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.

數據科學比比皆是。 它考慮了數據世界的不同領域，包括數據準備，清理，建模等等。 確切地說，就其覆蓋范圍和提供的機會而言，它是巨大的。 不用說，數據科學家的工作沒有任何區別。 從數據收集的早期階段到數據可視化，數據科學家的日常工作伴隨著眾多挑戰性任務。

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，如果您是編碼專家，那么這些任務就會變得容易一些，因為有無窮的資源可以幫助您。 但是，那些同樣熱愛這份工作卻沒有接觸過編碼的人呢？ 將他們從可能證明對他們有很大幫助的潛在候選人名單中排除，這還不夠公平。 畢竟，數據科學不僅與編碼有關。

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，我們將討論一種出色的軟件，該軟件旨在幫助數據科學家和數據科學愛好者完全不用或幾乎不用編碼知識就能解決復雜的問題。 并且，如您可能已經對本文標題所猜測的那樣，該軟件的名稱為KNIME。

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

由于本文是有關KNIME的簡要介紹，因此我們將其內容安排如下：

1. History behind KNIME

   KNIME背后的歷史

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工具的當前應用程序和用法

KNIME背后的歷史 (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的開發之旅始于2004年。由Michael Berthold領導的康斯坦茨大學軟件工程師團隊將KNIME開發為專有軟件。 其創建的主要動機是需要一個強大的平臺，該平臺可以輕松地執行與數據相關的任務，并且還可以有效集成其他服務。 最終，在2006年，KNIME的第一個版本發布了。 KNIME在發布的幾年中創造的超凡魅力經驗，幫助KNIME獲得了Gartner評選的2009年最佳數據科學平臺的認可。 制藥公司現在開始采用KNIME來完成與數據相關的任務。 到目前為止，甚至數據科學供應商也已經習慣了它的用法。 2012年，大約有15,000名KNIME用戶。

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是一個免費的開源平臺，可以執行數據科學領域的任務。 它使用流水線概念允許執行多種數據挖掘和機器學習技術。 除此之外，具有JDBC支持的交互式GUI的存在使數據供應商和其他用戶可以與不同源建立有效的集成。 KNIME已使用JAVA編程語言編寫，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是有助于數據科學生產的工具。 簡單來說，整個KNIME功能分為兩個主要階段：創建和生產。 創建階段從數據收集和整理開始，這幾乎允許為數據科學任務連接所有數據源。 可以是Excel文件，數據庫或文件讀取器。

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.

進入下一階段，即建模和可視化，KNIME支持各種工具的集成，R和Python的集成，統計分析以及大型開源項目的集成。 這種對軟件的添加和及時更新可以幫助人們跟上技術進步的步伐，并可以高效，輕松地執行復雜的機器學習問題。

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，在主要包括數據科學解決方案的部署，定制和優化的生產階段，KNIME支持已知工具的協作以提供有用的業務見解。 此外，借助KNIME，利用這些見解變得極為容易，因為它支持即時反饋機制來改善業務見解。

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根據業務需求提供各種功能。 下面列出了其某些功能：

1. Free and open source.
   免費和開源。
2. Continuous integration of services.
   不斷整合服務。
3. Design and development of data workflows.
   數據工作流的設計和開發。
4. Reusable components
   可重復使用的組件
5. Deployment of analytical solutions.
   部署分析解決方案。
6. KNIME server allows the newbies to get access to data science via the KNIME web portal.
   KNIME服務器允許新手通過KNIME Web門戶訪問數據科學。
7. KNIME server allows the use of RESTful APIs.
   KNIME服務器允許使用RESTful API。
8. Supports extensions.
   支持擴展。
9. Supports Integration.
   支持集成。
10. Allows the entire data science cycle right from the ETL phase to the deployment of solutions.
    允許從ETL階段到解決方案部署的整個數據科學周期。

KNIME工具的當前用法和應用 (Current usage and applications of KNIME tool)

The current applications of KNIME tool include:

KNIME工具的當前應用包括：

1. Chemical Informatics.
   化學信息學。
2. Analysis of nanoparticles.
   納米顆粒的分析。
3. Natural Language Processing.
   自然語言處理。
4. Data Analysis and Visualisation.
   數據分析和可視化。
5. Machine learning and any sort of data science tasks.
   機器學習和任何種類的數據科學任務。

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，我要說的是，KNIME在數據科學領域是絕對的幸福。 如果您覺得自己需要一個可以幫助您完成數據科學任務的工具，請繼續并探索KNIME必須提供的功能。 它不僅是一個很好的工具，而且還是一個很好的伴侶，可以幫助新手從一開始就清楚地了解數據科學和分析的功能。

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.

我希望本文能夠幫助您熟悉KNIME的基本功能以及它提供的功能。 甚至我對這個工具都不熟悉，我也在盡力去了解它。 因此，敬請關注，因為我將發布更多有關此出色軟件的文章。

Happy Reading :)

快樂閱讀：)