> For the complete documentation index, see [llms.txt](https://docs.sdv.dev/sdv/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sdv.dev/sdv/get-started.md).

# Get Started

## How it works?

SDV is designed to learn statistical patterns from your training data and then emulate those patterns when creating synthetic data. The patterns are saved in a synthesizer object. You can think of your synthesizer as a model that contains a condensed representation of your data.

{% stepper %}
{% step %}

### Data Integration

Load your data into SDV. You can connect your database or load in data from a local file. Then, create a metadata object that contains a description of your data for SDV to use.\
[More Information → ](/sdv/integration/overview.md)
{% endstep %}

{% step %}

### Modeling

Create a synthesizer and use it to learn patterns from your training data. Pick from a variety of synthesizers that incorporate various different ML modeling techniques.\
[More Information → ](/sdv/modeling/single-table-synthesizers.md)
{% endstep %}

{% step %}

### Sampling

Use your synthesizer to generate realistic synthetic data on-demand. Or supply instructions to your synthesizer to create specific types of data. When you're done, export the synthetic data into a different file or database.\
[More Information→](/sdv/sampling/sample-realistic-data.md) 
{% endstep %}

{% step %}

### Evaluation

Evaluate the synthetic data by comparing it against the real data. Check for basic diagnostic stats, compare the statistical quality, and visualize any differences.\
[More Information→](/sdv/evaluation/diagnostic.md) 
{% endstep %}
{% endstepper %}

## Tutorials

Use SDV Community to explore synthetic data, and create synthesizers for simple, proof-of-concept datasets. 

<table data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th><th data-hidden data-card-cover data-type="files"></th></tr></thead><tbody><tr><td><a href="https://colab.research.google.com/drive/1MCTkTj9-93Ei-cLDQoj9AXaqPhpue7a3?usp=sharing"><strong>Synthesize a Table (Gaussian Copula)</strong></a></td><td>A fast, customizable and transparent way to synthesize data.</td><td><a href="https://colab.research.google.com/drive/1MCTkTj9-93Ei-cLDQoj9AXaqPhpue7a3?usp=sharing">https://colab.research.google.com/drive/1MCTkTj9-93Ei-cLDQoj9AXaqPhpue7a3?usp=sharing</a></td><td></td></tr><tr><td><a href="https://colab.research.google.com/drive/15iom9fO8j_gHg4-NlGkzWF5thMWStXwv?usp=sharing"><strong>Synthesize a Table (CTGAN)</strong></a></td><td>A GAN-based approach to creating synthetic data with high fidelity.</td><td><a href="https://colab.research.google.com/drive/15iom9fO8j_gHg4-NlGkzWF5thMWStXwv?usp=sharing">https://colab.research.google.com/drive/15iom9fO8j_gHg4-NlGkzWF5thMWStXwv?usp=sharing</a></td><td></td></tr><tr><td><a href="https://colab.research.google.com/drive/1YLk2uwn8yrSRPy0soEeJwu8Hdk_tGTlE?usp=sharing"><strong>Synthesize Sequences (PAR)</strong></a></td><td>A neural network-based approach to creating synthetic data.</td><td><a href="https://colab.research.google.com/drive/1YLk2uwn8yrSRPy0soEeJwu8Hdk_tGTlE?usp=sharing">https://colab.research.google.com/drive/1YLk2uwn8yrSRPy0soEeJwu8Hdk_tGTlE?usp=sharing</a></td><td></td></tr><tr><td><a href="https://colab.research.google.com/drive/1L6i-JhJK9ROG-KFcyzT9G-8FC3L8y8Lc?usp=sharing"><strong>Synthesize Multi Tables (HMA)</strong></a></td><td>Synthesize data across multiple, connected tables in a database.</td><td><a href="https://colab.research.google.com/drive/1L6i-JhJK9ROG-KFcyzT9G-8FC3L8y8Lc?usp=sharing">https://colab.research.google.com/drive/1L6i-JhJK9ROG-KFcyzT9G-8FC3L8y8Lc?usp=sharing</a></td><td></td></tr><tr><td><a href="https://colab.research.google.com/drive/1DlUlHNohxBhxN6GA5C_C4Fd9wx5AR11Y?usp=sharing"><strong>Use Your Own Data</strong></a></td><td>Prepare your own data for the SDV:  Load your raw data and write a metadata description</td><td><a href="https://colab.research.google.com/drive/1DlUlHNohxBhxN6GA5C_C4Fd9wx5AR11Y?usp=sharing">https://colab.research.google.com/drive/1DlUlHNohxBhxN6GA5C_C4Fd9wx5AR11Y?usp=sharing</a></td><td></td></tr></tbody></table>

### Customizations

Using SDV Community, you can control the full workflow when preprocessing data, anonymizing sensitive values, adding constraints and more.

<table data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><a href="https://colab.research.google.com/drive/1Z9Rff5G3eDI-LEc1LXiew9E3hF5Ob-on?usp=sharing"><strong>Custom Processing &#x26; Anonymization</strong></a></td><td>Improve your synthesizer by customizing the data processing workflow.</td><td><a href="https://colab.research.google.com/drive/1Z9Rff5G3eDI-LEc1LXiew9E3hF5Ob-on?usp=sharing">https://colab.research.google.com/drive/1Z9Rff5G3eDI-LEc1LXiew9E3hF5Ob-on?usp=sharing</a></td></tr><tr><td><a href="https://colab.research.google.com/drive/1WCMQujfVKL5giULZXOPPIBoMfzR9Zj68?usp=sharing"><strong>Constraint-Augmented Generation</strong></a></td><td>Input business rules into your synthesizer using constraints. This ensures high-quality, valid synthetic data, 100% of the time.</td><td><a href="https://colab.research.google.com/drive/1WCMQujfVKL5giULZXOPPIBoMfzR9Zj68?usp=sharing">https://colab.research.google.com/drive/1WCMQujfVKL5giULZXOPPIBoMfzR9Zj68?usp=sharing</a></td></tr></tbody></table>


---

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