The Ultimate List of Data Scientist Tools

Expertise in data analytics and data management is crucial for business operations and business decisions. For data scientists and experts to effectively do their job, they use software tools that enable them to produce quality output.

If you’re a budding data scientist or even a seasoned one, this article is for you. Here, we will give you a list of data scientist tools that have excellent features and functions to help you be the best at what you do. This guide also covers popular data science tools costs and the companies that use data science tools, so you can decide which one best suits your needs.

The 10 Best Data Scientist Tools

1. Apache Spark
2. BigML
3. Dell Boomi
4. Jupyter
5. MATLAB
6. Microsoft Excel
7. Python
8. R Programming
9. Tableau
10. Talend

What Are Data Scientist Tools?

Data scientist tools are software platforms used in processes such as data visualization, forecasting, statistics, and integration. These tools enable data scientists to easily do their jobs thanks to the advanced features for automation, machine learning, and computer algorithms.

These tools also work with less human intervention, which eliminates possible risks and errors by automating processes and delivering accurate calculations.

What Are the Main Types of Data Scientist Tools?

In this section are the categories of tools used in data science. Depending on their functions and features, these tools can be used in scientific computing, advanced analytics, statistical analysis, predictive model building, and automation.

Data Science Visualization Tools

Data science visualization tools are software used for the graphical representation of data to show relevant information. They use elements such as charts, graphs, and maps that provide insights from data patterns and trends. They simplify complex and huge amounts of data to produce reports that are easily understood, even by non-technical users.

Examples of Data Visualization Tools

• Microsoft Excel
• Tableau

Scripting Languages

Scripting languages are programming languages that are interpreted. Scripting languages provide commands, also known as scripts, that are interpreted in a runtime environment. They are executed during runtime instead of during compilation. These data science tools are used to automate tasks and processes that would otherwise be operated manually.

Examples of Scripting Languages Tools

• MATLAB
• Python

Machine Learning Tools

Machine learning is a subset of artificial intelligence that automates analytical processes using computer algorithms. It refers to the ability of systems to automatically identify trends, create accurate analysis, and provide data-driven insights based on the collected data. Data scientists use machine learning models and tools to produce a quality statistical and predictive output with less human error.

Examples of Machine Learning Tools

• Apache Spark
• BigML
• Jupyter

Statistical Tools

Statistics is a powerful tool that helps data scientists generate patterns and deliver significant business decisions. Data scientists use statistical tools to gather and analyze data using mathematical formulas. These tools enable data scientists and analysts to perform quantitative analysis and predictions based on the collection of data.

Examples of Statistical Tools

• R Programming

Data Integration Tools

These tools are used to combine data from multiple resources into a centralized location. They make data more accessible and provide a single view of insights. Data integration tools help data scientists and analysts establish precise analysis from up-to-date relevant data. These are also used in data cleansing and data validation to maintain data integrity.

Examples of Data Integration Tools

• Dell Boomi
• Talend

Data Scientist Tools Cheat Sheet: A Tabular List of Data Scientist Tools

Tool	Uses	Companies That Use It	Cost	Availability
Apache Spark	Data engineering, statistics, machine learning	Agile Lab, Alibaba Taobao, Amazon, UC Berkeley AMPLab	Free	Open-source
BigML	Machine learning	Avast, Faraday, Nuffield Health, Pfizer, Seagate	Free $30-$50/month$10,000-$45,000/year	Open-source, commercial
Dell Boomi	Data integration	Azur, Boise State University, Dell Technologies, LinkedIn, Moderna	Starting from $550/ month	Commercial
Jupyter	Data cleaning, machine learning, simulation, statistical modeling, data visualization	Delivery Hero, Hepsiburada, Ruangguru, Trivago	Free	Open-source
MATLAB	Statistics, scripting language, modeling, simulation, data visualization, algorithm development	ADEXT, AMD, doubleSlash, Stan, Volvo Cars	$29-$2,350/licence	Commercial
Microsoft Excel	Data visualization, data management, programming, task management	Dell Technologies, Hour Bail Bonds Service, Samsung Electronics, Total	$160	Commercial
Python	Data analytics, game development, machine learning, scripting language, web development	Facebook, IBM, Intel, JPMorgan Chase, NASA, Netflix, Pixar	Free	Open-source
R Programming	Data analysis, data cleansing, statistics	Amazon, Firefox, Google, LinkedIn	Free	Open-source
Tableau	Data visualization, business intelligence, data blending	Amazon, Citigroup, Coca Cola, Ferrari, LinkedIn, The DarkStar Group	Free $15-$70/month	Open-source, commercial
Talend	Data integration	AstraZeneca, Lenovo, Newcastle University	Free$1,170/month $12,000/year	Open-source, commercial

The Best Data Scientist Tools, Explained

This section gives you detailed information on the data scientist tools listed above. Learn how these tools can help you in your data science projects.

Apache Spark

• Type: Machine learning tool
• Companies That Use Apache Spark: Agile Lab, Alibaba Taobao, Amazon, UC Berkeley AMPLab
• Apache Spark Cost and Availability: Free, Open-source

Apache Spark is an open-source software developed by Apache Software Foundation Inc. This tool is used in big data processing. It allows users to gather and analyze large-scale datasets. It uses resilient distributed datasets or RDDs that run on memory in processing. This tool consists of five major components. They are Spark Core engine, GraphX, Spark SQL, MLlib, and SparkR.

