ToolMeshToolMesh
A

Ask On Data

★3.8
💬109
💲Freemium

Ask On Data is an AI-powered, open-source ETL tool that simplifies data engineering with a chat-based interface. It enables users to create data pipelines without coding, supports various data sources, and offers both self-hosted and managed cloud options.

💻
Platform
web
AIChatbotCloudData AnalysisData CleaningData EngineeringData Integration

What is Ask On Data?

Ask On Data is an AI-powered, open source chat-based ETL tool designed for data engineering. It allows users to perform tasks like data migration, cleaning, and analysis through a simple chat interface, making it accessible for both data scientists and engineers. The tool uses natural language processing (NLP) and generative AI to convert plain English commands into actionable data pipelines, eliminating the need for coding skills.

Core Technologies

  • Artificial Intelligence
  • Natural Language Processing
  • Large Language Models
  • Open Source
  • Data Engineering
  • ETL Tools

Key Capabilities

  • Chat-Based Interface
  • Zero Learning Curve
  • Super Fast Development
  • Data Pipeline Mastery
  • Managed Service on Cloud
  • Action History and Undo Functionality
  • Data Preview
  • Job Scheduling
  • Cost Effective
  • Code Control
  • Data Sources

Use Cases

  • Data integration using union and joins
  • Data cleaning and transformation
  • Custom calculations and data wrangling
  • Creating and scheduling data pipelines
  • Previewing data before execution
  • Managing data operations through chat commands

Core Benefits

  • Intuitive, chat-based interface
  • No coding skills required
  • Fast data pipeline development
  • Cost-effective data pipeline creation
  • Supports various data sources
  • Offers code control with SQL, Python, and YAML options
  • Managed service on the cloud

Key Features

  • Chat-Based Interface
  • Zero Learning Curve
  • Super Fast Development
  • Data Pipeline Mastery
  • Managed Service on Cloud
  • Action History and Undo Functionality
  • Data Preview
  • Job Scheduling
  • Cost Effective
  • Code Control
  • Data Sources

How to Use

  1. 1
    Interact with the platform using plain English commands via the chat interface.
  2. 2
    The AI interprets your commands and converts them into data pipelines.
  3. 3
    Review and adjust the generated pipeline or use code control options.
  4. 4
    Schedule or manually trigger the job for execution.
  5. 5
    Monitor and manage your data operations through the interface.

Pricing Plans

Open Source

Free
Self hosted. All databases support as source and destination. Scheduling feature available. Community support. Patches and upgrades to be deployed manually.

FREE

Free
Managed cloud hosting by Ask On Data. Excel & CSV support only (5MB limit). No job scheduling. Community support. Automatic upgrades, patches, backups, and monitoring all done for you.

ENTERPRISE

Reach out on support@askondata.com
Managed cloud hosting by Ask On Data. All databases support as source and destination. Scheduling feature available. Enterprise support. Automatic upgrades, patches, backups, and monitoring all done for you.

Frequently Asked Questions

Q.What is Ask On Data?

A.Ask On Data is an open-source, AI-powered, chat-based ETL tool for data engineering. It allows users to create data pipelines using plain English commands, eliminating the need for coding.

Q.Who can benefit from Ask On Data?

A.It benefits data scientists, ML engineers, BI users, data analysts, and individuals with limited technical expertise who want to simplify data engineering tasks.

Q.How does the chat-based interface work?

A.The chat-based interface is powered by fine-tuned LLM models, allowing users to interact with the platform using plain English commands.

Q.What kind of operations can I do?

A.You can perform data integration, data cleaning, data wrangling, custom calculations, and data transformation operations.

Q.Will this work happen on actual data in real time?

A.Yes, once you connect to the database, the platform provides a data preview to help you understand how your instructions affect the data before executing the job.

Pros & Cons (Reserved)

✓ Pros

  • Intuitive, chat-based interface
  • No coding skills required
  • Fast data pipeline development
  • Cost-effective data pipeline creation
  • Supports various data sources
  • Offers code control with SQL, Python, and YAML options
  • Managed service on the cloud

✗ Cons

  • Limited Excel & CSV support in the free managed cloud hosting plan
  • Manual deployment of patches and upgrades in the open-source self-hosted plan
  • Reliance on AI for correct operations requires validation

Alternatives

No alternatives found.