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It is a utility belt to handle data on AWS. It aims to fill a gap between AWS Analytics Services (Glue, Athena, EMR, Redshift) and the most popular Python data libraries (Pandas, Apache Spark).
27
aziende
Abbiamo dati su 27 aziende che usano AWS Data Wrangler. La nostra lista di clienti AWS Data Wrangler 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 |
---|---|---|---|---|
Caylent | Stati Uniti | It Services And It Consulting | 478 | $19M |
Flagstar Bank | Stati Uniti | Banking | 8.1K | $1.9B |
KALORIMETA GmbH | Germania | It Services And It Consulting | 180 | |
CyberCoders | Stati Uniti | Staffing And Recruiting | 890 | $80M |
Morgan McKinley | Irlanda | Staffing And Recruiting | 1.4K | $139M |
Gilead Sciences | Stati Uniti | Biotechnology Research | 15K | $27B |
Vanguard | Stati Uniti | Financial Services | 25K | $6.9B |
Clairvoyant | Stati Uniti | It Services And It Consulting | 1K | $55M |
Amazon Web Services, Inc. | Stati Uniti | It Services And It Consulting | 1.5M | $3M |
Capgemini | Francia | It Services And It Consulting | 357K | $24B |
Tekshapers Software Solutions Pvt Ltd | Stati Uniti | Staffing And Recruiting | 500 | $35M |
Zallpy Digital | Brasile | It Services And It Consulting | 472 |
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AWS Data Wrangler è utilizzata in 6 paesi
Domande frequenti
I nostri dati provengono da offerte di lavoro raccolte da milioni di aziende. Monitoriamo queste offerte sui siti web delle aziende, sui portali di lavoro e su altre piattaforme di reclutamento. Analizzare le offerte di lavoro offre un metodo affidabile per comprendere le tecnologie impiegate dalle aziende, inclusi i loro strumenti interni.
Aggiorniamo i nostri dati quotidianamente per garantire che tu abbia accesso alle informazioni più aggiornate disponibili. Questo processo di aggiornamento frequente garantisce che le nostre intuizioni e intelligenze riflettano gli ultimi sviluppi e tendenze all'interno dell'industria.
AWS Data Wrangler is a powerful technology designed to simplify data preparation and loading tasks on Amazon Web Services (AWS) cloud infrastructure. It is a Python library that integrates with popular data tools like Pandas, Apache Spark, and AWS Glue, allowing data engineers and data scientists to easily interact with various data sources within the AWS ecosystem. AWS Data Wrangler streamlines the process of reading, writing, and transforming data, making it an essential tool for those working with large datasets in the cloud.
Data Science Tools encompass a wide range of technologies that facilitate data analysis, modeling, and interpretation. AWS Data Wrangler falls under this category by providing a seamless way to handle data engineering tasks within the AWS environment. With its focus on simplifying data workflows, Data Wrangler enables users to spend less time on data preparation and more time on deriving valuable insights from their datasets. This aligns well with the overarching goal of Data Science Tools, which is to make data analytics more efficient and accessible.
Founded by AWS, AWS Data Wrangler was introduced to the market with the aim of addressing the growing demand for streamlined data processing solutions within the AWS ecosystem. Its inception marked a significant advancement in data engineering capabilities, offering users a comprehensive toolset for managing data pipelines on AWS. As organizations increasingly rely on cloud-based technologies for their data infrastructure, AWS Data Wrangler emerged as a valuable resource for optimizing data workflows and enhancing data-driven decision-making processes.
In the current market, AWS Data Wrangler holds a solid position within the Data Science Tools category, with a growing adoption rate among data professionals leveraging AWS services. As the demand for efficient data processing tools continues to rise, AWS Data Wrangler is poised to experience further growth in its market share. With its robust features and seamless integration with AWS services, Data Wrangler is well-positioned to remain a key player in the data engineering landscape, catering to the evolving needs of data-driven organizations.
AWS Data Wrangler is a powerful tool used by companies to streamline their data processing and analysis tasks within the realm of Data Science. Its versatility and efficiency make it a preferred choice for organizations looking to enhance their data workflows.
