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Conversational AI is Changing the Way We Interact With Databy@Eye on AI

Conversational AI is Changing the Way We Interact With Data

by [email protected]January 18th, 2023
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Chat Data Prep is a machine learning platform that allows users to transform data using ordinary conversational language. Users can reformat dates, perform time-based math operations, and even fix messy data fields with a simple conversational command. This new method of interacting with data results in a 10-fold reduction in the time it takes to prepare data.
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In the world of spreadsheets and data analysis, a new player has emerged to shake up the game. Akkio, the easy-to-use AI company, has launched Chat Data Prep, a revolutionary machine learning platform that allows users to transform data using ordinary conversational language.


Gone are the days of struggling with complicated formulas and formatting commands in Excel. With Akkio's Chat Data Prep, users can simply type in conversational language to make changes to their spreadsheet data. Leveraging AI and large language models, the platform interprets the user's requests and makes the necessary changes to the data.


According to Jonathon Reilly, co-founder of Akkio, this new method of interacting with data results in a 10-fold reduction in the time it takes to prepare data for analysis. With Chat Data Prep, users can reformat dates, perform time-based math operations, and even fix messy data fields with a simple conversational command.


Large language models like ChatGPT have paved the way for this breakthrough, allowing for natural language processing capabilities that generate human-like text and images.


These models will revolutionize how we interact with and analyze data, making it easier and more efficient than ever before. One example of this is Chat Data Prep’s ability to quickly and easily manipulate large data sets with simple commands, instead of struggling to learn complex formulas or macros. This can be especially beneficial for those who are not experienced with data analysis, but still need to work with large amounts of information.


Since its public release in November, ChatGPT has led to a rush of business applications. Google has come out with a Chrome extension called GPT for Sheets, which allows users to manipulate data with conversational language, and Microsoft says it will integrate ChatGPT into all of its products.


But Akkio's Chat Data Prep is the first solution to utilize this technology for the preparation and transformation of large volumes of data from any database product. People who make their living as Excel jockeys are impressed.


“If AI can comprehend and set it up, that’s fantastic,” said Edward Godesky, a freelance Excel expert with more than a decade of financial and business analytics experience. “It’s another tool you can use for doing Excel work.”


Data scientists and analysts spend a significant amount of their time on data preparation, with some estimates putting it as high as 80%. Chat Data Prep aims to alleviate this issue by allowing users to clean and transform datasets in minutes, allowing for more time to be spent on insight and modeling.


By using natural language prompts, Chat Data Prep can help to make data analysis more intuitive and user-friendly, allowing anyone to gain insights from their data.


Additionally, Akkio’s product can improve the accuracy and efficiency of data analysis by quickly and easily identifying patterns and trends in large data sets. This can be particularly useful for industries such as finance and healthcare, where large amounts of data need to be analyzed.

By making data analysis more accessible, efficient and accurate, Chat Data Prep has the potential to change almost everything, from how we work with data to how we make important decisions.


Akkio's platform is already being used for a wide range of applications, from lead scoring and revenue forecasting to ad spend optimization and custom-built products. With the addition of Chat Data Prep, the platform now offers machine learning for data preparation as well.


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