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Dataiku

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Tableau

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7
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Dataiku vs Tableau: What are the differences?

What is Dataiku? Data science platform. It is the platform democratizing access to data and enabling enterprises to build their own path to AI in a human-centric way.

What is Tableau? Tableau helps people see and understand data. 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.

Dataiku belongs to "Data Science Tools" category of the tech stack, while Tableau can be primarily classified under "Business Intelligence".

Some of the features offered by Dataiku are:

  • Spend more time on high-impact AI projects
  • The power of AI + your business expertise = unlimited opportunity
  • Leverage the power of AI in every business decision for transformative impact

On the other hand, Tableau provides the following key features:

  • Connect to data on prem or in the cloud—whether it’s big data, a SQL database, a spreadsheet, or cloud apps like Google Analytics and Salesforce. Access and combine disparate data without writing code. Power users can pivot, split, and manage metadata to optimize data sources. Analysis begins with data. Get more from yours with Tableau.
  • Exceptional analytics demand more than a pretty dashboard. Quickly build powerful calculations from existing data, drag and drop reference lines and forecasts, and review statistical summaries. Make your point with trend analyses, regressions, and correlations for tried and true statistical understanding. Ask new questions, spot trends, identify opportunities, and make data-driven decisions with confidence.
  • Answer the “where” as well as the “why.” Create interactive maps automatically. Built-in postal codes mean lightning-fast mapping for more than 50 countries worldwide. Use custom geocodes and territories for personalized regions, like sales areas. We designed Tableau maps specifically to help your data stand out.

According to the StackShare community, Tableau has a broader approval, being mentioned in 168 company stacks & 588 developers stacks; compared to Dataiku, which is listed in 5 company stacks and 9 developer stacks.

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Pros of Dataiku
Pros of Tableau
    Be the first to leave a pro
    • 5
      Capable of visualising billions of rows
    • 1
      Intuitive and easy to learn
    • 1
      Responsive

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    Cons of Dataiku
    Cons of Tableau
      Be the first to leave a con
      • 1
        Very expensive for small companies

      Sign up to add or upvote consMake informed product decisions

      What is Dataiku?

      It is the platform democratizing access to data and enabling enterprises to build their own path to AI in a human-centric way.

      What is 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.

      Need advice about which tool to choose?Ask the StackShare community!

      Jobs that mention Dataiku and Tableau as a desired skillset
      CBRE
      Philippines National Capital Region Makati City
      CBRE
      India Telangana Hyderabad
      CBRE
      United States of America New York New York City
      CBRE
      India Telangana Hyderabad
      What companies use Dataiku?
      What companies use Tableau?
      See which teams inside your own company are using Dataiku or Tableau.
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      Sign up to get full access to all the companiesMake informed product decisions

      What tools integrate with Dataiku?
      What tools integrate with Tableau?
        No integrations found

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        What are some alternatives to Dataiku and Tableau?
        NumPy
        Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
        Pandas
        Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.
        SciPy
        Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
        Dataform
        Dataform helps you manage all data processes in your cloud data warehouse. Publish tables, write data tests and automate complex SQL workflows in a few minutes, so you can spend more time on analytics and less time managing infrastructure.
        Anaconda
        A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.
        See all alternatives