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.

我花了大量时间采访来自全球各个领域的SME，数据科学家，业务分析师，潜在客户及其客户，程序员，数据爱好者和专家，以找出并整理一份清单，该清单将在其领域中保留更长时间。

Lets get started {in no specific order}

让我们开始{无特定顺序}

R编程 (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.

有些数据科学家提出R的原因不只一个。 它的语法很简单，但是在处理各种复杂的数据驱动任务，统计学家选择的工具，大量的数据库以及易于安装的过程中功能强大。 与ggplot2 (基于图形语法构建)一起构建一些令人眼花dy乱的仪表板非常高兴 。 闪亮的品牌构建交互式仪表盘，一breeze.Have一看真棒R程序包和工具的组织列表在这里 。

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.

完全成熟且面向对象的编程语言，除常规的日常数据科学外， Python专门用于深度学习，Web开发和软件开发。 诸如Django和Flask之类的框架使您更容易以更少的代码更快地构建更好的Web应用程序。

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;

我进一步研究了Python＆R用户的选择，并测试了他们转向其他编程语言的意愿。 这是他们的观点和简要答复；

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社区数据科学家希望在深度学习和计算机视觉领域提供更多支持。 与我一起集思广益的人们一起使用，R用户非常乐于使用tidyverse ， dplyr和data.table进行一流的数据操作。 同样，他们的大多数用户都来自统计背景，ETL，IDE和数据处理功能，从而可以更快地执行复杂的数据处理。 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.

对于我所说的一些Python用户，他们已经听说过ggplot2并留下了深刻的印象，并期待看到matplotlib和seaborn一样闪闪发光。 他们同意可以提高数据操作的复杂性和速度。 Python用户有很大的优势利用theano ， TensorFlow ， Keras ; 一些业界最好的用python编写的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.

数据无处不在。 数据数字化的百分比已Swift增长，并且是原来的几倍。 已存储。如何轻松提取所需的数据和/或与数据进行交互； SQL ，一种与数据库通信的语言。

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

我的大量受访者认为，SQL是一种必须使用的数据处理和检索编程语言，可用于与各种数据库进行接口。

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

是的，谈论数据库； 大多数DBA已经开始将重点转向PostgreSQL 。

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

大数据也是一个有趣的话题。 您可能还想参考sparklyr和pyspark 。

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

Python ＆ R用户可以连接到各种数据库并直接从其IDE开始与数据表进行通信。

Special Mention

特别提及

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编程拥有巨大的支持者。 在软件开发领域，这种新兴的蒸汽编程语言仍然很热门。 诸如React.js和Vue.js之类的现代JavaScript框架在渐进式Web开发领域中越来越受欢迎。

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

我相信您不会猜到下一个。

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.

让我们开始构建一些很酷的信息图表，使数据驱动的动画焕发青春； 他补充说，在讨论围绕data2insights开展的活动时，数据科学高级总监解释说。人们非常关注洞察力，而在将数据转换为洞察力的过程中，洞察力却未被注意到。

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.

领导团队将始终依赖于您创建的那些数据仪表板。 用嵌入的超创意混凝土建造它们。 这些砖头是贵重物品信息。

特别提及 (Special Mentions)

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

现在，在可视化专家中，使用Tableau进行数据科学发展的趋势。 它在商业智能领域的能力很有前途。

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

Power BI与MS的现有应用程序生态系统无缝集成.Tableau和Power BI都不断创新。

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

打开论坛。 随时分享和提及您的观点。 谢谢大家。

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