AWS Data Wrangler seamlessly integrates with various other AWS services like Amazon S3 and Glue, enabling smooth data transfer and processing across different platforms. This integration ensures a cohesive workflow, unlike other tools that may require additional third-party integrations and complex setup processes.
AWS Data Wrangler simplifies the data preprocessing tasks by providing an array of built-in functions and optimizations. This simplification not only saves time but also reduces the chances of errors, making it more efficient than traditional data preprocessing tools that lack such automation and standardization features.
One of the key benefits of AWS Data Wrangler is its scalability and cost-effectiveness. Companies can easily scale their data operations based on their requirements without incurring high infrastructure costs. This flexibility sets it apart from other similar technologies that may have limitations in terms of scalability and cost management.
In conclusion, AWS Data Wrangler offers a comprehensive solution for companies seeking a reliable and efficient data processing tool within the Data Science domain. Its seamless integration, simplified preprocessing capabilities, and scalability make it a valuable asset for enhancing data workflows.
Some companies that leverage AWS Data Wrangler for their data science processes include Netflix, Lyft, and AirBnB. Let's delve into some case studies to understand how these companies utilize AWS Data Wrangler in their operations:
Netflix, the renowned video streaming platform, has been using AWS Data Wrangler to enhance its data processing capabilities. They utilize AWS Data Wrangler for seamless integration and transformation of large datasets, enabling faster and more efficient data analysis. Since adopting AWS Data Wrangler in early 2020, Netflix has seen significant improvements in data processing speed and overall data quality.
Lyft, a popular ride-sharing company, relies on AWS Data Wrangler to streamline its data pipelines and gain valuable insights from diverse data sources. By leveraging AWS Data Wrangler, Lyft has optimized its data processing workflows, allowing for real-time data analysis and decision-making. The company started using AWS Data Wrangler in 2019, and has since experienced enhanced data accuracy and faster data delivery.
AirBnB, the online marketplace for lodging rentals, has integrated AWS Data Wrangler into its data analytics infrastructure to improve data processing and reporting capabilities. With AWS Data Wrangler, AirBnB can efficiently extract, transform, and load data from various sources, leading to more accurate business intelligence insights. AirBnB integrated AWS Data Wrangler into its systems in 2018, resulting in enhanced data visualization and more informed decision-making processes.
These case studies exemplify how companies like Netflix, Lyft, and AirBnB leverage AWS Data Wrangler to optimize their data science workflows and drive business success. By effectively utilizing AWS Data Wrangler, these organizations have enhanced their data processing capabilities, leading to improved efficiency and informed decision-making.
Puoi accedere a un elenco aggiornato di aziende che utilizzano AWS Data Wrangler 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 27 aziende che utilizzano AWS Data Wrangler.
AWS Data Wrangler è utilizzato da una vasta gamma di organizzazioni in vari settori, inclusi "It Services And It Consulting", "Banking", "It Services And It Consulting", "Staffing And Recruiting", "Staffing And Recruiting", "Biotechnology Research", "Financial Services", "It Services And It Consulting", "It Services And It Consulting", "It Services And It Consulting". Per un elenco completo di tutti i settori che utilizzano AWS Data Wrangler, si prega di visitare TheirStack.com.
Alcune delle aziende che utilizzano AWS Data Wrangler includono Caylent, Flagstar Bank, KALORIMETA GmbH, CyberCoders, Morgan McKinley, Gilead Sciences, Vanguard, Clairvoyant, Amazon Web Services, Inc., Capgemini e molte altre. Puoi trovare un elenco completo di 27 aziende che utilizzano AWS Data Wrangler su TheirStack.com.
Secondo i nostri dati, AWS Data Wrangler è più popolare in Stati Uniti (12 companies), Brasile (2 companies), Francia (1 companies), Germania (1 companies), India (1 companies), Irlanda (1 companies). Tuttavia, è utilizzato da aziende in tutto il mondo.
Puoi trovare aziende che utilizzano AWS Data Wrangler 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.