In today’s digital age, the realm of data science stands as the epicenter of innovation and transformation. It’s a field where data isn’t just information; it’s the cornerstone of decision-making, strategy formulation, and business success. If you’re aspiring to dive into the fascinating world of data science, look no further than the Data Science Course in Hyderabad, that’s emerging as a hub for cutting-edge data science education.
Data Science has been named the sexiest job of the ’21st Century’ by Harvard Business Review. In addition, the Data Science field is one of the most reputed fastest-growing, and most profitable careers across the globe.
In today’s modern world, we generate a tremendous amount of data, be actual 2.5 quintillion bytes of data every day, which requires modern data processing tools and methods. And this is where Data Scientists come into the picture.
Are they well thinking about what it takes to become a Data Scientist? It could be tough to explain the various responsibilities and complex analytical problems a Data Scientist solves in a day-to-day role. However, since data has increased in the last couple of years, the demand for Data Scientists has also increased.
In fact, due to the rise in demand and thinking about career growth, Data Science enthusiasts are also taking a Data Scientist course in Hyderabad that would help them enhance their skills, gain hands-on experience with various tools, and ultimately start a career in this field.
Table of Contents
Who is a Data Scientist?
A Data Scientist is an experienced professional who gathers, extracts, and analyzes data to reach a conclusion that aligns with the overall business goals.
Data Scientists are constantly wrangling data into a cleaner and more representable format from its raw state. In addition, they often create algorithms that are being used to present data in a cleaner and more straightforward form that is easy for the stakeholders and other team members to understand.
What Does a Data Scientist Do?
A Data Scientist extracts meaningful information from various types of data such as structured, unstructured, and semi-structured that is generated every day within the enterprise. On any given day, a Data Scientist will be extracting data from a database, testing and building statistical models, preparing data for various analyses, or creating reports that include easily understandable data visualizations.
How To Become a Data Scientist?
To become a Data Scientist, you need to master a few mandatory skills. Here are the top six skills that are required:
1. Database Knowledge
2. Programming Langugage
3. Statistics
4. Concept of Machine Learning
5. Knowledge of Big Data Tools
6. Online Training
1. Database Knowledge: Database knowledge is required to store, extract, and analyze data using various tools. MYSQL, Microsoft SQL Server, Oracle Database, and Teradata are tools used by Data Scientists.
2. Programming Language: You need to learn at least one programming language, such as Python or R. Python is an open-source programming language and one of the most widely used programming languages in the data world. R is a free software for statistical programming, computing, and graphics widely used by statisticians.
3. Statistics: Statistics is collecting, organizing, analyzing, interpreting, and presenting data. Having a good knowledge of statistics is essential for becoming a Data Scientist.
4. Concept of Machine Learning: Machine Learning is a method of data analysis, a part of Artificial Intelligence that provides systems the ability to learn automatically and improve from experiences without being programmed. It helps in identifying patterns to make decisions.
5. Knowledge of Big Data Tools: Knowing Big Data tools such as Hadoop, Tableau, Apache Spark, and Talend is a plus point when starting as a Data Scientist. These tools deal with large and complex data that can not be handled by old traditional data processing tools and techniques.
6. Online Training: While many Data Science enthusiasts feel confident with their skills and abilities, some need guidance and training. This online training helps you enhance your skills by offering live training with industry projects and interactive classes.
Data Scientist Job Description
Data Scientist’s job description may vary depending upon the company and the industry. However, there are job roles that are common across all the Data Science positions:
● Collecting the massive amount of data and converting it to interpretable data
● Using programming languages for building data models
● Identifying various patterns and trends in raw data
● Create new algorithms to solve complex problems
● Predictive analysis
● Reporting and Data analysis methodologies
Data Scientist Salary in 2022
According to Glassdoor, the current average salary of a Data Scientist is $117,212 per year based on 18,134 salaries in 2021. Of course, the wage may differ depending on a candidate’s experience skillset to the table. However, the salary does vary depending upon the company, location, and industry.
Data Science Job Outlook
Data Science has been a career on the rise in the last few years and is regarded as one of the most in-demand fields, and it’s going to rise in the coming years. More and more companies are looking forward to Data Scientists to help them process and understand data. Companies like Google, Amazon, Facebook, and Apple are the most dominant and influential companies globally that use Data Science technology, and they require Data Scientists for data-driven decision-making.
According to a LinkedIn Workforce report, there was a shortage of nearly 151,171 people with Data Science skills overall in the United States in 2018.
Conclusion
The world of Data Science is continuously developing, and it is difficult for companies to survive without adopting a data-driven approach for modern businesses to thrive on. Hence,
Data Scientists are trained to stay at the leading edge of information and technology. To become a Data Scientist, you need to learn and master the skills mentioned above, such as programming languages, database knowledge, Big Data, tools, machine learning concepts, and data cleaning. In addition, the knowledge and skills you will gain in working on live projects, case studies, and simulations after completing a course or boot camp will set you ahead of the competition.
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