFlow, SciPy, and QlikView.
Data science is a 21st-century job skill that millennials should have. Moreover, students with a background in data science learn a much more robust skill set in whatever career they choose.
Big data: Data can be very large or complex, which can’t be managed with traditional data processing software alone. This is the primary reason why data scientists must keep themselves abreast with Apache Hadoop or Apache Spark, an open-sourced distributed processing system.
Data modeling: This involves formatting specific data into a database.
Data visualization is the graphic representation of data that reveals useful trends and insights.
Machine learning constitutes a series of techniques used to predict and forecast data.
Programming: It is important to know programming languages such as Python and R if you desire to automate data manipulation.
Statistics: It is equally important to know some form of applied statistics to interpret data.
Teamwork: Data scientists don’t work in silos; they are often part of more extensive data science teams composed of data engineers, software developers, and others.
In a world full of uncertainty, data is more critical than ever. As businesses continue to change, they’re looking for people with data science and analytical skills to help them optimize their resources and make data-driven decisions. If you enjoy complexity and ambiguity, like delving into a single question, and are okay with not finding an answer to a problem, you might be a good fit for a career in data science.
MicroStrategy research reveals that companies worldwide use data to make processes and costs more efficient, drive strategy and change, and monitor and improve financial performance. Therefore, 71% of global companies expect their investment in analytics to accelerate over the next few years. Therefore, a career in data science counts as a wise choice.
The data science roles require a mix of experience, know-how, and correct tools and technologies. It is a good career choice for both new and experienced professionals alike. Aspiring professionals from any educational background who possess an analytical frame of mind are best suited to pursue data science programs, including, but not limited to:
There are several ways you can brace yourself to take on some demanding yet attractive tasks if you want to enter the field of data science. Prestige University offers master’s degree programs in data science and data analytics that are created to help students gain the skills that businesses are actively seeking. The program offers students a lucrative opportunity to participate in co-ops and experiential learning opportunities, allowing them to gain practical experience before they graduate. It aims to accelerate your career in data science by providing you with the world-class training and skills required to succeed in this field.
You can become a data scientist by diving deep into the nuances of data interpretation, mastering technologies like machine learning, and mastering powerful programming skills to take your career in data science to the next level. Participants of the program get to develop a foundation for advanced understanding of these areas using hands-on training using in-demand tools and techniques, case studies, and capstone projects.
The data science program by Prestige University helps you gain the knowledge you need to turn your future organization’s data into a tactical asset to generate business value. It covers the in-demand concepts around data science, such as statistical analysis, data visualization, predictive analytics, prescriptive analytics, machine learning, neural networks, and more. It is aimed at helping you make data-driven strategic decisions for your organization to enable business growth and stay ahead of peers. Besides, the course also helps develop a data mindset and the analytical skills to interpret and communicate data to solve business problems. Students can leverage this data science course to demystify data analysis and equip themselves with the required skills for strategic decision-making.
This data science program includes 10+ industry-relevant projects from various domains to help you master data science concepts. These projects encompass all the critical aspects of data extraction, cleaning, mining, and visualization to build and tune data models.