Software Alternatives, Accelerators & Startups

Scikit-learn VS Domo

Compare Scikit-learn VS Domo and see what are their differences

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Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Domo logo Domo

Domo: business intelligence, data visualization, dashboards and reporting all together. Simplify your big data and improve your business with Domo's agile and mobile-ready platform.
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Domo Landing page
    Landing page //
    2023-10-08

Scikit-learn features and specs

  • Ease of Use
    Scikit-learn provides a high-level interface for common machine learning algorithms, making it easy for beginners and professionals to implement complex models with minimal coding.
  • Extensive Documentation and Community Support
    The library has comprehensive documentation and a large, active community. This makes it easy to find tutorials, examples, and solutions to common problems.
  • Integration with Other Libraries
    Scikit-learn integrates well with other scientific computing libraries such as NumPy, SciPy, and pandas, allowing for seamless data manipulation and analysis.
  • Variety of Algorithms
    It offers a wide array of machine learning algorithms for tasks such as classification, regression, clustering, and dimensionality reduction.
  • Performance
    Designed with performance in mind, many of the algorithms are optimized and some even support multicore processing.

Possible disadvantages of Scikit-learn

  • Limited Deep Learning Support
    Scikit-learn is primarily focused on traditional machine learning algorithms and does not offer support for deep learning models, unlike libraries like TensorFlow or PyTorch.
  • Not Ideal for Large-Scale Data
    While Scikit-learn performs well for moderate-sized datasets, it may not be the best choice for extremely large datasets or big data applications.
  • Lack of Online Learning Algorithms
    The library has limited support for online learning algorithms, which are useful for scenarios where data arrives in a stream and model needs to be updated incrementally.
  • Less Flexibility in Customization
    It can be less flexible compared to lower-level libraries when highly customized or specific implementations are needed.
  • Dependency Overhead
    Scikit-learn relies on several other Python libraries like NumPy and SciPy, which might require users to manage multiple dependencies.

Domo features and specs

  • Data Integration
    Domo supports integration with a vast array of data sources including databases, cloud services, spreadsheets, and more, allowing for seamless data consolidation.
  • Real-Time Data
    Domo provides real-time data processing and dashboard updates, ensuring users have access to the most current information for decision-making.
  • User-Friendly Interface
    Domo features an intuitive and easy-to-use interface, making it accessible even for non-technical users to create dashboards and reports.
  • Collaboration Tools
    Domo includes built-in collaboration tools, such as chat and notifications, which facilitate team communication and collaborative analysis.
  • Scalability
    Domo's cloud-based architecture ensures it can scale according to the size and needs of the business, managing large volumes of data efficiently.

Possible disadvantages of Domo

  • Cost
    Domo can be relatively expensive, especially for small businesses or startups with limited budgets, as it is priced based on data volume and user count.
  • Learning Curve
    Despite its user-friendly interface, some users may still find a steep learning curve when it comes to utilizing advanced features and functionalities.
  • Data Preparation
    Data preparation tools in Domo may not be as robust as some specialized ETL (Extract, Transform, Load) tools, sometimes requiring external preprocessing.
  • Customization Limitations
    While Domo offers a good degree of customization, certain advanced functionalities may still require custom development, which can be time-consuming.
  • Performance Issues
    Some users have reported performance issues, particularly with large datasets or complex queries, which can result in slower processing times.

Analysis of Scikit-learn

Overall verdict

  • Yes, Scikit-learn is generally regarded as a good library for machine learning, especially for beginners and intermediate users who need reliable tools with efficient implementation of numerous algorithms.

Why this product is good

  • Scikit-learn is considered a good machine learning library because it provides a wide range of state-of-the-art algorithms for supervised and unsupervised learning. It is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. The library is well-documented, easy to use, and has a consistent API that simplifies the integration of different algorithms. Furthermore, there's a strong community and continuous development, which means it is well-maintained and updated regularly with new features and improvements.

