As businesses and industries rely more on data analysis to make sense of the enormous amount of information, running analytical queries and creating visualizations can be intimidating and time-consuming for those who need more data skills. To simplify this process, an open-source project called Auto-Analyst has been created, which allows users to perform complex data analysis using natural language.
According to Aaditya Bhat, “Auto-Analyst provides an intuitive interface that enables users to upload a CSV file and start asking analytical questions about their data. The tool processes these questions, performs the required data analysis, and returns the results in an easy-to-understand format. Auto-Analyst is written in Python, users can easily run the tool on their local machines by cloning the code repository and following the ‘Run Locally’ instructions from the repository.”
Aaditya is an engineer passionate about exploring the latest developments in ML and AI. With over a decade of experience working with some of the biggest names in the industry, Aaditya has developed a deep understanding of the industry and its workings. Aaditya has extensive experience in Data Science and Engineering; he has built systems and tools to help organizations make data informed decisions in timely manner.
On the need for a new tool in the data analysis sector, Aaditya explains that the rise of “LLMs such as OpenAI’s ChatGPT, Facebook’s Llama, and Stanford’s Alpaca have demonstrated remarkable success in tasks like code generation, reasoning, and language understanding. Their capabilities open up new opportunities to make data analysis more accessible and user-friendly for non-technical users.”
He goes further to make a case for Auto-Analyst, claiming that the program “was born out of the need to harness the power of these LLMs to make data analysis more approachable. With the increasing importance of data in decision-making, it’s essential to empower people to analyze and visualize data without relying on programming skills or deep technical expertise.”
As he points out, “Auto-Analyst provides a user-friendly interface that allows you to ask questions about your data using natural language, simplifying the data analysis process and saving time. By leveraging the potential of LLMs, Auto-Analyst aims to become a powerful tool in the data analysis ecosystem, bridging the gap between complex data and its interpretation.”
In essence, Aaditya believes that there is a growing demand for user-friendly data analysis tools that cater to both technical and non-technical users. It is this need he is looking to fill in the industry.