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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Jupyter Notebook

    Score8.6 out of 10
    N/AJupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…N/A

    Supermetrics

    Score9.7 out of 10
    N/ASupermetrics, from the company of the same name in Helsinki, offers an application which automates integration of data from multiple online advertising platforms (e.g. Facebook, Google Analytics and Adwords, Bing, etc) and supports customizable presentations and visualizations of the aggregated data to make cross-platform comparisons and summaries easier for marketers.

    $29

    per month

    Pricing
    Jupyter NotebookSupermetrics
    Editions & Modules
    No answers on this topic
    Essential
    $29
    per month per user
    Core
    $159
    per month per user
    Offerings
    Pricing Offerings
    Jupyter NotebookSupermetrics
    Free Trial
    NoYes
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details—In addition to the basic licensing tiers, Supermetrics offers customized packages according to customer needs.
    More Pricing Information
    Community Pulse
    Jupyter NotebookSupermetrics
    Considered Both Products
    Open Source
    No answer on this topic
    Supermetrics
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    23 Answers
    100%
    Would buy again
    10 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    23 Answers
    100%
    Delivers good value for the price
    9 Answers
    Happy with the feature set
    96%
    Happy with the feature set
    22 Answers
    100%
    Happy with the feature set
    10 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    17 Answers
    100%
    Lived up to sales and marketing promises
    9 Answers
    Implementation went as expected
    95%
    Implementation went as expected
    20 Answers
    100%
    Implementation went as expected
    10 Answers
    Features
    Jupyter NotebookSupermetrics
    Platform Connectivity
    Comparison of Platform Connectivity features of Jupyter Notebook and Supermetrics
    Feature
    Jupyter Notebook
    9.0
    22 Ratings
    7% above category average
    Supermetrics
    -
    Ratings
    Connect to Multiple Data Sources10.022 Ratings00 Ratings
    Extend Existing Data Sources10.021 Ratings00 Ratings
    Automatic Data Format Detection8.514 Ratings00 Ratings
    MDM Integration7.415 Ratings00 Ratings
    Data Exploration
    Comparison of Data Exploration features of Jupyter Notebook and Supermetrics
    Feature
    Jupyter Notebook
    7.0
    22 Ratings
    19% below category average
    Supermetrics
    -
    Ratings
    Visualization6.022 Ratings00 Ratings
    Interactive Data Analysis8.022 Ratings00 Ratings
    Data Preparation
    Comparison of Data Preparation features of Jupyter Notebook and Supermetrics
    Feature
    Jupyter Notebook
    9.5
    22 Ratings
    15% above category average
    Supermetrics
    -
    Ratings
    Interactive Data Cleaning and Enrichment10.021 Ratings00 Ratings
    Data Transformations10.022 Ratings00 Ratings
    Data Encryption8.514 Ratings00 Ratings
    Built-in Processors9.314 Ratings00 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of Jupyter Notebook and Supermetrics
    Feature
    Jupyter Notebook
    9.3
    22 Ratings
    9% above category average
    Supermetrics
    -
    Ratings
    Multiple Model Development Languages and Tools10.021 Ratings00 Ratings
    Automated Machine Learning9.218 Ratings00 Ratings
    Single platform for multiple model development10.022 Ratings00 Ratings
    Self-Service Model Delivery8.020 Ratings00 Ratings
    Model Deployment
    Comparison of Model Deployment features of Jupyter Notebook and Supermetrics
    Feature
    Jupyter Notebook
    10.0
    20 Ratings
    16% above category average
    Supermetrics
    -
    Ratings
    Flexible Model Publishing Options10.020 Ratings00 Ratings
    Security, Governance, and Cost Controls10.019 Ratings00 Ratings
    Best Alternatives
    Jupyter NotebookSupermetrics
    Small Businesses
    RapidMiner
    Score8.9 out of 10
    Agency Analytics
    Score8.9 out of 10
    Medium-sized Companies
    Anaconda
    Score8.8 out of 10
    TrackMaven
    Score8.5 out of 10
    Enterprises
    IBM Watson Studio
    Score10 out of 10
    TrackMaven
    Score8.5 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Jupyter NotebookSupermetrics
    Likelihood to Recommend
    10.0
    (23 ratings)
    10.0
    (12 ratings)
    Usability
    10.0
    (2 ratings)
    -
    (0 ratings)
    Support Rating
    9.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Jupyter NotebookSupermetrics
    Likelihood to Recommend
    Open Source
    I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.
    Incentivized
    Read full review
    Supermetrics
    If you are looking to pull and aggregate data from multiple sources for reporting or analytics, Supermetrics is the best option for connecting those data sources into a single table. Supermetrics is less beneficial if you report on a single data source or do not need to aggregate your data into a single source.
    Incentivized
    Read full review
    Pros
    Open Source
    • Simple and elegant code writing ability. Easier to understand the code that way.
    • The ability to see the output after each step.
    • The ability to use ton of library functions in Python.
    • Easy-user friendly interface.
    Incentivized
    Read full review
    Supermetrics
    • Supermetrics is easy to use, the ui is helpful for creating queries.
    • Supermetrics allows to run the created queries on triggers.
    • Supermetrics allows to connect with different data sources like Google analytics etc .,
    • Supermetrics sends alert on the failure of queries to the desired email address
    Incentivized
    Read full review
    Cons
    Open Source
    • Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
    • Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.
    Incentivized
    Read full review
    Supermetrics
    • Sometimes I have to refer to the website to find which metrics are what - the names aren't always the same as the platform calls them.
    • No public data for LinkedIn.
    • Definitely requires knowledge on how to use Google Data Studio.
    Incentivized
    Read full review
    Usability
    Open Source
    Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.
    Incentivized
    Read full review
    Supermetrics
    No answers on this topic
    Support Rating
    Open Source
    I haven't had a need to contact support. However, all required help is out there in public forums.
    Incentivized
    Read full review
    Supermetrics
    No answers on this topic
    Alternatives Considered
    Open Source
    With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.
    Incentivized
    Read full review
    Supermetrics
    Supermetrics is better because of its ease of use and it mirrors most of the metrics on ad platforms. For some similar reporting platforms, metrics are often called something slightly different or are not able to pull the same data as presented on the ad platform; Supermetrics is the closest you'll get to exact data alignment.
    Incentivized
    Read full review
    Return on Investment
    Open Source
    • Positive impact: flexible implementation on any OS, for many common software languages
    • Positive impact: straightforward duplication for adaptation of workflows for other projects
    • Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration
    Incentivized
    Read full review
    Supermetrics
    • Positive! Supermetrics helped us transition into Google Data Studio as our monthly reporting system.
    • Savings! We saved money by switching our reporting to Google Data Studio + Supermetrics.
    • Time! We save a lot of time on our monthly reports thanks to Supermetrics.
    Incentivized
    Read full review
    ScreenShots

    Supermetrics Screenshots

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