What is Data Science, and How to Get Into It?

Modern technology has enabled the development and usage of storage, increasing the volume of information and data. As a result, data storage in recent years has been explosive. However, most of this data is untouched in databases and data lakes. 

For organizations and society to reap the benefits of collected data, we must interpret it. This requires high-level skills, where Data Science comes into the picture.

Data Science is the science of using scientific methods, processes, systems, and algorithms to best use structured or unstructured data by converting them into desirable and actionable knowledge.

Data Science combines multiple fields, such as statistics, data analysis, machine learning, and artificial intelligence. In addition, data Science involves collating, preparing, cleaning, and manipulating data to perform advanced data analysis. 

Why is Data Science So Popular?

With technology and the use of data continuing to rise, there are millions of job openings in Tech and Big Data.

If you look at Glassdoor, most of the top 50 jobs include a job role involving data analysis. Businesses rely heavily on data to make important decisions and effectively plan; therefore, the need for people with these hard technical skills, combined with the logical skills to deal with the data, will always be there.

How to Get into Data Science?

You must have the correct qualifications to get into Data Science or a related field such as Machine Learning. There are a few routes you can go through to get into the world of Data Science. Let’s look into them. 

STEM Degrees

STEM stands for Science, Technology, Engineering, and Mathematics.

These degree programs include Physics, Mathematics, Biology, Chemistry, Computer Science, Information and Communications Technology (IT/ICT), and Economics. These degrees help make a base of what a data scientist requires in terms of knowledge and skills.

Such study programs involve strong mathematical, analysis, and research skills. For example, the statistics modules in Mathematics are vital to Data Science as they are heavily used in data analysis and machine learning models. 

M.Sc. in Data Science 

The demand for roles in Data Science has increased immensely; universities have noticed this and now offer M.Sc. programs in Data Science. It provides training in Data Science and computational approaches, emphasizing statistical context and technical and practical skills. Moreover, this provides students with the vital skills to move into the Data Science world, accessing roles they had taken as an undergraduate, for example, becoming a Data Scientist in the Finance sector. 

Coding Bootcamps 

Coding boot camps have become a great and cheaper alternative to university degrees. They are short, intense training programs that help guide students to develop or improve skills in data science, Software Development, Web/Mobile App Development, and cyber security.

The duration of these boot camps can make it difficult for people without an understanding of the field. However, with the right mindset and determination, many people who have never written a piece of code before graduating are currently in Data Science roles.

How to Improve your Data Science skills:

There are many ways to analyze data and produce the same output. Therefore, it is essential to emphasize that being in Data Science requires constant learning, and the field is still evolving. Below are ways to keep up with your Data Science role and not feel left behind. 

Specializing in Chosen Programming Language

Many programming languages, such as R, Python, JavaScript, Ruby, C++, and more, can be used in Data Science roles. Refining the fundamentals of your chosen programming languages and constantly keeping up to date with the changes in their tools and libraries will benefit your career in the short and

Practice Makes Perfect!

A major element of learning is practicing it till it is perfect. Understanding and being able to implement your coding language is good.

However, putting it to the test will take it to the next level. Continually working on coding challenges is a great way to help you understand what you know and don’t. This enables you to define your strategy for improving your weaknesses and utilizing your strengths. You can access coding challenges on platforms such as Kaggle and Leetcode.

Data Science Roles:

There are various roles in Data Science, not just a Data Scientist. The use of data is becoming more prominent in nearly every sector, from fashion to politics. There is also a lot that you can do with data and how it can benefit a business in many ways. Below are a few roles in the Data Science field. 

1. Data Scientists and Senior Data Scientists 

A data scientist is tasked to analyze and interpret complex data. They may have graduated from a mix of mathematicians, computer scientists, or a trend-spotter. Deciphering these large datasets and analyzing and interpreting the outcomes allows companies to use the knowledge and actionable insight hidden in the enormous structured and unstructured data for their short and long-term business goals. 

Data scientists extract, analyze, and interpret large amounts of data from various sources, which meet the business’s needs. Before analyzing the data, they check the business’s agenda concerning the data to develop a hypothesis and use algorithmic approaches, artificial intelligence, machine learning, and statistical tools to identify patterns.

Senior Data Scientists are more experienced Data Scientists with a wide range of hard skills such as Machine Learning, SQL, and different programming languages (R, C++, Python, Java, and more). They use data to help shape the company in the most beneficial direction based on understanding its current issues and future needs. 

Their role involves guiding, implementing, and employing junior staff to steer the company toward the new goals implemented from analyzing the data. Aside from this, data analysis is also conducted to resolve complex business concerns and drive the development of new standards.

For Senior Data Scientists to be successful in their role, they also must have exceptional soft skills such as interpersonal, communication, and people skills. In addition, their position requires them to manage and mentor highly skilled staff. 

2. Business Analyst

Business Analysts (BA) are the bridge between IT and Business departments, using data analytics to assess current processes, requirements, products, and software to help street businesses improve these. To improve efficiency, they deliver data-driven recommendations and reports to CEOs, executives, and stakeholders. 

They are responsible for creating new models that fit the business’s current and future plans, working closely with the finance and information technology (IT) teams to establish these strategies. They require a strong understanding of financial analysis and identifying and outlining problems, solutions, and potential opportunities for a business.

3. Business Intelligence Analyst

A Business Intelligence Analyst’s primary role is to use data to help businesses make the right decision. Their role is to identify potential opportunities, spot trends, and help the business grow by leveraging the data. Their primary function is to improve efficiency, productivity, drive sales, and meet the business’s short and long-term goals. 

A Business Intelligence Analyst’s role may involve collating, cleaning, and analyzing data linked to sales, revenue, customer engagement, and market strategies. They will identify patterns or find potential opportunities from the data, producing a report to share their findings, such as visualizing data in charts or graphs. 

There are many more, such as a Data Architect, Data Engineer, and more. 

Where can Data Science Take Me?

Once you have the right qualifications to work in Data Science, you will reap the benefits of having a high-paying, transferable job.

As more and more sectors adopt the need for data as it becomes a vital element in their decision-making process, the vacancies for roles in Data Science continue to increase. Data Science roles allow you to move between different sectors, taking your hard skills with you and learning new ones.