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Data Science is an inter-disciplinary field, which deals with algorithms, processes, systems and is used to extract insights from huge amounts of data and improve understanding. Data mined can be in any form – structured or unstructured. Data Science utilizes numerous theories and techniques that are part of other fields such as Mathematics, Statistics, Computer Science, Information Science, and Chemometrics.
The Rise of Data Science
The emergence of Data Science has been primarily due to the burgeoning growth of data. For instance, today an estimated 2.5 quintillion bytes of data is created daily. Over time, businesses have not only understood the importance of data, storing the data but also analyzing it that impacts key business decisions gaining a competitive edge and improving customer experience.
Data Science has gradually become a vital engine of various sectors including Risk Management, Fraud Detection, Marketing Optimization, Marketing Analytics and others. Presently, Data Science has far-reaching implications in various streams, both academic as well as applied research fields such as speech recognition, digital economy, machine translation on the one side with areas such as medical informatics, healthcare, social science on the other side.
It’s gradually becoming apparent that the value lies solely in cleaning, processing and analysing the humongous data, and this is exactly where the role of a data scientist becomes so important. We have heard that Data science is a sexy industry but many people are not very clear about the value that a data scientist can bring to an organisation.
Role & Responsibility of a Data Scientist
Playing a data scientist role varies from industry to industry. However, there are a few common skills, education, training and experience that can provide the much-needed boost in starting one’s Data Science career.
A data scientist’s key responsibility is to organize, clean and analyze the large dataset, mostly using software tools specifically designed for the task. Within this, their biggest responsibility is that of data analysis, a process which begins right from data collation which eventually culminates with business decisions being made based on the data scientist’s final data analytics insight.
The prime focus of Data Science is to help humans in making better and faster decisions. This benefit is not related to any particular industry, but to all industries across the world including Healthcare, E-commerce, Retail, etc.
Sensors collect large amounts of data, and advanced machine learning algorithms offer valuable insights to businesses. In fact, most MBA institutions have recognized its importance and have made it part of their MBA curriculum.
The Roadmap for becoming a Data Scientist
The hype is such that people have started calling themselves data scientists depending on the work they do due to the Data Science degree they have and others who attain a job title through data science online certifications.
According to RJMetrics report, about 11,400 self-identifying data scientists are available on LinkedIn. These are the data scientists who do not have a degree or certification, and perhaps they do not even know what makes them a data scientist. This report also states that about 52% of data scientists jumped into the data science industry about four years ago.
This has also had an impact on different industries such as Finance, Travel, Retail, who have started relying on Data Science to automate their business processes. Thanks to this boom, many professionals are enrolling themselves in Data Science certification course so they can learn the principles of Data Science and use it to benefit their organizations.
The Benefits of Joining a Data Scientist Course
If you are an aspiring data scientist you need to know what the course has to offer. Today, growing demand for Data Science courses, considering the huge demand supply gap currently, will only rise. There is considerable focus on grooming freshers and 3-5 years experienced professionals. Online learning platforms along with training institutes are collaborating to bring in 6-7 month full-time or short crash courses, which are industry acceptable and can churn out the right talent to meet the industry standards by offering a traditional as well as non-traditional course curriculum.
Non-traditional course curriculum focuses on the fundamentals of computer science, statistics and applied mathematics, while incorporating real-world examples. Students learn to balance the theory and practice of applied mathematics and computer science, thereby allowing them to analyze and handle large-scale data sets. These Data Science programs will position oneself to succeed in specialized jobs involving everything from the data pipeline and storage, to statistical analysis and eliciting the story the data tells.
One will be able to learn how to transform information to discover relationships and insights into complex data sets for today’s business world.
Unleash the Power of Conceptual Vision
As a data scientist, you are expected to interpret data in multiple forms. If you want to meet the required standard of your work, then you need to focus on the application of information. Among the various domains of science, Data Science is a field that deals with information in different formats. Those who hold expertise in this course will be in charge of managing statistical information and turning it into meaningful form by using visualization and analytical tools. Moreover, you would play an essential role in decision making by generating useful insights that could help a particular business grow. You would also require the development of all essential applications that give new meaning to the customer relationship.
Data scientists are expected to have a specific set of skills that will help them wrangle and mold data. Some of the key skills required to succeed include:
- Understanding of Programming languages
- Knowledge of Statistics
- Quantitative Analysis
- Good Communication skills and most importantly
- Love to play with numbers & huge sets of data to find insights from it.
A Data Science course program teaches you the latest tools and techniques that can help interpret the latest marketing trends by using statistical information. High expertise in database programming, SQL, R, and Python will also help you get ahead in this field. In addition, skills like how to utilize a particular algorithm and a strong acumen in linear algebra and calculus are what you need to be a successful data scientist. A software engineering degree would be an added benefit.
Salary is no constraint for skilled data scientists as top multinationals offer salary package anywhere in the range of USD 55K – 90K annually. Some of the popular roles being Data Analyst, Data Architect, Research Scientist, Statistician, Business Intelligence Analyst etc. Do note, your salary is also impacted by your work experience and the skills you bring to the table.
Data Science role is a highly respected field. You will be a part of the technical team and the management team and will be working with both teams to enhance the overall profits for your company. Moreover, the profit’s life cycle is heavily dependent on the development of informationally based projects, which makes you, a data expert, and a valuable asset to your company.
A Data Science course can bring a paradigm shift not only on career grounds but also in business by integrating statistics & valuable insights. Machine learning algorithms take it to the higher level as one can predict what would be the results of a particular event. With sectors such as Retail where the value of Data Science is quite visible, other sectors like Healthcare, Education and Energy will see far reaching implications in future. Especially healthcare where the advent of newer drugs will have far-reaching implications in patient care techniques, thereby improving scope for satisfaction levels drastically. Thus, keeping in mind the huge need of data scientists in the future considering the demand supply gap; the need of the hour is to harness the skills and creativity of data scientists so that they are ready to fulfil the gaps and help people experience life, products and services in a very new way.
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