In recent years, generative AI has been a great asset to the world at large. The impact of generative AI is apparent in many industries and functions, where there is substantial evidence of how it has buttressed daily operations. Generative AI is fuelled by the availability of large language models (LLMs) powered by 3rd party data. LLMs are machine learning models trained on significantly large amounts of data. 

The prowess of generative AI is yet to be fully realized, especially within the landscape of data science. With generative AI's fundamental roots in machine learning, there is a myriad of opportunities that it can help in data interpretation, processing, and utilization. 

Before delving into how generative AI is a transformative force within the data science industry, what is data science? Data science is the science that primarily involves the combination of mathematics and statistics to uncover actionable insights hidden in data. 

With the advent of online education, enrolling in data science courses online is paramount to staying up-to-date in this ever-growing branch of science.

This article will highlight the various avenues in how generative AI is transforming data science tools. 

Generative AI on Data Science 

Existing data science tools such as VS Code, Jupyter Notebook, and Google Collaboratory Notebook are of great capabilities. However, their power can be greatly enhanced by generative AI. 

Generative AI is capable of accelerating the intricate process of getting business insights from organizational data. This provides a pedestal to boost the productivity and efficiency of businesses thereby arriving at a consensus fairly earlier than usual. 

Einblick and Alteryx are sample generative AI tools that have been developed to help complement the existing data science tools. 

How Einblick is Shaping Data Science?

Einblick introduces an AI agent called "Prompt". Prompt works based on natural language processing (NLP), which allows users to create entire data workflows. It plays a pivotal role in data preprocessing, exploratory data analysis, and model building. Einblick combines the power of existing data science notebooks such as Jupyter with ChatGPT. 

Einblick is a great tool for data science as it reduces the need for verbose input to the Prompt in generating a well-structured code. 

Tedious tasks such as data cleaning, handling missing values, and splitting data into training, validation, and testing sets are among the operations that Einblick can process with high efficiency. 

The Director & Head of Digital Analytics and Insights (Marketing Science) at Virtual Gaming World, Fawad Memon, asserted the statement "One compelling illustration is the introduction of Einblick's Prompt - a tool that, at the click of a button, streamlines data formatting, checks for missing values, generates editable code, and even aids in debugging. As a former data analyst, the seamless transformation of findings into visualizations using natural language commands particularly caught my interest. These streamlined processes markedly accelerate the time it takes for impactful outputs to be delivered." 

A data scientist from Google said "I found a data scientist's gold mine! Einblick turns your Jupyter notebook into a visual & interactive canvas, where you can build and test machine learning models in seconds."

Role of Alteryx in Data Science 

Atleryx similar to Einblick is a leading AI platform for enterprise analytics that delivers actionable insights by automating analytics. However, Alteryx combines the power of AI, machine learning, and generative AI with the Alteryx analytics cloud platform to accelerate analytics efficiency and productivity. 

Corporations such as Siemens, Unilever, Visa, Abbott, Dell, and General Electric are great users of Alteryx in their daily operations. 

According to Meghan Gohil, the Automation and Data Visual Manager at Fender, "We can get really deep in the weeds because we're not dealing with lines and lines of code, which means we can focus on truly understanding our players and their needs. Before Alteryx, decisions had been made based on gut feeling. This way, we are able to get closer to a more scientific way to do it."

Conclusion 

Undoubtedly, generative AI is creating an absolute shift within the data science scene. 

Complex and tedious such as dataset exploration, handling of missing values, and splitting of a dataset into training, validation, and testing data can now be handled with ease and just by clicking of buttons. 

Generative AI tools such as Einblick and Alteryx, are great tools in addition to the existing powerful tools such as VS Code, Jupyter Notebook, and Google Collaboratory Notebook.

It will be of great benefit for all businesses, either big or small to leverage the prowess of generative AI in data science to boost their productivity and efficiency.