Data Science is abounding. It considers different realms of the data world including its preparation, cleaning, modeling, and whatnot. To be precise, it is massive in terms of the span it covers and the opportunities it offers. Needless to say, the job of a data scientist holds no difference. Right from the early stages of data collection to data visualization, there is a plethora of challenging tasks that accompanies the day-to-day work of a data scientist.

数据科学比比皆是。 它考虑了数据世界的不同领域，包括数据准备，清理，建模等等。 确切地说，就其覆盖范围和提供的机会而言，它是巨大的。 不用说，数据科学家的工作没有任何区别。 从数据收集的早期阶段到数据可视化，数据科学家的日常工作伴随着众多挑战性任务。

Well, if you are a pro at coding then these tasks become a bit easier because there are infinite resources to help you out. But, what about the individuals who are equally passionate about the job but have not been in touch with coding? It wouldn’t be fair enough to eliminate them from the list of potential candidates who might prove as a great addition to them. After all, data science is not only about coding.

好吧，如果您是编码专家，那么这些任务就会变得容易一些，因为有无穷的资源可以帮助您。 但是，那些同样热爱这份工作却没有接触过编码的人呢？ 将他们从可能证明对他们有很大帮助的潜在候选人名单中排除，这还不够公平。 毕竟，数据科学不仅与编码有关。

Therefore, in this article, we will talk about a fantastic software that is aimed at assisting data scientists and data science enthusiasts to solve complex problems with little or no coding knowledge at all. And, as you might have guessed by the title of this article, the name of the software is KNIME.

因此，在本文中，我们将讨论一种出色的软件，该软件旨在帮助数据科学家和数据科学爱好者完全不用或几乎不用编码知识就能解决复杂的问题。 并且，如您可能已经对本文标题所猜测的那样，该软件的名称为KNIME。

Since this article is a brief introduction about KNIME, we will structure the content as follows:

由于本文是有关KNIME的简要介绍，因此我们将其内容安排如下：

1. History behind KNIME

   KNIME背后的历史

2. What is KNIME?

   什么是KNIME？

3. How does the KNIME tool function?

   KNIME工具如何起作用？

4. Features of the KNIME tool

   KNIME工具的功能

5. Current applications and usage of the KNIME tool

   KNIME工具的当前应用程序和用法

KNIME背后的历史 (The history behind KNIME)

KNIME’s development journey began in the year 2004. A team of software engineers at the University of Konstanz, headed by Michael Berthold, developed KNIME as proprietary software. The main motive behind its creation was the need for a robust platform that could easily perform data-related tasks and allow for efficient integration of other services as well. Finally, in the year 2006, KNIME’s first version was released. The charismatic experience that KNIME created within its few years of release, helped KNIME achieve the recognition of the best data science platform in the year 2009 by Gartner. The pharmaceutical companies now started adopting KNIME for their data-related tasks. By now, even the data science vendors had accustomed to its usage. The year 2012 reported more than 15,000 users of KNIME approximately.

KNIME的开发之旅始于2004年。由Michael Berthold领导的康斯坦茨大学软件工程师团队将KNIME开发为专有软件。 其创建的主要动机是需要一个强大的平台，该平台可以轻松地执行与数据相关的任务，并且还可以有效集成其他服务。 最终，在2006年，KNIME的第一个版本发布了。 KNIME在发布的几年中创造的超凡魅力经验，帮助KNIME获得了Gartner评选的2009年最佳数据科学平台的认可。 制药公司现在开始采用KNIME来完成与数据相关的任务。 到目前为止，甚至数据科学供应商也已经习惯了它的用法。 2012年，大约有15,000名KNIME用户。

什么是KNIME？ (What is KNIME?)

KNIME is a free and open-source platform that performs tasks of the data science domain. It allows for the execution of several data mining and machine learning techniques by using a pipelining concept. In addition to that, the presence of an interactive GUI with JDBC support allows the data vendors and other users to establish efficient integrations with different sources. KNIME has been written in the JAVA programming language and is based on the Eclipse IDE.

KNIME是一个免费的开源平台，可以执行数据科学领域的任务。 它使用流水线概念允许执行多种数据挖掘和机器学习技术。 除此之外，具有JDBC支持的交互式GUI的存在使数据供应商和其他用户可以与不同源建立有效的集成。 KNIME已使用JAVA编程语言编写，并且基于Eclipse IDE。

KNIME工具如何起作用？ (How does the KNIME tool function?)

