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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
companies
We have data on 27 companies that use AWS Data Wrangler. Our AWS Data Wrangler customers list is available for download and comes enriched with vital company specifics, including industry classification, organizational size, geographical location, funding rounds, and revenue figures, among others.
Company | Country | Industry | Employees | Revenue |
---|---|---|---|---|
Caylent | United States | It Services And It Consulting | 478 | $19M |
Flagstar Bank | United States | Banking | 8.1K | $1.9B |
KALORIMETA GmbH | Germany | It Services And It Consulting | 180 | |
CyberCoders | United States | Staffing And Recruiting | 890 | $80M |
Morgan McKinley | Ireland | Staffing And Recruiting | 1.4K | $139M |
Gilead Sciences | United States | Biotechnology Research | 15K | $27B |
Vanguard | United States | Financial Services | 25K | $6.9B |
Clairvoyant | United States | It Services And It Consulting | 1K | $55M |
Amazon Web Services, Inc. | United States | It Services And It Consulting | 1.5M | $3M |
Capgemini | France | It Services And It Consulting | 357K | $24B |
Tekshapers Software Solutions Pvt Ltd | United States | Staffing And Recruiting | 500 | $35M |
Zallpy Digital | Brazil | It Services And It Consulting | 472 |
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Technoloy Usage Stadistics and Market Share
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AWS Data Wrangler is used in 6 countries
There are 28 alternatives to AWS Data Wrangler
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Frequently asked questions
Our data is sourced from job postings collected from millions of companies. We monitor these postings on company websites, job boards, and other recruitment platforms. Analyzing job postings provides a reliable method to understand the technologies companies are employing, including their use of internal tools.
We refresh our data daily to ensure you are accessing the most current information available. This frequent updating process guarantees that our insights and intelligence reflect the latest developments and trends within the industry.
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.
You can access an updated list of companies using AWS Data Wrangler by visiting TheirStack.com. Our platform provides a comprehensive database of companies utilizing various technologies and internal tools.
As of now, we have data on 27 companies that use AWS Data Wrangler.
AWS Data Wrangler is used by a diverse range of organizations across various industries, including "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". For a comprehensive list of all industries utilizing AWS Data Wrangler, please visit TheirStack.com.
Some of the companies that use AWS Data Wrangler include Caylent, Flagstar Bank, KALORIMETA GmbH, CyberCoders, Morgan McKinley, Gilead Sciences, Vanguard, Clairvoyant, Amazon Web Services, Inc., Capgemini and many more. You can find a complete list of 27 companies that use AWS Data Wrangler on TheirStack.com.
Based on our data, AWS Data Wrangler is most popular in United States (12 companies), Brazil (2 companies), France (1 companies), Germany (1 companies), India (1 companies), Ireland (1 companies). However, it is used by companies all over the world.
You can find companies using AWS Data Wrangler by searching for it on TheirStack.com, We track job postings from millions of companies and use them to discover what technologies and internal tools they are using.