ask-on-data
Ask On Data is an open source, GenAI-powered chat-based data engineering tool that enables users to create and manage data pipelines using natural language commands, eliminating the need for coding skills. It is designed for both technical and non-technical users to simplify and accelerate data engineering tasks.
ask-on-data is business intelligence software teams evaluate for business intelligence. Use this page to review pricing, integration signals, and the best alternatives before you commit.
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Quick Overview
Best for: Business Intelligence
What it does
Business Intelligence software for decision-makers comparing workflow fit and alternatives.
Best fit
Business Intelligence
Pricing snapshot
Freemium from Free
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ask-on-data
Ask On Data is a pioneering next-generation data stack tool that leverages natural language processing (NLP) and GenAI to provide a chat-based interface for data engineering. It allows users to create, manage, and optimize data pipelines simply by conversing in plain English, removing the traditional complexities of coding. The platform supports users ranging from data scientists, engineers, analysts, to non-technical business users, democratizing access to data engineering capabilities. It also offers options for advanced users to write SQL, YAML, and Python for greater control. The tool supports various data sources including flat files, APIs, databases, data lakes, and warehouses, and provides managed cloud hosting as well as self-hosted open source options.
AI-powered, open source chat-based ETL tool for data engineering.
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Claim this listingKey Features
Data Pipeline Mastery
Create, manage, and optimize data pipelines seamlessly using an AI-powered chat interface without coding.
Chat Interface
A simple, intuitive chat-based interface that allows users to build data pipelines with no technical knowledge or learning curve.
Managed Service on Cloud
Available as a managed cloud service, removing the need for infrastructure management, with options for cloud deployment.
Action History and Undo Functionality
Comprehensive history tracking of all data actions with the ability to undo changes.
Data Preview
Real-time data preview with every transformation instruction to validate changes before committing.
Job Scheduling
Create end-to-end data pipelines and schedule jobs with options for full load, incremental load, truncate and load, etc.
Cost Effective
Offers over 80% cost savings compared to other data engineering tools.
Code Control
Advanced users can write and edit SQL, Python, and YAML files for handling edge cases and custom logic.
Support for Multiple Data Sources
Supports flat files, APIs, databases, data lakes, data warehouses, and log files with custom data source support available.
Pricing
Open source self-hosted version is fully free with community support and scheduling features.
Open Source Self Hosted
Free- Supports all databases as source and destination
- Scheduling feature available
- Community support
- Manual deployment of patches and upgrades
Managed Cloud Hosting (Free Tier)
Free- Excel & CSV support only (5MB limit)
- No job scheduling
- Community support
- Automatic upgrades, patches, backups, and monitoring
Enterprise
Contact [email protected] for pricing- Managed cloud hosting
- Supports all databases as source and destination
- Job scheduling
- Enterprise support
Use Cases
Data Pipeline Creation for Non-Technical Users
Enables business analysts and decision-makers to create and manage data pipelines without coding knowledge.
Streamlining Data Engineering Workflows
Allows data engineers and analysts to accelerate pipeline development using natural language commands.
Data Preparation for Data Scientists
Empowers data scientists to preprocess and transform data independently for machine learning and AI tasks.
Cost-Effective Data Integration
Helps organizations reduce data engineering costs by over 80% compared to traditional tools.
Managed Cloud Data Engineering
Provides managed cloud hosting for organizations that prefer not to handle infrastructure.
Integrations
Apache Spark
Data pipelines are created as Apache Spark jobs for scalable data processing.
Langchain
Used for natural language processing and AI capabilities.
Olama
Part of the AI technology stack supporting the platform.
Airbyte
Supports data integration and connectors.
SQL Plugin
Enables writing full SQL code within the platform for advanced data operations.
Benefits
Limitations
Frequently Asked Questions
What is Ask On Data?
Who can benefit from Ask On Data?
How does the chat-based interface work?
Can I perform complex data operations?
Is the data processing real-time?
How can I trust the AI-generated pipelines?
What is the pricing model?
What technologies is Ask On Data built on?
Getting Started
- 1 Step 1: Register for a free trial or download the open source self-hosted version.
- 2 Step 2: Connect your data sources such as databases, files, or APIs.
- 3 Step 3: Use the chat interface to create and customize data pipelines using plain English commands.
- 4 Step 4: Preview data transformations in real-time and validate changes.
- 5 Step 5: Schedule and orchestrate data pipeline jobs as needed.
- 6 Step 6: Optionally, write or edit SQL, Python, or YAML for advanced control.
Support
Contact support via email at [email protected] for demos, pricing, custom implementations, or partnerships.
docs
Documentation is available on the website under the Docs section.
API
No specific API documentation mentioned.
Not available.
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