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Additionally, tabular data usually comprises both *numeric* and *categorical* features. **Numeric** features are those that encode **quantitative** values, whereas **categorical** represent **qualitative** measurements. Categorical features can further divided in *ordinal*, *binary* or *boolean*, and *nominal* features.
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Learn more about synthesizing tabular data in this [article](https://ydata.ai/resources/gans-for-synthetic-data-generation), or check the [quickstart guide](getting-started/quickstart.md#synthesizing-a-tabular-dataset) to get started with the synthesization of tabular datasets.
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Learn more about synthesizing tabular data in this [article](https://ydata.ai/resources/gans-for-synthetic-data-generation), or check the [quickstart guide](/synthetic_data/single_table/ctgan_example) to get started with the synthesization of tabular datasets.
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=== "Time-Series Data"
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**Time-series data** exhibit a sequencial, **temporal dependency** between records, and may present a wide range of patterns and trends, including **seasonality** (patterns that repeat at calendar periods -- days, weeks, months -- such as holiday sales, for instance) or **periodicity** (patterns that repeat over time).
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Read more about generating [time-series data in this article](https://ydata.ai/resources/synthetic-time-series-data-a-gan-approach) and check this [quickstart guide](getting-started/quickstart.md#synthesizing-a-time-series-dataset) to get started with time-series data synthesization.
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Read more about generating [time-series data in this article](https://ydata.ai/resources/synthetic-time-series-data-a-gan-approach) and check this [quickstart guide](/synthetic_data/time_series/timegan_example) to get started with time-series data synthesization.
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=== "Multi-Table Data"
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**Multi-Table data** or databases exhibit a referential behaviour between and database schema that is expected to be replicated and respected by the synthetic data generated.
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Read more about database [synthetic data generation in this article]() and check this [quickstart guide for Multi-Table synthetic data generation]()
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Read more about database [synthetic data generation in this article](https://ydata.ai/resources/whitepaper-relational-databases-synthetic-data) and check this [video guide for Multi-Table synthetic data generation](https://www.youtube.com/watch?v=40Q56xZbv00&ab_channel=YData)
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**Time-series data** exhibit a sequential, **temporal dependency** between records, and may present a wide range of patterns and trends, including **seasonality** (patterns that repeat at calendar periods -- days, weeks, months -- such as holiday sales, for instance) or **periodicity** (patterns that repeat over time).
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## Validate the quality of your synthetic data generated
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Heading towards the future of synthetic data generation we recommend everyone to transition to [ydata-sdk](https://docs.sdk.ydata.ai/latest/), which provides a superior experience with enhanced performance, precision, and ease of use, making it the preferred tool for synthetic data generation and a perfect introduction to Generative AI.
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### Older version with open-source models
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[Check the deprecated documentation](docs/getting-started/index.md)
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#### Older version with open-source models
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Check the deprecated documentation [here](getting-started/index.md).
Copy file name to clipboardExpand all lines: docs/support/help-troubleshooting.md
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If you are just starting, or you are dealing with something new we are always eager to help!
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Join us in the [Data-Centric AI community Discord](https://discord.com/invite/mw7xjJ7b7s), we have a space reserved for all your questions about Synthetic Data! Don't be shy 😳
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Join us in the [Data-Centric AI community Discord](https://discord.com/invite/mw7xjJ7b7s), we have a space reserved for all your questions about Synthetic Data!
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Users have access to advanced settings, such as [conditional synthetic data generation](https://ydata.ai/resources/conditional-synthetic-data-generation-for-robust-machine-learning-applications) or business rules.
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-**Preserving Data Integrity:** For datasets requiring strict adherence to structural patterns (e.g., time-series data, healthcare records or databases).
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### Getting started with YData Fabric (Community version)
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YData Fabric’s Community Version offers users a free, accessible entry point to explore synthetic data generation.
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To get started, users can [sign up for the Community Version and access the guided UI directly](https://ydata.ai/register).
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Once registered, users are provided with a range of features, including data profiling, synthetic data generation, pipelines and access to YData’s proprietary models for data quality!
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[Reach out to the YData team](https://ydata.ai/contact-us) to learn more about YData Fabric.
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