KNIME is a tool that helps in the productionization of data science. In simple terms, the entire KNIME functionality is divided into two major phases- creation and productionization. The creation phase starts with data collection and wrangling which allows almost every and any source of data to be connected for the data science task; be it an excel file, a database, or a file reader.

KNIME是有助于数据科学生产的工具。 简单来说，整个KNIME功能分为两个主要阶段：创建和生产。 创建阶段从数据收集和整理开始，这几乎允许为数据科学任务连接所有数据源。 可以是Excel文件，数据库或文件读取器。

Coming to the next phase which is modeling and visualization, KNIME supports the integration of diverse tools, R and Python integrations, statistical analysis, and integration of large open-source projects. This type of additions and timely updates to the software helps one keep in pace with the technological advancements and allows efficient and easy execution of the complex machine learning problems.

进入下一阶段，即建模和可视化，KNIME支持各种工具的集成，R和Python的集成，统计分析以及大型开源项目的集成。 这种对软件的添加和及时更新可以帮助人们跟上技术进步的步伐，并可以高效，轻松地执行复杂的机器学习问题。

Finally, in the production stage that mainly includes the deployment, customization, and optimization of the data science solutions, KNIME supports the collaboration of known tools to deliver useful business insights. Also, the leveraging of these insights become extremely easy with the help of KNIME as it supports immediate feedback mechanisms for improving the business insights.

最后，在主要包括数据科学解决方案的部署，定制和优化的生产阶段，KNIME支持已知工具的协作以提供有用的业务见解。 此外，借助KNIME，利用这些见解变得极为容易，因为它支持即时反馈机制来改善业务见解。

KNIME工具的功能 (Features of the KNIME tool)

KNIME offers a variety of features depending on the business needs. Some of its features are listed below:

KNIME根据业务需求提供各种功能。 下面列出了其某些功能：

1. Free and open source.
   免费和开源。
2. Continuous integration of services.
   不断整合服务。
3. Design and development of data workflows.
   数据工作流的设计和开发。
4. Reusable components
   可重复使用的组件
5. Deployment of analytical solutions.
   部署分析解决方案。
6. KNIME server allows the newbies to get access to data science via the KNIME web portal.
   KNIME服务器允许新手通过KNIME Web门户访问数据科学。
7. KNIME server allows the use of RESTful APIs.
   KNIME服务器允许使用RESTful API。
8. Supports extensions.
   支持扩展。
9. Supports Integration.
   支持集成。
10. Allows the entire data science cycle right from the ETL phase to the deployment of solutions.
    允许从ETL阶段到解决方案部署的整个数据科学周期。

KNIME工具的当前用法和应用 (Current usage and applications of KNIME tool)

The current applications of KNIME tool include:

KNIME工具的当前应用包括：

1. Chemical Informatics.
   化学信息学。
2. Analysis of nanoparticles.
   纳米颗粒的分析。
3. Natural Language Processing.
   自然语言处理。
4. Data Analysis and Visualisation.
   数据分析和可视化。
5. Machine learning and any sort of data science tasks.
   机器学习和任何种类的数据科学任务。

In conclusion, I would like to say that KNIME is absolute bliss in the field of data science. If you ever feel like you need a tool that can help you out with the data science task, go ahead, and explore the features that KNIME has to offer. It’s not only a great tool but also a great companion to help the newbies develop a clear cut understanding of how data science and analytics function right from scratch.

最后，我要说的是，KNIME在数据科学领域是绝对的幸福。 如果您觉得自己需要一个可以帮助您完成数据科学任务的工具，请继续并探索KNIME必须提供的功能。 它不仅是一个很好的工具，而且还是一个很好的伴侣，可以帮助新手从一开始就清楚地了解数据科学和分析的功能。

I hope this article was able to help you get accustomed to the basics of what KNIME does and what are the functionalities it offers. Even I am new to this tool and I’m trying my best to learn about it. So, stay tuned cause I will be posting more articles about this amazing software.

我希望本文能够帮助您熟悉KNIME的基本功能以及它提供的功能。 甚至我对这个工具都不熟悉，我也在尽力去了解它。 因此，敬请关注，因为我将发布更多有关此出色软件的文章。

Happy Reading :)

快乐阅读：)