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10 Data Science Tools to Look For In 2020
November 18, 2019

The demand for competent data scientists is on a rise. They are hired by top organizations to get perceptions about the market, evaluate organizational risks, forecast sales, appraise risks within an organization, boost customer experience and improve the quality of consumer and industrial products. For implementing these tasks data scientists utilize various data science tools.

These tools help them to interpret, extract, leverage, pre-process and generate predictions from vast and complex structured and unstructured data. We have put together the list of top 10 data science tools to look forward to in 2020.

 

  1. Tableau

Tableau is a powerful software that visualizes and analyzes data. It is loaded with advanced graphics that help in visualizing geographical data and simplifying unprocessed data into a format that is easy to understand. The software can interface with databases, spreadsheets, OLAP, and cubes.

 

  1. TensorFlow

TensorFlow is an open-source data science tool with multi-dimensional arrays famous for its efficient analysis of raw data and computational capacities. With its ability to function on CPUs and GPUs, it has emerged as a powerful platform. The tool finds application in advanced ML algorithms such as Deep Learning.

 

  1. Matplotlib

Used for generating graphs by utilizing the analyzed data, this powerful data science tool is a popular choice to look forward to in 2020. With the help of this tool, you can generate complex histograms, bar graphs, and scatterplots. These complex graphs in the analytics tool can be created by simple coding.

 

  1. MATLAB

MATLAB is an advanced closed-source software that processes mathematical data. The analytics platform can be automatically generated by using code, output, and formatted text. The versatile and multi-paradigm numerical computing environment tool for data scientists can be used for image and signal processing, execution of algorithms, and demonstration of data through statistics. The tool also features a graphic library that is used for creating powerful visualization, processing of image and signal.

 

  1. SAS

SAS is a leader in the domain of analytics and cloud computing. It is closed source software that is used for analyzing and presenting data powerfully and interactively. It is mainly used by large organizations for statistical operations.

The trusted technology empowers businesses by converting their data into better decisions. So whether you are a data scientist or statistician, business analyst or forecaster, you can surely benefit from it.

 

  1. BigML

Next in the data science tools list of our countdown is BigML. It is a powerful data analyzing and visualization tool that is going to become more popular in 2020. It provides a fully communicative, cloud-based GUI (graphic user interface) setting for handling machine learning Algorithms.

BigML is the ideal tool that specializes in predictive modeling. Therefore, it is mainly used for estimating sales, analyzing risks, and creating new products. The best feature of the tool is that it is equipped with different automation methods and facilitates interactive data visualization.

 

  1. ggplot2

ggplot2 is an advanced software that creates powerful illustrations and visualizations. You can create maps of different styles such as chloropleths, hexbins, and cartograms. It can also deliver customized visualizations for enhanced storytelling with it.

The tool facilitates data scientists and statisticians to add text labels to data points and increases interactivity and aesthetic value of the graphical representations.

  1. Weka 

Weka (an abbreviation of Waikato Environment for Knowledge Analysis) is open-source GUI software with an interactable platform. The advanced software is an assortment of different machine learning algorithms that can be used for data mining. The most popular data science tool includes tools such as classification, regression, clustering, visualization, and data preparation.

 

  1. NLTK

NLTK is one of the powerful data science tools and techniques that’s going to dominate in 2020. It assists computers to learn and decode human language by developing statistical models that form a vital part of machine learning.

NLTK is an abbreviation of natural language processing and finds extensive application in different language processing methods like tagging, stemming, parsing, tokenization, and machine learning.

 

  1. Apache Spark

Apache Spark is a powerful analytics tool that is particularly created to deal with batch processing and stream processing. It features many application programming interfaces for helping data scientists to create repeated data access for the purpose of Machine Learning.

To conclude, the above-mentioned data analyzing and visualization tools are going to have a major impact in 2020. They are going to transform businesses and revolutionize the ways organizations operate in a competitive scenario.

 

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