7 Tools used by Data Scientists

By POOJA BISHT |Email | Mar 25, 2019 | 18138 Views

The opportunities in Data Science are growing every day. There are several platforms risen to help aspirants learn and explore in this field. Due to the bulk of information available over the internet, a sort of confusion always pervades related to the tools that are used by the Data Scientists in managing large and big data sets for finding insights.

A Data Scientist is the key person sitting in an organization who plays a critical role in making useful decisions for the Business to enhance its operational efficiency and take the business to a next level by finding key insights from data and presenting those in front of the key decision makers in an organization.

Apart from the Reasoning and the soft skills a Data Scientist possess, he is an expert in using some tools which are very helpful in analyzing big data sets. He must be open to the new technology and methods while having an excellent command over the existing.

Although it depends on the company of which of the tools are preferred by it for working with its data, here are the 6 tools that are mostly used by the Data Scientists today and the one that you should actually put your eyes on while exploring into the field of Data Science. 
Let's have a quick look

  • Apache Spark
Whether its Netflix, Amazon, Microsoft or Oracle, Apache Spark has been adopted by the top companies and businesses today to process their big data fastly. Apache Spark is excellent in processing a large amount of big data sets fastly which is the utmost need of the businesses today. What do the businesses working with data need more other than to process their big data faster?

  • Python
Python is the most sought after Programming Language in Data Science today that is looked by the majority of the companies.

  • R
R is the programming Language which is used by the Data Scientists for Statistical computing. R makes it easier to visualize big data sets and finding insights out of them, in the absence of which is a tiresome and difficult task for handling large datasets and finding relevant information.

  • A/B Testing
A/B Testing is used by many of the Businesses today to find out the more effective version between their created versions, suppose A & B. It is needed by the businesses to provide the best of the version of their products to enhance the user experience. The better the version will be, the more profit the business will gain. A/B Testing finds its popularity in businesses due to this exceptional feature.

MYSQL, which is an open source Relational Database Management System is used by Data Scientists in the process of collecting data, processing those large datasets and finally analyzing it.

  • SAS
Statistical Analysis System or SAS is used for analysis of data, in business Intelligence by many of the companies with mostly in the Financial sector. It has its feature of visualizing data in the statistical form which is obviously easier to analyze. Most of the companies prefer R while many still use SAS.

Source: HOB