Zoho DataPrep is a cloud-based, no-code platform for preparing, moving, and monitoring data pipelines. It helps data analysts, business users, data engineers, and data scientists clean datasets, automate recurring flows, and deliver data to downstream systems.
Zoho DataPrep is a cloud-based data preparation and pipeline platform that combines ETL, data cleaning, enrichment, movement, and monitoring in one workspace. It is designed to help teams take raw data from business applications, APIs, files, databases, cloud storage, and warehouses; prepare it for analysis or operations; and deliver it to downstream destinations.
The platform uses a visual, no-code pipeline builder and includes more than 250 built-in transforms. Users can also ask Zia to perform preparation tasks through natural-language prompts. Scheduled workflows, sandbox testing, monitoring dashboards, failure alerts, and automated retries support recurring data operations. A separate browser-based Data Quality Analyser checks CSV files locally and produces quality reports before data is used downstream.
Build source-to-destination data flows with a no-code visual pipeline builder. DataPrep can import from business applications, REST APIs, cloud storage, databases, and data warehouses, then export prepared data to warehouses, storage, and business applications.
Use a spreadsheet-like preparation workspace with more than 250 built-in transforms to clean, standardize, reshape, blend, and enrich datasets without writing scripts.
Ask Zia, Zoho's in-house AI engine, can help clean and transform data from prompts in natural language. OpenAI integration can provide additional datasets and assist with complex formulas.
Combine datasets and apply enrichment operations, including machine-learning-powered sentiment analysis and keyword extraction for user-generated content.
Schedule recurring data movement and preparation workflows. A sandbox environment lets teams test a pipeline before publishing it to production.
Track pipeline status from a dashboard, receive email alerts for failed jobs, and use automated retries to improve run resilience. Workspaces and pipelines can be shared with team members.
Data analysts can combine datasets, correct invalid values, standardize fields, and reshape messy source data into datasets that are ready for reporting or analytics.
Business teams can move data between applications, storage, databases, and warehouses on a schedule instead of repeating manual exports, imports, and cleanup.
Teams working with feedback or other user-generated content can apply sentiment analysis and keyword extraction, then combine the results with other datasets.
Data engineers can test flows in a sandbox, schedule recurring jobs, monitor run status, receive failure alerts, and use retries or backfilling processes when jobs do not complete.
Data scientists can prepare larger datasets with no-code AI capabilities or use the Python code studio for analytics and model-related work.
The product describes use cases for data analysts, business users, data engineers, and data scientists. Analysts and business users can work through the no-code interface, while engineers and data scientists can manage pipelines and use the Python code studio.
Yes. Users can schedule data movement and preparation workflows, monitor pipeline status, receive email alerts for failed jobs, and use automated retries to improve run reliability.
Many preparation and pipeline tasks can be completed through the no-code visual interface and Ask Zia's natural-language prompts. The site also describes a Python code studio for users who need code-based data-science workflows.
The analyzer currently accepts CSV files with headers in the first row. It recommends files around 20 MB, automatically detects column types such as text, number, date, email, and boolean, and lets users adjust those types before analysis.
Yes. The Data Quality Analyser can export a printable PDF report or a structured JSON file containing issues and per-column statistics. Its analysis runs locally in the browser, so the uploaded file is not sent to a server.
gptforwork.com
GPT for Work adds an AI agent and bulk-processing tools to Excel and Google Sheets. It helps spreadsheet users clean, analyze, translate, enrich, and reorganize data, as well as create and check formulas.
datafold.com
用于 AI 迁移、数据质量测试和智能体上下文的数据工程自动化平台
www.alteryx.com
Alteryx One is a unified data analytics and automation platform for analysts and business teams. It prepares data, builds governed no-code workflows, automates repeatable processes, and delivers insights to reports, dashboards, applications, and AI systems.
versium.com
面向B2B2C身份解析、数据 enriquecimiento 和受众创建的云端数据平台
ceritmustafa.github.io
ScreenMark is a macOS menu bar app for live screen annotation, zoom, whiteboard overlays, freeze frames, and recording. It is designed for presenters, teachers, workshop facilitators, and anyone who needs to explain on-screen content without leaving their workflow.
apra-labs.github.io
apra-fleet runs a fleet of AI agents across multiple machines and provider CLIs. It provides a common execution model for combining Claude, Codex, Copilot, Antigravity, and local models.
