Ask On Data: An Open Source Chat based Data Engineering tool, Powered by GenAI

Ask On Data is pioneering Next gen data stack. It is an Open Source chat based GenAI powered data engineering tool. With simple chat interface, it allows anyone to create data pipelines by using plain English language.

This innovative platform eliminates the need for intricate coding, offering an intuitive and efficient solution to transform data engineering tasks. Whether you’re a seasoned data professional or a newcomer, Ask On Data opens the door to streamlined and accessible data pipeline creation, empowering users to harness the power of their data with unparalleled ease.

Ask On Data is designed to benefit a broad spectrum of users, ranging from Data Scientists & ML AI Enggs, BI users and data analyst, data professionals to individuals with limited technical expertise. Data engineers and analysts can streamline their workflow by simplifying the creation of complex data pipelines using natural language commands. Business analysts and decision-makers gain a user-friendly interface to interact with data without delving into coding intricacies. Data scientists can get the required preprocesssed data by themselves to further run the ML AI algorthims. Even those new to data engineering can benefit, as Ask On Data’s intuitive design allows them to create end-to-end data pipelines effortlessly. In essence, Ask On Data is tailored to empower both technical and non-technical users, democratizing the data engineering process for greater accessibility and efficiency.

The chat-based interface of Ask On Data is powered by fine tuned LLM models. It allows users to interact with the platform using plain English commands. Users can communicate their data engineering requirements in a conversational manner. Ask On Data’s sophisticated algorithms understand and interpret these commands, converts them into actionable data pipelines and then these jobs can be orchestrated and scheduled.

You can do all kind of operations which includes data integration (like union, joins etc), data cleaning, data wrangling, custom calculations, data transformations operations etc.

As soon as you connect to the database to create certain jobs, we load a preview of the data. This preview is helpful because it allows you to understand how your instructions are affecting the data as such. So you can type and create your entire pipeline. When done, then you can orchestrate/schedule it.
When this job gets actually triggered, then it will work on the actual data. You even have options of triggering the job also manually as well.

As you keep on instructing the platform with your commands, it also keeps on creating end to end data pipeline. You also have an option of seeing the YAML file, that YAML file you can view, validate and even edit before orchestrating and running those jobs.

Further, by going to settings, you can enable certain kind of plugins. One of the plugin is SQL plugin. When enabled, it can allow you to even write full SQL code also.

Aside, while scheduling we also give you an option to write full fledged Apache Spark code also.

If you are self hosting, then it is fully free. However if you would like to use our enterprise version, then our costing is based on the amount of data. You can reach out to us on support@askondata.com for more questions.

Ask On Data is built on top of Python and frontend is React. When you type and create data pipelines, we are creating Apache Spark jobs which then gets orchestrated. Other technologies used are Langchain, Olama, Airbyte

Ask On Data stands out from other data engineering tools through its pioneering chat-based interface and robust natural language processing (NLP) capabilities. By allowing users to communicate their data engineering needs in plain English, the platform eliminates the complexities of coding, making it exceptionally user-friendly and accessible. What sets Ask On Data apart is not just its innovative interface but also the unparalleled speed it brings to pipeline development. With a simple chat-based interaction, users can create end-to-end data pipelines swiftly, reducing the time and effort traditionally associated with data engineering tasks. Aside, the chat interface ensures that there is zero learning curve, simply type and start using. This emphasis on efficiency, coupled with its intuitive design, positions Ask On Data as a frontrunner in transforming how data pipelines are conceived and developed 

Absolutely, Ask On Data is tailored to cater to businesses of all sizes. Whether you’re a small startup, a mid-sized enterprise, or a large corporation, Ask On Data’s intuitive and user-friendly interface empowers users across various business scales. Small businesses with limited technical resources can benefit from the platform’s accessibility, enabling them to harness the power of data without the need for extensive coding knowledge.
Mid-sized enterprises seeking streamlined data engineering processes will find Ask On Data to be a valuable asset in enhancing efficiency and productivity. Larger corporations, dealing with complex data scenarios, can leverage Ask On Data’s capabilities to simplify and accelerate their data pipeline development.
In essence, Ask On Data’s versatility and scalability make it a suitable solution for businesses of all sizes, democratizing data engineering and ensuring that organizations, regardless of their scale, can unlock the full potential of their data with ease.

Yes, there is undo functionality. Once you login, at the top right you can see that option.

If you have any other questions regarding the demo or features or pricing or custom implementation or partnership or anything else, you can reach out on Support@AskOnData.com