Software Alternatives & Reviews

Microsoft Power BI VS Scikit-learn

Compare Microsoft Power BI VS Scikit-learn and see what are their differences

Microsoft Power BI logo Microsoft Power BI

BI visualization and reporting for desktop, web or mobile

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Microsoft Power BI Landing page
    Landing page //
    2023-06-14
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Microsoft Power BI videos

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Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

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

Category Popularity

0-100% (relative to Microsoft Power BI and Scikit-learn)
Data Dashboard
87 87%
13% 13
Data Science And Machine Learning
Data Visualization
100 100%
0% 0
Data Science Tools
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 Microsoft Power BI and Scikit-learn

Microsoft Power BI Reviews

Embedded analytics in B2B SaaS: A comparison
A few options were disregarded from the start due to a hefty price tag, these were Looker, Tableau, Power BI, GoodData. A few options like Trevor.io, Preset, Observable were disregarded as they did not seem to fit our criteria (based on the evaluation matrix).
Source: medium.com
Best 8 Redash Alternatives in 2023 [In Depth Guide]
Users can also sign up for Power BI and Power BI Desktop for free to receive data, insights, and visual analytics. However, the premium versions offer more advanced features like AI, data management, and greater capacity and users.
Source: www.datapad.io
8 Alternatives to Apache Superset That’ll Empower Start-ups and Small Businesses with BI
PowerBI is one of the leading BI solutions in the market. It’s a highly scalable BI tool owned by the Microsoft team. It can be cloud-hosted or downloaded on-premise. It’s self-service and fosters enterprise-level answers to ad hoc queries. Trevor.io, Metabase and Looker can also work as Power BI alternatives.
Source: trevor.io
Top 10 Data Analysis Tools in 2022
Power BI Power BI is owned by Microsoft and, as such, has excellent compatibility with Microsoft Excel, which is a highly popular tool for data analysis. Power BI Premium costs $27.5 per month for each user. Power BI is a powerful tool produced by Microsoft and has proven itself as a powerful data analysis tool. However, its best features are seen within the Microsoft...
Best Google Data Studio Alternatives (Self-Service BI)
For personal use, Power BI can be downloaded on your local machine for free. However, if you want to use more Power BI services, you will need to pay $9.99/user/month for a cloud solution or $4,995/month for a dedicated server (cloud compute and storage resource)

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...

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Microsoft Power BI. It has been mentiond 27 times since March 2021. 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.

Microsoft Power BI mentions (17)

  • Unified Analytics Platform: Microsoft Fabric
    Microsoft Fabric is currently in preview and provides data integration, engineering, data warehousing, data science, real-time analytics, applied observability, and business intelligence under a single architecture by integrating services such as Azure Data Factory, Azure Synapse Analytics, Data Activator, and Power BI. In addition, it comes with a SaaS, multi-cloud data lake called "OneLake" that is built-in and... Source: 11 months ago
  • NSS Data Analytics Program Question
    I'd suggest spending some time learning the material before you invest thousands in tuition only to find that you don't like it or aren't good at it. Download Tableau Public or Power BI and force yourself to use them for a few months. That's how I taught myself R. Source: about 1 year ago
  • Why Is Data Analytics Important?
    Discover why business analytics is crucial for your business and how to utilise data analytics and PowerBI to make informed and data-backed decisions! Source: about 1 year ago
  • Cloud dB reporting tool?
    Power BI is popular... But for table reports with Excel/PDF export you can use Pebble Reports. Source: about 1 year ago
  • Asking for guidance on migrating to a database from Excel
    Yes, MySQL can do the job. You can use Airforms to do data entry. No need to learn MySQL syntax. You will also need a reporting tool, such as Power BI. Source: about 1 year ago
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Scikit-learn mentions (27)

  • 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 / 11 months ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 12 months ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: 12 months ago
  • Help on using R for Machine Learning?
    Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
  • Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
    This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago
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What are some alternatives?

When comparing Microsoft Power BI and Scikit-learn, you can also consider the following products

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.

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

Qlik - Qlik offers an Active Intelligence platform, delivering end-to-end, real-time data integration and analytics cloud solutions to close the gaps between data, insights, and action.

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