“We are going to completely change what it means to do advanced analytics with our data solutions. We have machine-learning stuff that is about really bringing advanced analytics and statistical machine learning into data science departments everywhere.” – Satya Nadella, CEO, Microsoft.
The above quote shows the importance of Data Science and how crucial it is to grow for companies in the coming years. Eventually, it shows how great a move it can be to take up a Data Science online course and get certified so that you reskill yourself and make a career in the ever-demanding domain.
2.5 quintillion bytes.
This is the whopping amount of data generated every day by our activities over the Internet. The activities over the Internet may vary from posts on social media to transactions on eCommerce, pictures on smartphones to sensors in shopping malls, the enormous amount of data is generated every second.
Today, enterprises are flooded with huge amounts of raw, unstructured data which is often referred to as Big Data. they are required to deploy a variety of scientific methods to extract useful insights from Big Data, which is accelerated by the IoT (Internet of Things).
This is where the role of Data Scientist comes into play. Data Scientists today are considered to be ‘superheroes’. The demand for data scientists is fueled by the disparity between the requirement and supply of skilled data scientists.
If you are a data analyst who performs the task of organizing unstructured data (with the help of various algorithms and data visualization tools) to extract useful information, you can successfully transform your career into Data Scientist. This is because everyone wishes to upskill oneself and upgrade the career, to have a boost in salary and the position as well.
In the U.S., Data Scientists are regarded as one of the highest-paid IT professionals with an average annual salary of $113,000, according to Glassdoor, and that of a Data Analyst is found to be USD 62,000.
Let us see what actually a data analyst and data scientist mean, and how you can transform your career from a data analyst to a data scientist.
What is a Data Analyst?
Typically, a Data Analyst collects the data from various resources, organizes it effectively to find out underlying relationships, transform it into a user-readable format, perform statistical analysis, and utilizes data visualization tools such as graphs, charts, etc, to extract meaningful insights in order to help in making feasible business decisions.
It is very important for a data analyst to understand the business context and define the goals of the business to be achieved clearly. So, you need to measure the performance of the business to drive its decision-making capabilities.
What is a Data Scientist?
There is considerable overlap between the roles of analysts and data scientists. A data scientist also needs to understand the business context clearly and have proper knowledge of business objectives. The difference in their roles lies in the methodology they implement. Data Scientists are required to use technical and scientific methods to perform calculations and make predictions.
The scientific methods used by a data scientist may include math, statistics, linear regression, decision trees, and advanced analytics methods such as neural networks, machine learning, and predictive modeling to drive business decision-making.
To become a data scientist, you need to acquire deep technical/computer science skills. Software development skills are crucial to building predictive and prescriptive models.
How to make a career transition from Data Analyst to Data Scientist?
To make a transition, you first need to understand the two job roles. Though both of them look similar at first. The skills required for both the job roles are almost similar, with one key difference that data scientists are required to develop coding/programming skills.
It is easy to develop programming skills in a few months, so a career transition from data analyst to data scientist is not a difficult task.
The series of steps you need to follow to make the transition are mentioned below:
Understand the job role of Data Scientist
You need to have a concise knowledge of the difference between the roles and responsibilities of a data scientist and a data analyst, to fit successfully in the role of a data scientist. The approach to drive decision making in both jobs is entirely different.
To become a data scientist, you need to:
- Evaluate data models to demonstrate the accuracy of the analyses.
- Build ETL (Extract, Transform, Load) pipelines.
- Use APIs(Application Programming Interfaces) for data mining.
- Use machine learning algorithms such as linear regression, gradient boosting, decision trees, etc, for building predictive models.
- Leverage data science programming languages such as R or Python for data cleaning.
- Test and enhance the accuracy of existing machine learning models.
- Create visualizations of the advanced analysis results in a user-readable format.
- Design automation tools and techniques to simplify routine tasks.
To become a successful data scientist, you need to master programming languages such as Python, R, or Java. To highlight the coding skills, try to go hands-on with some real-world data science projects. Having practical experience will let you master the concepts of programming and its implementation.
Develop Mathematical and Model Building Skills
Writing algorithms from scratch requires thorough knowledge of linear algebra, and calculus, so you need to develop your math, so as to understand how machine learning algorithms work.
Developing model building skills will help you in solving business challenges. Elevating the skills is necessary to become a successful data scientist.
By now, you know why it is beneficial to make a career transformation from a data analyst to a data scientist. Apart from a hike in salary, you get one level up in the position too.
To make a successful transition, you are required to go with a well-crafted plan by doing a self-assessment of your existing skills and the skills you need to develop. Simply put, you need to fill the skill-gap between the two roles.
The best way to make the transition is to take up an online training course and get certified. The certification validates that you have the required knowledge and skills to become a data scientist.
The online training course lets you go hands-on with charts, graphs, programming languages, and helps you work with the skills required. In this way, you can brush up your skills and knowledge and land up to a career in Data Science.
Get yourself enrolled now!