odbc

From Data to Dollars: Improving Medical Billing Accuracy Using NLP (Julianne Gent, Emory Healthcare)

Protecting our Healthcare Heroes: Using Natural Language Processing to Prevent Billing Mistakes in Healthcare

Speaker(s): Julianne Gent

Abstract:

Edgar Ruiz - Easing the pain of connecting to databases

Workflow Demo Live Q&A - September 25th!

Data-level permissions using Posit Connect (with Databricks, Snowflake, OAuth)

Should one viewer of your app be able to see more (or different) data than another? Maybe colleagues in California should only see data relevant to them? Or managers should only have access to their own employee data?

The Connect team joined us for a demo on inheriting data-level permissions using Posit Connect and Databricks Unity Catalog. While this workflow uses Databricks to illustrate federated data access controls, this same methodology can also be applied to Snowflake or any external data source that supports OAuth.

During this workflow demo, you will learn:

1. How to define row-level access controls in Databricks Unity Catalog
2. How to create a Databricks OAuth integration in Posit Connect
3. How to write interactive applications that utilize the viewer’s Databricks credentials when reading data from Databricks Unity Catalog, providing the viewer with a personalized experience depending on their level of data access
4. How to deploy this application to Posit Connect and share it within your organization

Predicting Lending Rates with Databricks, tidymodels, and Posit Team

Machine learning algorithms are reshaping financial decision-making, changing how the industry manages financial risk.

For our workflow demo today on June 26th at 11 am ET, Garrett Grolemund at Posit will show how to use both Posit and Databricks to apply machine learning methods to the consumer credit market, where accurately predicting lending rates is critical for customer acquisition.

*Please note that while the workflow focuses on a financial example, the general workflow will be useful to those using Databricks and R together across any industry.

During this workflow demo, you will learn how to:

1. Connect to historical lending rate data stored in Databricks Delta Lake
2. Tune and cross-validate a penalized linear regression (LASSO) that predicts interest rates
3. Select variables with the penalized linear regression model (LASSO)
4. Build an interactive Shiny app to provide a customer-facing user interface for our model
5. Deploy the app to production on Posit Connect, and arrange for the app to access Databricks

Connecting RStudio and Databricks with ODBC

The odbc package, in conjunction with a driver, provides DBI support and an ODBC connection.

With the new odbc::databricks_connect function, you can create an ODBC connection to determine and configure the necessary settings to access your Databricks account. Your Databricks HTTP path is the only argument you need to run databricks_connect(). Provide your HTTP path and you will be able to see your Databricks data in the RStudio Connections Pane. Then, you can analyze your data in RStudio.

Learn more:

Databricks Pro Driver in Posit Workbench

We’ve added a Databricks driver to our Professional Drivers. The RStudio Connections Pane allows users to connect to their Databricks clusters from the IDE. Select the Databricks driver from the list of available drivers. Select the Driver to establish the connection. The driver can be used with the new databricks() function from the odbc package to connect to Databricks clusters and SQL warehouses.

Learn more:

Databricks x Posit | Improved Productivity for your Data Teams

Timestamps: 0:00-7:30 Introduction to Databricks 7:31-15:40 Introduction to Posit 15:41-27:51 Demo of VS Code, Model Serving 27:52-30:00 Demo of signing into Posit Workbench via OAuth 30:01-37:50 New Databricks pane: accessing Databricks compute and exploring data in Unity Catalog via Databricks Connect 37:51-43:40 New Simplified ODBC access to Databricks 43:41-50:06 Publishing data apps to Posit Connect with a Databricks backend 50:07-51:18 Demo recap 51:19-54:15 Roadmap and the future 54:16-1:07:33 Q&A

Leveraging R & Python in Tableau with RStudio Connect | James Blair | RStudio

Leveraging R & Python in Tableau with RStudio Connect Overview Demo / Q&A with James Blair

Tableau combines the ease of drag-and-drop visual analytics with an open, extensible platform. RStudio develops free and open tools for data science, including the world’s most popular IDE for R. RStudio also develops an enterprise-ready, modular data science platform to help data science teams using R and Python scale and share their work.

Now, with new functionality in RStudio Connect, users can have the best of both worlds. Tableau users can call R and Python APIs from Tableau calculated fields, getting access to all the power and analytic depth of these open-source data science ecosystems in real-time.

For Tableau users, this makes it easy to add dynamic, advanced analytic features from R and Python to a Tableau dashboard, such as scoring predictive models on Tableau data. They can leverage all the great work done by their organization’s data science team and even call both R and Python APIs from a single dashboard.

Data science teams can continue to use the code-first development and deployment tools from RStudio that they know and love. Using these tools, they can build and share R APIs (using the plumber package) and Python APIs (using the FastAPI framework).

Speaker Bio: James is a Solutions Engineer at RStudio, where he focuses on helping RStudio commercial customers successfully manage RStudio products. He is passionate about connecting R to other toolchains through tools like ODBC and APIs. He has a background in statistics and data science and finds any excuse he can to write R code.

James Blaire & Barret Schloerke | Integrating R with Plumber APIs | RStudio (2020)

Full title: Expanding R Horizons: Integrating R with Plumber APIs

In this webinar we will focus on using the Plumber package as a tool for integrating R with other frameworks and technologies. Plumber is a package that converts your existing R code to a web API using unique one-line comments. Example use cases will be used to demonstrate the power of APIs in data science and to highlight new features of the Plumber package. Finally, we will look at methods for deploying Plumber APIs to make them widely accessible.