Whenever you have seen a roadmap to learn data science, you must have found people often highlighting Python or R. Python and R are the most popular programming languages among the data science community. But just having the practical knowledge of Python or R will not help you land a job as a data science professional. There are a bunch of software and tools for data science that you should know about to become a data science professional. So if you want to know about such tools, this article is for you. In this article, I will take you through some of the most important software and tools for data science that you should know.
Software and Tools for Data Science
Microsoft Excel may not help you as the only tool to work with data. That is where programming languages like Python and R comes in. But still, Microsoft Excel helps to see what kind of data you are going to work with properly, compared to any other tool. Learning Microsoft Excel may not be necessary for you, but knowing its basics will always benefit you as a data scientist.
Data Visualization Tools
As data science professionals, we need to visualize the data very well to analyze it properly to find various trends and relationships between the features. There are a lot of data visualization tools that you can choose from, but the best ones are Tableau and Power BI.
Both Tableau and Power BI are the best tools for data visualization. I prefer Tableau over Power BI. You can explore both of these tools and choose the one you find easy to use.
A database is a collection of structured data controlled and managed by a database management system. There are two types of databases that a data science professional should know:
- Relational databases
- NoSQL databases
As a data science beginner, you can learn MySQL and MongoDB to get your first job as a data science professional.
Big Data Frameworks
Most businesses generate millions of data every hour, minute, and even in seconds. Big Data frameworks are used in working with such an amount of data as they compute on distributed architectures.
As a data science beginner, you don’t need to learn about big data frameworks. But you should know that you will need to learn big data frameworks like Hadoop and Spark to work with big data as an experienced data science professional.
Code editors are software that provides you with the functionality to write and execute your code. As a data science professional, you will find a lot of code editors, but the most popular code editors for data science are Jupyter Notebook and Google Colab.
Both of these code editors are used by data science professionals. I prefer Google Colab over Jupyter notebooks. You can explore these two code editors and choose the one you find easy to use.
So below is a list of all the software and tools for data science you should know:
- Microsoft Excel
- Data Visualization tools:
- Power BI
- Big data frameworks:
- Apache Spark
- Code Editors:
- Google Colab
- Jupyter Notebook
I hope you liked this article on the software and tools for data science you should know. Feel free to ask valuable questions in the comments section below.