I spent a good amount of time interviewing SMEs, data scientists, business analysts, leads & their customers, programmers, data enthusiasts and experts from various domains across the globe to identify & put together a list that will remain in its area for a longer time.

我花了大量時間采訪來自全球各個領域的SME，數據科學家，業務分析師，潛在客戶及其客戶，程序員，數據愛好者和專家，以找出并整理一份清單，該清單將在其領域中保留更長時間。

Lets get started {in no specific order}

讓我們開始{無特定順序}

R編程 (R Programming)

There is more than one reason why some data scientists 💜R. It is simple in its syntax yet so powerful in processing a variety of complex data-driven tasks, statisticians tool of choice, an ocean of libraries and ease of installing them. It is so joyful to work with ggplot2 (built on grammar of graphics) to build some eye-candy dashboards. Shiny makes building interactive dashboards, a breeze.Have a look at a curated list of awesome R packages and tools here.

有些數據科學家提出R的原因不只一個。 它的語法很簡單，但是在處理各種復雜的數據驅動任務，統計學家選擇的工具，大量的數據庫以及易于安裝的過程中功能強大。 與ggplot2 (基于圖形語法構建)一起構建一些令人眼花dy亂的儀表板非常高興 。 閃亮的品牌構建交互式儀表盤，一breeze.Have一看真棒R程序包和工具的組織列表在這里 。

Python (Python)

Fully-fledged and object oriented programming language, Python is exclusively built and used for deep learning, web development and software development, apart from regular day-to-day data science. Frameworks like Django and Flask make it easier to build better web apps more quickly and with less code.

完全成熟且面向對象的編程語言，除常規的日常數據科學外， Python專門用于深度學習，Web開發和軟件開發。 諸如Django和Flask之類的框架使您更容易以更少的代碼更快地構建更好的Web應用程序。

I probed Python & R users further on their choice and tested their willingness towards shifting to other programming language; here are their views and summary response;

我進一步研究了Python＆R用戶的選擇，并測試了他們轉向其他編程語言的意愿。 這是他們的觀點和簡要答復；

R community data scientists expect additional support on the area of deep learning and computer vision. With the people I brainstormed with, R users are very comfortable performing top-notch data manipulation using tidyverse, dplyr, data.table. Again, majority of their users are from statistical background, ETL, IDE & data handling capability, performing complex data-manipulation faster. RMarkdown is a noteworthy mention.

R社區數據科學家希望在深度學習和計算機視覺領域提供更多支持。 與我一起集思廣益的人們一起使用，R用戶非常樂于使用tidyverse ， dplyr和data.table進行一流的數據操作。 同樣，他們的大多數用戶都來自統計背景，ETL，IDE和數據處理功能，從而可以更快地執行復雜的數據處理。 RMarkdown值得一提。

To some of the Python users I spoke, they have heard and impressed about ggplot2, and looking forward to seeing matplotlib & seaborn to shiny the same way. They agree that the complexity and speed of the data operations can be improved. Python users have a great advantage over utilizing theano, TensorFlow, Keras; some of the industries’ best API written in python.

對于我所說的一些Python用戶，他們已經聽說過ggplot2并留下了深刻的印象，并期待看到matplotlib和seaborn一樣閃閃發光。 他們同意可以提高數據操作的復雜性和速度。 Python用戶有很大的優勢利用theano ， TensorFlow ， Keras ; 一些業界最好的用python編寫的API。

SQL (SQL)

Data is all around us. The percentage of data digitization has been rapidly increased, multiple-fold. Stored.How do we easily pull the data we want and/or interact with the data; SQL, a language that communicates with the databases.

數據無處不在。 數據數字化的百分比已Swift增長，并且是原來的幾倍。 已存儲。如何輕松提取所需的數據和/或與數據進行交互； SQL ，一種與數據庫通信的語言。

An ample amount of my respondents believe SQL is a must-known data-manipulation and retrieval programming language utilized to interface with various databases.

我的大量受訪者認為，SQL是一種必須使用的數據處理和檢索編程語言，可用于與各種數據庫進行接口。

Yes, talking about databases; a majority of DBAs have started shifting their focus towards PostgreSQL.

是的，談論數據庫； 大多數DBA已經開始將重點轉向PostgreSQL 。

BIG DATA is an interesting topic too. You may also would like to refer to sparklyr and pyspark.

大數據也是一個有趣的話題。 您可能還想參考sparklyr和pyspark 。

Python & R users can connect to various databases and start communicating with the data tables right from their IDEs.

Python ＆ R用戶可以連接到各種數據庫并直接從其IDE開始與數據表進行通信。

Special Mention

特別提及

Java (Java)

Java programming has a huge fan base. In the field of software development, this rising steam programming language still go hot. The modern day JavaScript frameworks like react.js and Vue.js are gaining more popularity in the field of progressive web development.

Java編程擁有巨大的支持者。 在軟件開發領域，這種新興的蒸汽編程語言仍然很熱門。 諸如React.js和Vue.js之類的現代JavaScript框架在漸進式Web開發領域中越來越受歡迎。

I’m sure you wouldn’t have guessed the next one.

我相信您不會猜到下一個。

Adobe After Effects (Adobe After Effects)

Lets get into building some cool infographics, rejuvenating data-driven animations; explained a senior director — data science while discussing about the activities that revolve around data2insights.There is a remarkable interest of insights that go unnoticed during the process of data getting translated into insights, he added.

讓我們開始構建一些很酷的信息圖表，使數據驅動的動畫煥發青春； 他補充說，在討論圍繞data2insights開展的活動時，數據科學高級總監解釋說。人們非常關注洞察力，而在將數據轉換為洞察力的過程中，洞察力卻未被注意到。

The leadership team will always have dependency on those data dashboards you create. Build them with some super-creative concrete embedded. Those bricks are pieces of valuables information.

領導團隊將始終依賴于您創建的那些數據儀表板。 用嵌入的超創意混凝土建造它們。 這些磚頭是貴重物品信息。

特別提及 (Special Mentions)

Data science using Tableau is now trending among visualisation experts. The ability it has in the field of business intelligence is promising.

現在，在可視化專家中，使用Tableau進行數據科學發展的趨勢。 它在商業智能領域的能力很有前途。

Power BI integrates seamlessly with the existing application ecosystem of MS.Both Tableau and Power BI have innovation in constant.

Power BI與MS的現有應用程序生態系統無縫集成.Tableau和Power BI都不斷創新。

Open forum. Feel free to share and mention your views too. Thank you folks.

打開論壇。 隨時分享和提及您的觀點。 謝謝大家。

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