# Getting started Redivis is a platform that allows researchers to seamlessly discover, access, and analyze data. This brief guide will walk you through the basics to get up and running and provide a launching point for exploring other resources in this documentation. {% embed url="" %} ## 1. Create your account Many datasets on Redivis are public, and you can browse them without creating an account. However, you'll need an account in order to analyze data, as well as to apply for access to restricted datasets. Click the **Create account** button in the top right of any page to sign up. You can use your academic institution's login credentials or any Google account. Once you create an account, you'll be navigated to your **Workspace,** which is your private area for creating workflows to work with data, uploading your own datasets, and managing your Redivis account. ## 2. Join an organization Most data on Redivis is uploaded and managed by an organization. If you've arrived here because an organization you're working with is using Redivis to host and manage data then you'll want to get started by finding and joining your organization. You can browse **organizations** by clicking the Redivis logo in the top left corner of any Redivis page to navigate to the [Explore](https://redivis.com/explore) page. Once you find an organization, you can **Join** it which will add this Organization to your workspace and allow you to start applying for any restricted access datasets they have. You can also skip this step and use Redivis to find data directly if you're not affiliated with an organization! ## 3. Find datasets All data on Redivis is stored within a Dataset. If you've joined an organization you can find datasets managed by your Organization by going to your organization's home page and clicking on the **Datasets** tab. You can also look for datasets in your broader institution (such as [Stanford](https://redivis.com/stanford) or [Columbia](https://redivis.com/columbia)) or across all of Redivis on the [Explore](https://redivis.com/explore) page. ![](https://1672950126-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-LVodLwUXgJUGcm5Cvso%2Fuploads%2FP7xlmP8dMzQ7dS5UPN6w%2FScreenshot%202024-12-09%20at%207.16.46%E2%80%AFPM_out.png?alt=media\&token=cd2c47bd-e3d5-4a95-a88b-35b69c6375fc) All searches perform a full-text search across a dataset, its documentation, tables, variables, and rich metadata content. Click on any dataset title to go to that **Dataset** page where you can view the data and metadata it contains. The data for this dataset will be available on the **Tables** tab, which you can explore further. While looking for data you will also probably come across restricted datasets. For these you will need to click the **Apply for access** button on the top right of the **Dataset** page and complete the requirements to gain approval from the dataset's administrators. *Learn more in the* [*Discover & access data*](https://docs.redivis.com/guides/discover-and-access-data) *guide.* ## 4. Analyze data Once you've found a dataset that you want to work with, you can add it to a **Workflow**. Workflows are the fundamental analysis interface on Redivis, where you can query, merge, reshape, and analyze any dataset that you have access to — all from within your web browser. Add a dataset to a workflow by clicking the **Analyze in workflow** button on the top right of the dataset page. ![](https://1672950126-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-LVodLwUXgJUGcm5Cvso%2Fuploads%2FAlc7nGQ3Wp83kn6rn6DP%2FScreenshot%202024-12-09%20at%206.40.58%E2%80%AFPM_out.png?alt=media\&token=4fb3acef-a0f5-48eb-ba42-e60dad414cd2) In a workflow we can create a **Transform** by selecting any table and clicking the **+Transform** button, which allows us to combine and reshape our data into a final output table that best serves our analysis. These transforms use a powerful SQL engine under the hood, allowing us to query incredibly large tables - even billions of records - in seconds. After creating output tables for analysis, we can create a computational **Notebook** in R, Python, Stata, or SAS to further analyze our data and develop our final figures. Select any table and click the **+Notebook** button to get started. The notebook will initialize and pull in the table you've selected (or a sample of the table if it is a large table). We can also export and query this table from external environments, allowing us to use whatever analytical tools best suit our research question by clicking the **Export table** button on the right side of any table. Here we can download the table in a number of common formats, interface with the it programmatically via the API, or export the table to supported integrations. *Learn more in the* [*Analyze data in a workflow*](https://docs.redivis.com/guides/analyze-data-in-a-workflow) *guide.* ## Next steps #### Upload your own datasets Augment your data analysis in Redivis by uploading your own datasets, with the option to share with your collaborators (or even the broader research community). *Learn more in the* [*Create & manage datasets*](https://docs.redivis.com/guides/create-and-manage-datasets/create-and-populate-a-dataset) *guide.* #### **Administer your organization** Organizations allow for research groups and centers to securely distribute data to their research community. Organization administrators can create datasets, manage access, review logs, and create customized reports of their data utilization. *Contact an existing administrator to add you to their organization, or* [*contact us*](https://redivis.com/contact) *to set up a new organization. Learn more in the* [*Administer an organization*](https://docs.redivis.com/guides/administer-an-organization) *guide.* --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.redivis.com/guides/getting-started.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.