Learn what data science is, how does data science work, and career opportunities as a data scientist.
What is Data Science?
Data Science is a field of study where anyone can learn about various tools, algorithms, and machine learning used to find new & valuable patterns from the raw data. It’s a process where so many tools and algorithms are applied to big data collected from different sources to find something unique and valuable.
How does Data Science Work?
The main purpose of using data science is to collect, process, analyze and filter helpful information that helps to find unique patterns. Data Science follows a complete workflow to produce useful information from the raw data.
Let’s see the step-by-step process of data science:
Step 1. Collecting Data
In the first step, it should be clear what type of data will be analyzed, whether it’s customers’ buying behavior, sales, best-selling products, or other factors that require analysis for business growth. Once the purpose is cleared, start collecting the relevant data at one storage and label for easy recognition and analysis.
Step 2. Cleaning the Data
Once the data is collected from different sources, then it’s time to remove irrelevant and unnecessary data and clean the data properly so that it’s easy to analyze.
Step 3. Analyzing Data
It’s time to analyze the well-structured data. There are various patterns and methods available to analyze the big amount of data and filter the most valuable data from it.
Is Data Science a Good Career?
The demand for data science skills will increase by 27.9% in 2026, according to the WorldDataScience. It clearly shows that data science can be a good career in the future. It’s already in high demand with amazing salaries and Perks, and that’s why it’s also known as the “Most promising career” by LinkedIn.
So, if you’re planning to make your career in data science, then it’s the right time with huge demand, and later its demand will keep increasing. Make yourself an expert in this field and explore opportunities in life.
Data Science Tools for Beginners
To implement Data Science, there are many valuable tools available for beginners. These tools are easily accessible and do not require coding knowledge because these tools come with pre-defined functions, algorithms, user-friendly GUI, and many more.
We’ve handpicked the Top 5 Tools used in Data Science for beginners:
SAS is one of the most in-demand data science tools specifically designed for statistical operations. Some large organizations are using this tool to analyze data for statistical modeling, and it comes with advanced features that help in data analysis in the best possible way.
2. Apache Spark
Apache Spark is the most useful Data Science tool specifically designed for a powerful analytical purpose. And it’s used to handle batch processing and stream processing. Apache Spark comes with many Machine Learning APIs that help data scientists predict near accuracy with given data.
BigML is another widely used data science tool used to process machine learning algorithms. It’s a great tool for predictive modeling, and data scientists use it for better predictions, and it is also helpful for better data visualization.
MATLAB is used for simulating neural networks and fuzzy logic, and it’s also used in image and signal processing. Data scientists can do so many things with MATLAB, from handling all the problems, data cleaning, analyzing, and deep learning algorithms.
The most popular and widely used data analysis tool is Excel. Microsoft Excel is mainly used for calculation and data processing, visualization, and other complex calculations. It comes with predefined formulas, tables, filters, and slicers that help data scientists to do calculations more effectively.
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