Recommended for

  • Beginners learning machine learning concepts and application.
  • Data scientists and engineers looking for a robust and efficient toolkit to build and deploy machine learning models.
  • Researchers who need an easy-to-use library that facilitates the experimentation of various algorithms.
  • Developers who require a seamless, Python-based machine learning library that integrates well with other data analysis tools and environments.

Analysis of Domo

Overall verdict

  • Domo is a strong option for businesses looking for a robust, scalable, and user-friendly data analytics platform. Its strengths lie in real-time analytics, data integration capabilities, and ease of use. However, it might be costly for small businesses or those with limited budgets.

Why this product is good

  • Domo is a comprehensive business intelligence platform that offers a wide range of data visualization and analytics tools. It integrates with various data sources, allowing users to create interactive dashboards and reports.
  • The platform is user-friendly and cloud-based, which means it is accessible from anywhere with an internet connection. This flexibility is often appreciated by teams that require remote access or collaboration.
  • Domo offers real-time data insights, enabling businesses to make informed decisions quickly. Its ability to handle large volumes of data and provide meaningful insights is generally well-regarded.
  • The platform allows for custom app development on top of its existing infrastructure, which can help businesses tailor the solution to their specific needs.

Recommended for

  • Large enterprises that need to manage and analyze vast amounts of data efficiently.
  • Teams that prioritize real-time data insights and decision-making.
  • Organizations seeking a cloud-based solution for remote accessibility and collaboration.
  • Businesses that desire a platform capable of custom app development for unique business needs.

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Domo videos

Domo Overview

More videos:

  • Review - Domo Customer Review: National Geographic
  • Review - Domo Customer Review: La-Z-Boy

Category Popularity

0-100% (relative to Scikit-learn and Domo)
Data Science And Machine Learning
Data Dashboard
15 15%
85% 85
Data Science Tools
100 100%
0% 0
Business Intelligence
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Scikit-learn and Domo

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

Domo Reviews

Explore 6 Metabase Alternatives for Data Visualization and Analysis
Domo is a robust BI tool known for its ease of use and powerful data aggregation capabilities. It allows users to effortlessly combine data from various sources, apply advanced formulas, and create comprehensive views for accurate analysis.
Source: www.draxlr.com
Explore 7 Tableau Alternatives for Data Visualization and Analysis
Domo BI is a powerful business intelligence platform that transforms raw data into actionable insights. It offers flexible data experiences, diverse visualizations, and automated user management. User-friendly and browser-based, it connects to thousands of data sources with over 1000 connectors. Features like Magic ETL, data lineage tools, and Jupyter integration simplify...
Source: www.draxlr.com
5 best Looker alternatives
Domo: Domo is yet again a legacy data visualization tool with a vast set of data connectors to connect to. However, users often express concerns about its limited customer support and challenges in handling large datasets efficiently.
Source: www.draxlr.com
10 Best Alternatives to Looker in 2024
Domo: Domo is built for decision-makers who need real-time data access across various business operations. With strong mobile support and built-in connectors for multiple data sources, Domo offers versatile, on-the-go analytics.
25 Best Statistical Analysis Software
Intuitive interface: Domo offers an easy-to-use interface that allows users to quickly navigate and interact with their data, making it suitable for users with varying levels of technical expertise.

Social recommendations and mentions

Based on our record, Scikit-learn seems to be a lot more popular than Domo. While we know about 31 links to Scikit-learn, we've tracked only 1 mention of Domo. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Scikit-learn mentions (31)

  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
  • 🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖
    Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 12 months ago
  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / about 1 year ago
  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / almost 2 years ago
View more

Domo mentions (1)

  • URL with Login code
    We currently use domo.com and need to display dashboards to screens. Source: almost 3 years ago

What are some alternatives?

When comparing Scikit-learn and Domo, you can also consider the following products

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

OpenCV - OpenCV is the world's biggest computer vision library

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

NumPy - NumPy is the fundamental package for scientific computing with Python

Sisense - The BI & Dashboard Software to handle multiple, large data sets.