What Tools Do Employers Expect Their Data Scientists To Know?

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Every move that we make online, actively creates data somewhere for something. It’s the job of the Data Scientist to make sense of this data and retrieve actionable insights. In order to do this, Data Scientists employ several tools – from MATLAB to SQL to SPSS.

With so many tools out there, if you were to pick the 5 top ones, which ones would they be? Here are the five tools that employers expect their Data Scientists to know:

Python & R – Python and R are both open-source programming languages used by Data Scientists. Together, they allow data scientists to build and automate a large portion of their analysis, and are used to run, share, and distribute work among colleagues and companies. R is mainly used for statistical analysis. Built by statisticians, R uses their specific language while Python utilizes a general-purpose language with readable syntax.

What makes them popular?

The cutting-edge difference between R and the other statistical products is the output, as R has great tools to communicate results.  According to a recent poll conducted by KDNuggets, more than 40% of Data Scientists use R to solve statistical problems.

Python, on the other hand allows a more general approach to Data Science, and makes replicability and accessibility easier than R.

SQL – SQL or “Structured Query Language” is used by Data Scientists to organize databases and pull specific subsets of data for analysis and modeling. It gives Data Scientists the ability to acquire, sort, and mine data in order to build powerful predictive models.

What makes it popular?

Though it’s a 44-year old language, SQL is still among the most commonly used programming language by developers for its simplicity, error-free operation and familiarity. According to the KDNuggets survey, SQL has had a steady share value of 40% over the last 3 years making it a good tool to learn for the long run!

Hadoop – Hadoop is an open source distributed processing framework that was designed to store and retrieve big chunks of data. The best way to use Hadoop for analysis is to use it to store information in a structured format.

What makes it popular?

Hadoop is a preferred tool by Data Scientists as it gives them the advantage of essentially unlimited storage, high performance, and the ease of using familiar and fast tools like SQL and R without having to take additional, complex steps to impose structure on data.

Tableau- Tableau is the most powerful, secure, and flexible end-to-end analytics platform for data. With Tableau, you can prepare your data for analysis, build data sources and dashboards, publish and share content, and collaborate – all with the security and control you require.

What makes it popular?

Easy to use, flexible to suit the requirements of enterprises as well as individuals, and easy to integrate and upgrade, Tableau is one of the most popular data visualization tools worldwide.

IBM Watson- IBM Watson is a question-answering computer system that helps organizations integrate AI into their most important business processes. A supercomputer that combines sophisticated analytical software with Artificial Intelligence, Watson can learn from small data sets of quality, while allowing you to maintain ownership of your data and protect your insights.

What makes it popular?

The unique combination of natural language processing, hypothesis generation and evaluation, and evidence-based learning is what makes Watson so noteworthy.

Want a comprehensive course that can teach you 12+ Analytics tools in 6 months? Check out SSN SACE’s PG Program in Business Analytics & Data Science – http://bit.ly/2pSJ9mf

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