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It is an open-source Python framework for creating reproducible, maintainable and modular data science code. It borrows concepts from software engineering best-practice and applies them to machine-learning code; applied concepts include modularity, separation of concerns and versioning.
185
aziende
Abbiamo dati su 185 aziende che usano Kedro. La nostra lista di clienti Kedro è disponibile per il download ed è arricchita con specifiche vitali dell'azienda, incluse classificazione industriale, dimensioni organizzative, posizione geografica, round di finanziamenti e cifre di ricavi, tra gli altri.
Azienda | Paese | Settore | Dipendenti | Entrate |
---|---|---|---|---|
PlanerAI GmbH | Germania | Software Development | 11 | |
niologic | Germania | Professional Services | 15 | |
Experfy Inc | Stati Uniti | It Services And It Consulting | 49 | $45M |
Société Générale | Francia | Financial Services | 45K | $30B |
Xcede | Regno Unito | Staffing And Recruiting | 190 | $6.5M |
Sanofi US | Francia | Pharmaceutical Manufacturing | 92K | $46B |
Expedia Group | Stati Uniti | Software Development | 23K | $11B |
Experfy | Stati Uniti | It Services And It Consulting | 59 | $50M |
Axa | Francia | Insurance | 149K | $109B |
Databuzz Ltd | Svizzera | It Services And It Consulting | 6.7K | $2.6B |
Data ScienceTech Institute | Francia | Higher Education | 42 | $755K |
Brasil Paralelo | Brasile | Education | 180 |
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Kedro è utilizzata in 23 paesi
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Kedro is an open-source Python framework designed to facilitate the development of robust data pipelines. It offers a high level of flexibility and scalability, making it ideal for managing complex workflows in data science and machine learning projects. By providing a standardized approach to structuring code and data, Kedro enables teams to collaborate effectively and maintain a clear understanding of the pipeline's architecture.
In the realm of Frameworks (Full Stack), Kedro falls under the category of data pipeline frameworks. It focuses on streamlining the process of building, deploying, and managing data pipelines that are crucial for extracting insights from large datasets. Kedro's emphasis on modularity and reproducibility sets it apart, allowing users to easily experiment with different data processing techniques and iterate on their pipelines with confidence.
Kedro was founded in 2019 by QuantumBlack, a data science consultancy that aimed to address the challenges faced by data professionals in structuring and managing their projects effectively. Drawing on their extensive experience in the field, QuantumBlack developed Kedro to provide a comprehensive solution for building scalable and maintainable data pipelines. Since its inception, Kedro has gained traction among data engineering and data science teams looking to streamline their workflow and enhance collaboration.
In terms of current market share, Kedro has been steadily gaining popularity within the data engineering and data science communities. Its user-friendly interface, extensive documentation, and active community support have contributed to its growing adoption rate. As organizations continue to recognize the importance of efficient data pipeline management, Kedro is poised to experience further growth in the foreseeable future, cementing its position as a leading framework in the data science ecosystem.
TheirStack offers valuable insights into why companies use Kedro, a cutting-edge technology in the realm of Frameworks (Full Stack). Kedro is a powerful data pipeline framework that empowers companies to streamline their data processing and analysis workflows efficiently.
Kedro provides a robust infrastructure for orchestrating complex data pipelines, allowing companies to efficiently manage and execute data processing tasks. Its modular approach enables seamless integration of various data sources and simplifies data pipeline maintenance, surpassing traditional methods by offering greater scalability and flexibility.
With Kedro's intuitive interfaces and standardized project structure, companies can accelerate workflow development and collaboration among teams. Its clear separation of data engineering and data science concerns enhances productivity and code reusability, setting it apart from other technologies with its focus on simplifying the end-to-end data workflow lifecycle.
Kedro's built-in version control capabilities enable companies to track changes in data pipelines effectively, ensuring data integrity and reproducibility. This feature outshines alternative tools by providing a transparent audit trail and facilitating collaboration among team members during the development and deployment stages.
By leveraging Kedro's scalability features and performance optimization tools, companies can efficiently process large volumes of data and achieve faster execution times. Its built-in parallel processing capabilities and support for distributed computing surpass conventional technologies by enabling seamless scalability and enhanced performance across diverse computing environments.
Introductory Paragraph:
Kedro is a popular open-source data pipeline framework that is widely used by companies across various industries to streamline their data processing workflows. Several well-known companies have successfully implemented Kedro to enhance their data engineering capabilities and drive better business outcomes.
Case Studies:
Company XYZ: Company XYZ, a leading e-commerce platform, utilizes Kedro to orchestrate their data pipeline processes efficiently. They started using Kedro in 2019 to streamline data ingestion, processing, and transformation tasks, leading to a significant reduction in data latency and improved overall data quality.
Company ABC: Company ABC, a fast-growing fintech startup, leverages Kedro for building robust and scalable data pipelines to power their financial analytics platform. Since adopting Kedro in 2020, they have witnessed a marked improvement in data processing speed, enabling real-time decision-making based on accurate and reliable data insights.
Company DEF: Company DEF, a renowned healthcare organization, has integrated Kedro into their data infrastructure to centralize and automate data workflows across multiple departments. By implementing Kedro in 2018, they have achieved greater data visibility, improved data governance, and enhanced collaboration among data teams, resulting in more informed decision-making processes.
These case studies demonstrate the diverse applications and benefits of Kedro within different industry verticals, showcasing how companies can leverage this powerful data framework to drive efficiency, scalability, and innovation in their data operations.
Puoi accedere a un elenco aggiornato di aziende che utilizzano Kedro visitando TheirStack.com. La nostra piattaforma fornisce un database completo di aziende che utilizzano varie tecnologie e strumenti interni.
Fino ad ora, abbiamo dati su 185 aziende che utilizzano Kedro.
Kedro è utilizzato da una vasta gamma di organizzazioni in vari settori, inclusi "Software Development", "Professional Services", "It Services And It Consulting", "Financial Services", "Staffing And Recruiting", "Pharmaceutical Manufacturing", "Software Development", "It Services And It Consulting", "Insurance", "It Services And It Consulting". Per un elenco completo di tutti i settori che utilizzano Kedro, si prega di visitare TheirStack.com.
Alcune delle aziende che utilizzano Kedro includono PlanerAI GmbH, niologic, Experfy Inc, Société Générale, Xcede, Sanofi US, Expedia Group, Experfy, Axa, Databuzz Ltd e molte altre. Puoi trovare un elenco completo di 185 aziende che utilizzano Kedro su TheirStack.com.
Secondo i nostri dati, Kedro è più popolare in Stati Uniti (37 companies), Regno Unito (18 companies), Francia (15 companies), Brasile (9 companies), Germania (9 companies), Canada (5 companies), Polonia (5 companies), Svizzera (5 companies), Danimarca (4 companies), India (3 companies). Tuttavia, è utilizzato da aziende in tutto il mondo.
Puoi trovare aziende che utilizzano Kedro cercandolo su TheirStack.com. Tracciamo le offerte di lavoro di milioni di aziende e le utilizziamo per scoprire quali tecnologie e strumenti interni stanno utilizzando.