Top 5 Data Science Tools

Trending Data Science Tools you should know

Data Science is the revolution that changed the way many businesses and industries work. Automation of industrial processes, domestic work, and agriculture are the best examples of advanced data science technology. The reason behind its growth is highly-effective Data Science tools.

Data science tools process, filter and analyze the raw data to give useful insights. Various data science tools are important in developing algorithms, data analytics models, and visual graphics.

Here are the Top 5 Data Science Tools

It is important to know the role of data science tools in demand to deliver productive results and achieve desired business targets.

1. Apache Spark 

Apache spark is an open-source data processing framework; it handles large data volumes and processes them in a short time. It’s the alternative to Apache Hadoop. Spark has seen tremendous growth due to the fast processing of data and is also suitable for Continuous Intelligence Applications. As an analytics engine, it can retrieve and modify data. Its high-level APIs and rich developer & machine learning libraries make it easier for data scientists to perform tasks efficiently.

2. MATLAB

MATLAB is a closed-source high-level programming language that performs numerical computations of mathematical expressions. Its’ main features are matrix functions, algorithm development, and statistical modeling. It is an interactive system that requires no coding. It creates powerful visualizations which are used in signal and image data processing.

3. Big ML

Big ML is a cloud-based online machine-learning platform that is helpful in threat analysis, weather forecasting, linear regression, and risk analysis. This is a GUI-based tool that performs data processing and data visualization. Many machine learning algorithms, such as cluster analysis, anomaly detection, and time series, are automated in a single framework. Many companies use it to build and visualize machine learning models quickly.

4. Tableau

Tableau is one of the most powerful data visualization toolused by many companies and enterprises. Large and complex data is analyzed and visualized with the help of powerful graphics. Its ability to extract data from multiple sources and interact with databases, OLAP (OnLine Analytical Processing) cubes, and spreadsheets makes it a significant data science tool. It is used in processing Geographical data that can plot longitude and latitude on maps. More than 60 companies are using this tool around the world.

5. Tensor Flow

TensorFlow is an open-source machine learning and deep learning library. The name Tensor comes from the datatype used, which is an N-dimensional array. It is mostly used in the field of research and production. It helps in the development of machine learning algorithms and data analysis. It is used in NLP to create machines that understand human language, human recognition, and image classification. It can build and deploy data science models on various platforms like smartphones, computers, and servers.

 Where to learn Data Science Tools? 

Today data is the biggest tool in any field; handling large chunks of data requires highly effective data science tools. Without data analytics and data visualization, it is nearly impossible to organize and draw insights from the raw data. It is a must for any data scientist to have expertise in trending data science tools.

You can learn about data science tools through Online Data Science courses. This also helps in understanding the role of data scientists and their responsibilities in a more organized way.