Training materials, FAQs, video tutorials, guides, and a designated help desk are available to assist researchers in their Workbench activities. All of Us genomic data are only available through the Controlled Tier of the Researcher Workbench. Currently, only registered researchers whose institutions have Data Use and Registration Agreements in place with All of Us that include the Controlled Tier can access genomic data.

If your institution has access, you can follow the steps on our Register page to become an All of Us researcher. Accessing the Researcher Workbench data is easy and takes only a few steps. If you are interested in applying for Researcher Workbench access, please visit the Register page for information on the steps you will need to complete.

A cohort is a group of participants whom researchers are interested in studying. Researchers can create cohorts by adding inclusion or exclusion criteria. Researchers should always check with their local institutional review board to ensure compliance with local requirements for conduct of research.

We have provided the template language below as a resource to use for local IRB applications. All data available to researchers has had direct identifiers removed and has been further modified to minimize re-identification risks.

This includes removing all explicit identifiers in both EHRs and participant provided information, all free-text fields, geolocation data smaller than U.

state level, living situations, race and ethnicity subcategories, active duty military status, cause of death, and diagnosis codes subject to public knowledge.

Additionally, the following demographic fields are generalized: race and ethnicity, education, employment, and information regarding sex at birth, gender identity, and sexual orientation. Also, all dates are systematically shifted backwards by a random number between 1 and , and data from participants over the age of 89 are removed.

The All of Us Research Program data will be accessed for research strictly using the Researcher Workbench researchallofus. External data can be brought into this secure environment; however, researchers are restricted from importing any individually identifiable information and from row-level linkage of the external data.

Data searches, cohort building, and analysis will solely take place on the Researcher Workbench, a secure cloud-based resource with statistical analysis software available for use with All of Us data. Researchers are granted access to the Researcher Workbench after their affiliated institution signs a Data Use and Registration Agreement, and they create an account, including setting up two-factor authentication, verify their identity through Login.

gov or ID. me, complete the All of Us Responsible Conduct of Research training, and sign a Data User Code of Conduct, which prohibits any re-identification of All of Us participants.

For more information, please visit researchallofus. Our Data Browser includes Public Tier aggregate data from physical measurements, surveys, and electronic health records, including concepts. Dismiss alert. Explore Topics Trending Collections Events GitHub Sponsors. Here are 16 public repositories matching this topic Language: All Filter by language.

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A sponsor of the WWDVC. SqlDBM is a strong supporter of the data vault community, a sponsor of the WWDVC conference two years running, and the modeling tool of choice during official data vault courses.

Hubs, links, satellites. Colors and view modes. Colors and view mode options make it easy for users to find their way around expansive DV architectures and work with them at any level of detail.

Automated DV templates and an object creation wizard are currently in the works and will be available soon, along with other exciting enhancements. Premier partner Find us on the Snowflake Partner Connect In , SqlDBM became the first online modeling tool to support Snowflake projects and has continued to add support for Snowflake's latest objects, such as views, functions, and procedures.

Get started Learn more. Strategic advisors Meet the experts and industry thought-leaders helping shape the future of SqlDBM.

Kent Graziano. The Data Warrior, Strategic Advisor, Data Vault Master, Author, Speaker, and Tae Kwon Do Grandmaster. Leading organizations through analytics transformations, preference for social missions, healthcare, energy, education, and civic engagement.

Everything you need at your fingertips Database Modeling Direct connection Lineage analysis Documentation and governance Compare Collaboration Git and DataOps. Make changes and generate new SQL scripts including alter scripts. Securely connect to cloud databases such as Snowflake and Azure Synapse directly from SqlDBM to browse schemas and retrieve DDL automatically.

Visualize sources, joins, transformations, and outputs in real-time at column level to understand complex views and DML logic quickly. Syntax to column highlighting in the editor and diagram allows users to track any field as it flows from the sources to final output.

Comments are read from DDL and available on a single screen where users can find and edit objects across the entire project. Flags help identify sensitive fields and can be used for tracking and filtering at the object or column level.

With unlimited revision history for every project, users can compare changes between any two save points and open and recover a project from a previous state. Users can instantly find any revision using labels, icons, and related filters.

Work concurrently and comment on any object tagging and alerting specific team members. View modes allow users of any technical level to view, explore, or develop a DB schema without converting the project.

Compare project revisions to live DB environments and generate ad-hoc alter scripts between them. Pair your project with any online git repository to automatically push alters or individual objects to new branches and pair with CICD tools like Schemachange or Flyway for fully automated deployments.

Get started. Data management partner Find us on the Azure Marketplace SqlDBM supports Azure Synapse modeling with extended support for views, functions, procedures, and more.

SqlDBM helps develop or transition to leading cloud data warehouses, including Snowflake, Synapse, and Redshift. Whether migrating an existing enterprise data warehouse, data lake, or building one from scratch, SqlDBM's functionality is designed to meet the needs of BI professionals by providing users with cutting-edge capabilities.

An intuitive web-based interface lowers the technical barrier and lets all team members take advantage of data discovery and explore the data landscape. From exploring business entities in a simplified conceptual view to flagging sensitive or critical fields and objects, all roles get to take advantage or contribute to project metadata without using SQL.

Like modeling in SqlDBM, change tracking and revision comparison is a simple, visual process that requires no prior knowledge of git. With Jira integration, project managers can tie model changes to Jira tasks for full audit history and synchronized comment thread.

Enterprise plan SqlDBM's Enterprise plan allows users to go beyond modeling by offering integrations like Confluence for sharing and Jira for task management.

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