BigML

• Type: Machine learning tool
• Companies That Use BigML: Avast, Faraday, Nuffield Health, Pfizer, Seagate
• BigML Cost and Availability: Open-source free, $30 per month for Standard Prime Personal account, $55 per month for Standard Prime Organizational account, $10,000 per year for BigML Lite Private Deployment, $45,000 per year + $10,000 per year for BigML Lite Private Deployment, Open-source and commercial availability

BigML is a scalable cloud-based machine learning platform that is used both in small and big data. This tool brings automation features, such as automatic optimization and scripting workflows. Machine learning models can be viewed as well using the BigML web interface. Data scientists can also integrate these models using the BigML’s REST API.

Dell Boomi

• Type: Data integration tool
• Companies That Use Dell Boomi: Azur, Boise State University, Dell Technologies, LinkedIn, Moderna
• Dell Boomi Cost and Availability: Starting from $550 per month, Commercial

This tool is a cloud integration platform that allows users to connect cloud-based processes, which are also called Atoms. This tool integrates cloud and on-premises data and applications with a higher level of efficiency using its drag-and-drop feature on its user interface. It allows data scientists to synchronize data across multiple resources.

Jupyter

• Type: Machine learning tool
• Companies That Use Jupyter: Delivery Hero, Hepsiburada, Ruangguru, Trivago
• Jupyter Cost and Availability: Free and open-source

Jupyter is a web-based platform used to write and share documents such as software codes, computational outputs, texts, and interactive visualizations. The Jupyter Notebook app can be used in a web browser or on a desktop even without internet access. This platform can be used to integrate big data and allows users to share work using GitHub, email, Dropbox, and Jupyter Notebook Viewer.

MATLAB

• Type: Scripting language tool
• Companies That Use MATLAB: ADEXT, AMD, doubleSlash, Stan, Volvo Cars
• MATLAB Cost and Availability: Individual (Standard): $2,350 for perpetual license and $940 for an annual license, Academic Use: $550 for perpetual license and $275 for an annual license, Personal Use: $95, Student Use: $55 for Student Suite License and $29 for Student License, Commercial

MATLAB is a matrix language developed by MathWorks that features advanced mathematical functions such as elementary functions, matrix functions, and high-level arithmetic. This platform is also used in deep learning models, signal processing, control systems, and machine learning models. Its high-performance computing environment helps data scientists in data exploration, analysis, and visualization.

Microsoft Excel

• Type: Data science visualization tool
• Companies That Use Microsoft Excel: Dell Technologies, Hour Bail Bonds Service, Samsung Electronics, Total
• Microsoft Excel Cost and Availability: $160, Commercial

Microsoft Excel is a popular tool for data visualization. It’s a spreadsheet software application that contains rows and columns used in analyzing data. It consists of different tools and features for data visualization, organization, and statistics. These tools include pivot tables, Visual Basic for Applications or VBA, functions, formulas, tables, charts, and graphs.

Python

• Type: Scripting language tool
• Companies That Use Python: Facebook, IBM, Intel, JPMorgan Chase, NASA, Netflix, Pixar
• Python Cost and Availability: Free, Open-source

Python is an open-source tool and interpreted high-level language used in object oriented programming, web development, and automation. It’s a popular programming language for machine learning, game development, artificial intelligence, and application design. Python features different useful libraries for data cleaning, analysis, and visualization. If you are interested in learning Python, consider Enki or SoloLearn, which are some of the best coding apps for beginners.

R Programming

• Type: Statistical tool
• Companies That Use R Programming Software: Amazon, Firefox, Google, LinkedIn
• R Programming Software Cost and Availability: Free, Open-source

R is a programming language used for statistical computing. Its functions are helpful in data visualization, exploration, and modeling. Data scientists use R programming software in statistical models and data analytics. R features static graphics and diagrams for data visualization. It can also perform complex statistical computations even in large data sets.

Tableau

• Type: Data science visualization tool
• Companies That Use Tableau: Amazon, Citigroup, Coca Cola, Ferrari, LinkedIn, The DarkStar Group
• Tableau Cost and Availability: Free for Tableau Public, $15 per month for Tableau Viewer, $42 per month for Tableau Explorer, $70 per month for Tableau Creator, Open-source and commercial

Tableau is a visualization tool that helps data scientists view and analyze data to make actionable insights. It features a dashboard that lets users view their data in the form of stories and visual objects. Tableau comes in a wide range of interactive data visualization including charts, histograms, charts, treemaps, and boxplots. This can be used in forecasting as well.

Talend

• Type: Data integration tool
• Companies That Use Talend: AstraZeneca, Lenovo, Newcastle University
• Talend Cost and Availability: Open-source free, Talend Cloud Data Integration: Paid monthly for $1,170 per user or paid annually for $12,000 per user, Open-source and commercial

Talend is a platform used to integrate data and applications from different sources. It also helps users in data management, data preparation, and big data. Talend features a cloud-based data science platform that allows users to connect and share cloud and on-premise data integration projects.

Why Data Scientist Tools Are Important

Data is very crucial in business operations and processes. Improper use of data can cause a waste of money and time. To avoid this, businesses use data science to identify patterns and trends and get valuable insights. Data scientists use these essential tools to increase business productivity and improve effectiveness, aiming for less to no error.

Data science tools enable data scientists to understand complex real-time data for business decision-making. These tools make it easier for them to have rich insights using a data-driven approach through automation, statistics, machine learning, deep learning, and data analytics.

Data Science Tools FAQ