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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Explorium

    Score7.7 out of 10
    N/AExplorium, headquartered in San Mateo, provides an External Data Platform that automatically discovers thousands of relevant data signals and uses them to improve analytics and machine learning. The automated Explorium Platform enables organizations to discover and use third party data to improve predictions and ML model performance. With faster, better insights, organizations can increase revenue, streamline operations and reduce risks.N/A

    Streamlit

    Score8 out of 10
    N/AStreamlit is an open-source Python library designed to make it easy to build custom web-apps for machine learning and data science, from the company of the same name in San Francisco. Streamlit also hosts its community's Streamlit Component offered via API to help users get started.N/A
    Pricing
    ExploriumStreamlit
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    ExploriumStreamlit
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Features
    ExploriumStreamlit
    Platform Connectivity
    Comparison of Platform Connectivity features of Explorium and Streamlit
    Feature
    Explorium
    7.8
    1 Ratings
    7% below category average
    Streamlit
    -
    Ratings
    Connect to Multiple Data Sources8.01 Ratings00 Ratings
    Extend Existing Data Sources8.01 Ratings00 Ratings
    Automatic Data Format Detection7.01 Ratings00 Ratings
    MDM Integration8.01 Ratings00 Ratings
    Data Exploration
    Comparison of Data Exploration features of Explorium and Streamlit
    Feature
    Explorium
    6.5
    1 Ratings
    25% below category average
    Streamlit
    -
    Ratings
    Visualization6.01 Ratings00 Ratings
    Interactive Data Analysis7.01 Ratings00 Ratings
    Data Preparation
    Comparison of Data Preparation features of Explorium and Streamlit
    Feature
    Explorium
    6.5
    1 Ratings
    23% below category average
    Streamlit
    -
    Ratings
    Interactive Data Cleaning and Enrichment6.01 Ratings00 Ratings
    Data Transformations6.01 Ratings00 Ratings
    Data Encryption7.01 Ratings00 Ratings
    Built-in Processors7.01 Ratings00 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of Explorium and Streamlit
    Feature
    Explorium
    7.3
    1 Ratings
    15% below category average
    Streamlit
    -
    Ratings
    Multiple Model Development Languages and Tools7.01 Ratings00 Ratings
    Automated Machine Learning8.01 Ratings00 Ratings
    Single platform for multiple model development8.01 Ratings00 Ratings
    Self-Service Model Delivery6.01 Ratings00 Ratings
    Model Deployment
    Comparison of Model Deployment features of Explorium and Streamlit
    Feature
    Explorium
    8.0
    1 Ratings
    7% below category average
    Streamlit
    -
    Ratings
    Flexible Model Publishing Options8.01 Ratings00 Ratings
    Security, Governance, and Cost Controls8.01 Ratings00 Ratings
    Best Alternatives
    ExploriumStreamlit
    Small Businesses
    RapidMiner
    Score8.9 out of 10
    TensorFlow
    Score7.6 out of 10
    Medium-sized Companies
    Anaconda
    Score8.8 out of 10
    Google Cloud AI
    Score8.7 out of 10
    Enterprises
    IBM Watson Studio
    Score10 out of 10
    Google Cloud AI
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    ExploriumStreamlit
    Likelihood to Recommend
    8.0
    (1 ratings)
    10.0
    (1 ratings)
    User Testimonials
    ExploriumStreamlit
    Likelihood to Recommend
    Explorium
    We need to constantly measures costs in our health business and we forecast pricing acoording to several values and conditions. Explorium works quite good analysing simple datasets, but when hierahies start to increase, meaning 6-10 olap variables, the system start to slow down quite a bit until was no longer to retrieve the info we required. This is why we test several tools, because even world-class solutions we purchase, don´t do the job we need. Explorium is a good tool, but complexity will be a minus in some scenarios.
    Incentivized
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    Streamlit
    - Don't want to pay Tableau $1,000 / seat? Use Streamlit - Want fully custom views and navigation? Use Streamlit - Want access to Machine Learning and not just your dev team? Use Streamlit - Want to keep things internal and secure? Use Streamlit - Want your Data Science team to be able to crank out projects quickly? Use Streamlit - Sick of Jupyter Notebooks and Business Leaders not understanding them? Use Streamlit Our D.S. strategy has moved completely to delivering pages in Streamlit. I can hand an executive a Jupyter notebook and it'll get lost in translation. I can give them sign-in access to a page and they can answer all of their own "What-If?" questions! We've used Streamlit to productize our Data Science and Machine Learning capabilities.
    Incentivized
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    Pros
    Explorium
    • Data ready for consumption.
    • Good enough relationships between entities.
    • Nice integration with other players. That's a good thing.
    Incentivized
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    Streamlit
    • Incredibly Easy
    • Customizable
    • Quick and powerful
    Incentivized
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    Cons
    Explorium
    • relationships between entities could be better. Would be great to have scenarios.
    • The data normalized needs improvement. Works pretty good, but it needs more refinement when using AND-OR Formulas that came from various datasets.
    Incentivized
    Read full review
    Streamlit
    • Recent Security issues (they quickly released an update to combat this though...)
    • Requires a bit of HTML knowledge to really customize. If you're going quick, you don't need HTML though. Streamlit commands will pump your page out fast.
    Incentivized
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    Alternatives Considered
    Explorium
    The simplicity of the tool is an advantage. The integrations as well work quite well. All these solutions have worked well until some point and what we have discovered over the years is that we need to combine various solutions. There is no such thing as one tool ruling them all. Explorium works quite well until we start testing more advanced relations, and here, the tool is promising but requires a little work.
    Incentivized
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    Streamlit
    I started using Streamlit when it first came out and thought it was really useful and powerful. A few years later and they've really hit their stride! The features / widgets / materials they provide have been well researched, well designed, and well implemented. I will take Streamlit to any future companies I go to as well as be a strong promoter wherever I'm currently at. It's free. It's easy to use. It is really powerful. Sure? You could go pay for a larger system but your Data Science team should be able to handle Streamlit easily. I'd argue a non-technical person spending a few weeks in python could pick up Streamlit really quickly.
    Incentivized
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    Return on Investment
    Explorium
    • Positive. The time save in analysis per hour of internal consulting was the best compared to our SAP and Cognos solutions.
    • In term of objetives works as stated, but when using multi-conditions of dataset, start the issues.
    Incentivized
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    Streamlit
    • I've scaled my team 2x since using Streamlit. We show off actual results that users can play with
    • We're building a customer facing page that we're going to monetize.
    • Incredible amounts of visibility into my team and what we're accomplishing.
    Incentivized
    Read full review
    ScreenShots