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Data preparation simplified with AI

Derive data wrangling formulas in seconds, bring in third party data for enrichment, and more. With Zia, and powered by ChatGPT API, Data Preparation gets even more easier - use natural language prompts to get your data management on auto drive.

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Transform by example

Transform by example easily helps you transform the data in any column to your needs just by providing examples of the output. This can transform text, date or numerical data by performing complex text extractions, date formatting and arithmetic operations behind the scenes.

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Chat formula builder

Simplify formula creation by narrating the logic in natural language. Derive formula columns quickly without the hassles of learning all of the available functions or their syntax. Cut down the time to prepare data and use that time effectively for analysis and other downstream processes.

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Dataset Finder

Discover relevant public datasets and generate sample data by simply asking for it. Dataset finder enables you to generate datasets based on your data needs. Blend created datasets with first party data during data preparation process. Use synthetic data for data analysis or for experimentation.

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Why use Zia background

Powered by generative AI for Zoho DataPrep, you can

  •  Derive complex string manipulation formulas in a matter of seconds
  •  Arrive at data transformation recipes using natural language queries
  •  Remove complexities surrounding data preparation processes
  •  Improve accuracy of overall data preparation process

Benefits

Data engineering for everyone

Data Preparation using natural language prompts makes it accessible to everyone, from managers to business owners. No code required.

Saves time

AI-based data transformation comes up with intelligent suggestions that can save up time for analysts for downstream processes like analytics.

Run experiments

Augment first party data with external data to enrich the data and draw key insights. Use synthetic data built with by Open AI to run experiments and build models.

Refine and reuse rules

Use transformation suggestions and formulas to improve data quality consistently. Reuse the rule sets and set your business on a data-forward trajectory.

Save time, remove complexities, and improve overall accuracy of data preparation

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