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Key tools for data scientists in 2019

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A data scientist is required to perform complicated tasks like acquiring and storing large sets of unstructured data, analysing such data sets, extracting usable information out of those and then utilizing that for specific purposes.

For such tasks, data scientists are required to use advanced tools designed for data science. While there are many data science tools available in the market, one might wonder which tools are vital in achieving success in the field of data science.


Designed specifically for data science operations, SAS is one of the most reliable commercial software available today. Developed by the SAS Institute, it has been a leader in the world of data science and analytics since long.

SAS utilizes its own programming language and is fairly simple to use. It offers a range of statistical libraries, data scientists can easily use it for tasks like data modelling, data organizing and analysis. It also has capability to handle big data and can be used efficiently for big data analytics.

SAS institute also features as a key player in markets like Global data mining tools market, Business Analytics Software market and Life Science Analytics market.


Python is one of the most popular high-level, object-oriented Programming languages and has emerged as a top data science platform in the recent times. Dedicated data science libraries and simple syntax makes this open-source tool essential for data scientists today. Be it data wrangling or data munging, Python library Pandas is used by many and Python is also a top tool in the fields of Machine Learning and Deep Learning.

One amazing advantage of Python is its great support community. Being open source and highly popular, there is a huge community of developers, data scientists, software engineers who are constantly sharing ideas and helping each other out.


When it comes to self service BI tools or software for data visualization, only a few can rival Tableau. A leader in the Gartner magic quadrant for six consecutive years, tableau is favoured over other tools because of its highly interactive dash board, quick analysis capabilities and powerful data visualization.

Data visualization is one of the key tasks in any data related activity and Tableau offers a range of charts, graphs and histograms to efficiently and quickly visualize data. Thus, Tableau skills are extremely important for data professionals who has to deal with data visualization a lot.

To conclude:

Gaining proficiency in such data science tools is instrumental in achieving success in the field of data science. And in Malaysia there are many reputed institutes offering quality training in Data science and by opting for such a training in Malaysia you can greatly increase your employability!