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What is dotData?
dotData enables your organization to focus on the results of artificial intelligence and machine learning projects, simplifying the intricate data science process by automating the entire lifecycle of data science. With the ability to initiate a comprehensive AI and ML pipeline within minutes, you gain the advantage of real-time updates through continuous deployment. This groundbreaking approach expedites data science projects, cutting down timelines from months to just days thanks to automated feature engineering. By leveraging data science automation, discovering valuable insights hidden within your business becomes a hassle-free task. Traditionally, engaging with data science to build and implement accurate machine learning and AI models is often a labor-intensive and protracted process, requiring collaboration among various specialists. By automating the most monotonous and repetitive aspects of data science, you can drastically reduce the time needed for AI development, shrinking it from several months to just a few days. This transformation not only improves overall efficiency but also empowers teams to concentrate on more strategic and innovative initiatives, ultimately driving better business outcomes. Such advancements in automation are reshaping the landscape of data science, making it more accessible and effective for organizations of all sizes.
What is Kedro?
Kedro is an essential framework that promotes clean practices in the field of data science. By incorporating software engineering principles, it significantly boosts the productivity of machine-learning projects. A Kedro project offers a well-organized framework for handling complex data workflows and machine-learning pipelines. This structured approach enables practitioners to reduce the time spent on tedious implementation duties, allowing them to focus more on tackling innovative challenges. Furthermore, Kedro standardizes the development of data science code, which enhances collaboration and problem-solving among team members. The transition from development to production is seamless, as exploratory code can be transformed into reproducible, maintainable, and modular experiments with ease. In addition, Kedro provides a suite of lightweight data connectors that streamline the processes of saving and loading data across different file formats and storage solutions, thus making data management more adaptable and user-friendly. Ultimately, this framework not only empowers data scientists to work more efficiently but also instills greater confidence in the quality and reliability of their projects, ensuring they are well-prepared for future challenges in the data landscape.
Integrations Supported
Amazon SageMaker
Apache Airflow
Apache Spark
Azure Databricks
Azure Machine Learning
Dask
Docker
Gemini Enterprise Agent Platform
Jupyter Notebook
Kubeflow
API Availability
API Availability
Pricing Information
Pricing not provided
Pricing Information
Free
Free Version
Supported Platforms
SaaS
Supported Platforms
Linux
Customer Service / Support
Standard Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
Training Options
Documentation Hub
Company Facts
Organization Name
dotData
Date Founded
2018
Company Location
United States
Company Website
dotdata.com
Company Facts
Organization Name
Kedro
Company Website
kedro.org
Categories and Features
Data Science
Not specified
Categories and Features
Data Science
Not specified