使用 Dask 的公司

常见问题

这些数据的来源是什么?

我们的数据来自于从数百万家公司收集的招聘信息。我们在公司网站、招聘平台和其他招聘平台上监控这些招聘信息。分析招聘信息提供了一种可靠的方法来了解公司正在使用的技术，包括他们使用的内部工具。

数据多久更新一次?

我们每天更新数据，以确保您访问的是最新的可用信息。这一频繁的更新过程保证了我们的洞察力和情报反映了行业内的最新发展和趋势。

什么是Dask?

Dask is a flexible parallel computing library in Python that enables seamless execution of complex computations. It provides advanced parallel and distributed computing capabilities to tackle tasks that involve large datasets, thus making it an essential tool for data scientists and engineers. Dask allows users to scale their data-intensive applications from a single machine to a cluster of machines, effectively managing the distribution of workloads and optimizing performance.

In the realm of Data Science Tools, Dask falls under the category of distributed computing frameworks. Its primary focus is on enabling efficient parallel processing of data, making it particularly valuable for tasks like data manipulation, machine learning model training, and large-scale data analysis. By leveraging Dask, users can overcome the limitations of traditional single-node computing and explore new possibilities in handling big data workloads with ease.

Founded in 2015 by the team at Anaconda, Dask originated from the need to address the challenges posed by the growing demand for scalable data processing in the Python ecosystem. Motivated by the desire to provide a flexible and user-friendly solution for parallel computing, the creators of Dask set out to develop a tool that could seamlessly integrate with existing Python data libraries while offering enhanced performance and scalability.

Currently, Dask maintains a strong foothold in the data science and scientific computing domains, attracting a growing user base due to its versatility and efficiency in handling large-scale computational tasks. With an increasing demand for scalable data processing solutions, Dask's market share within the Data Science Tools category is expected to experience significant growth in the coming years. As organizations continue to grapple with ever-expanding datasets and the need for faster processing speeds, Dask's role in enabling efficient parallel computing is likely to become even more pronounced, solidifying its position as a leading technology in the field.

如何获得使用Dask的公司的最新列表？

您可以访问 TheirStack.com，获取使用 Dask 的公司更新名单。我们的平台提供了一个全面的数据库，涵盖了使用各种技术和内部工具的公司。

Dask 有多少客户？

截至目前，我们拥有关于 1,767 家使用 Dask 的公司的数据。

谁在使用Dask?

Dask 被广泛应用于包括 "Financial Services", "Business Consulting And Services", "Defense And Space Manufacturing", "Software Development", "Defense And Space Manufacturing", "Financial Services", "Software Development", "Software Development", "Environmental Services" 在内的各个行业的各种组织中。欲了解所有使用 Dask 的行业的完整列表，请访问 TheirStack.com。

哪些公司使用Dask?

一些使用Dask的公司包括Capital One, Bain & Company, STR, Systems & Technology Research, Domino Data Lab, BlackSky, Checkout.com, InstaDeep, Doctrine, Pachama以及更多公司。您可以在TheirStack.com上找到使用Dask的1,767家公司完整列表。

哪些国家使用Dask最多？

根据我们的数据，Dask 在 美国 (691 companies), 英国 (144 companies), 法国 (62 companies), 印度 (48 companies), 加拿大 (45 companies), 德国 (36 companies), 西班牙 (24 companies), 比利时 (14 companies), 荷兰 (13 companies), 波兰 (12 companies) 最受欢迎。然而，它被全世界的公司所使用。

如何找到使用Dask的公司？

您可以在TheirStack.com上搜索Dask，来找到使用该技术的公司。我们跟踪数百万家公司的招聘信息，并借此发现他们正在使用的技术和内部工具。