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Dataiku is a comprehensive software platform for designing, deploying, and managing data analytics applications and predictive machine learning (ML) models.
The platform, which is pronounced “data-eye-coo,” is known for its collaborative features that allow data scientists and business professionals to work together on predictive models for business use.
A predictive model is a statistical tool that uses machine learning and historical data to forecast future events or outcomes. The effectiveness of this type of artificial intelligence (AI) depends on the quality of the historical data, the appropriateness of the learning algorithms used to analyze the data, and the model’s ability to apply what it learned from training data to new scenarios.
Recently, Dataiku has been promoting its Generative AI Use Case Collection for enterprise applications. The collection is intended to make it easier for enterprises to tune large language foundation models and implement generative AI at scale.
Dataiku is used to simplify and streamline the steps required to turn data into actionable insights. The platform includes tools for data preparation, exploration, and analysis, as well as tools for building, validating, testing, deploying, and governing ML models.
Dataiku Academy is an online learning center that provides registered users with free access to a limited number of guided learning paths.
The academy has an active community forum and maintains a knowledge base (library) of free tutorials, how-tos, tips, and FAQs. The academy also offers more advanced courses and certification opportunities for a fee.
Data Science Studio (Dataiku DSS) is a virtual collaboration environment. It is primarily used for the “hands-on” parts of the data science workflow, including data preparation, analysis, and model building.
DSS can be supplemented by a number of additional components for orchestrating data pipelines, deploying data products, and managing their deployments.
Dataiku offers a freemium subscription model that provides registered users with limited access to Dataiku Data Science Studio and learning resources. They also offer a tiered subscription model.
Many of Dataiku’s top competitors started out by focusing on specific features and components of the Dataiku platform.
According to Gartner Peer Insights, competitive vendors include:
As companies strive to capture a bigger share of the generative AI market, many of the vendors mentioned above are adding components and features to make their platforms more comprehensive. Arguably, Dataiku still maintains unique advantages in areas like collaboration, scalability, and user-friendliness.
Databricks marketing campaigns are aimed at enterprises that require robust big data processing capabilities. Alteryx marketing campaigns are aimed at professionals who lack deep technical knowledge but need to perform complex data analytics – and Dataiku marketing campaigns are aimed at collaboration and meeting the needs of users with varying degrees of technical and skill levels.
No, Dataiku is not a Japanese company. Dataiku was founded in France in 2013. Over time, Dataiku has expanded its presence globally, but its roots and origins are in France, not Japan.
Yes. Dataiku is considered a unicorn. In business, a unicorn refers to a privately held startup that is valued at over $1 billion. Dataiku achieved this status in August 2020 after a $100 million Series D funding round led by a growth equity firm called Stripes.
No. Dataiku includes features that facilitate data extraction, transformation, and loading, but that’s not all the platform can be used for. It may be helpful to think of Dataiku as a Swiss army knife for creating, deploying, and managing predictive AI models – and ETL is just one of the knife’s many tools.
Yes, Dataiku can be considered an AI tool because the platform enables users to build and deploy predictive machine learning models.
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Margaret is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical business audience. Over the past twenty years, her IT definitions have been published by Que in an encyclopedia of technology terms and cited in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine, and Discovery Magazine. She joined Techopedia in 2011. Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages.
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