# Data Collaboration and Sharing

Data Collaboration and Sharing is a powerful concept that allows enterprises to unlock unique use cases for their organization. These use cases must be supported with the appropriate design that takes into consideration the security and privacy while still achieving appropriate utility. Rearc can help implement an appropriate solution to meet your Data Collaboration needs.

## Use Cases

### What are your goals?

Modern Data collaboration and Sharing enable you to drive additional value for your business without giving up control. Data is valuable, but you only see your part of the picture. Working with trusted business partners, you can combine data to drive even greater value for both parties. You might work together to build a new model, research joint customer trends, and more. Your data collaboration and sharing needs are specific. Develop an actionable plan for them with Rearc.

- Perform joint analytics and insights with partners
- Drive Revenue through Data Products
- Share insights across internal business units
- Develop new ML models with collaborators

## Techniques

### Data Sharing Trade Offs

Different approaches may be required to achieve your needs

01  Replication

The simplest form of sharing, where data is copied and provided to a recipient. The usability of the data set is high but there is little security or control of the data that is duplicated.

02  Direct Access

Direct Table access can increase the security of the data by reducing replication. Direct sharing utilizes technologies such as Databricks Delta Sharing, to grant access to specified parties.

03  Filtered Access

Filtering, aggregation and anonymization techniques may be utilized to improving the security and privacy of a data set that is being directly shared. These techniques increase the complexity of sharing the data while also reducing the utility of the data set due to its modification.

04  Clean Rooms

Clean rooms provide a secure, independent compute environment for data collaboration. This approach enhances utility and flexibility of data sharing.

## Capabilities

### How can we help?

Let the experts at Rearc assist you with your Data Collaboration and Sharing needs.

- **Architecture**  
  Rearc will work directly with your stakeholders to develop a solution tailored to your use case with the right technical mix.

- **Privacy**  
  Privacy of your data is critically important. Rearc has experience with data masking, anonymization, synthetic data and differential privacy. We will implement appropriate approaches for your dataset.

- **Auditing and Logging**  
  You want to know what is happening to the data being shared with your partners. Rearc will ensure the right information is logged and available for auditing around your use case.

- **Security**  
  Rearc will work to implement security best practices and ensure appropriate data access controls. Data access will be tightly scoped to the needs of the Data Collaboration and sharing Use Case.

- **Testing**  
  Developing a data collaboration and sharing capability inherently involves multiple parties. Rearc will help develop testing without involving clients or customers directly.

## Case Studies

### Driving Customer Value_

Let us make your Data Collaboration and sharing goals a reality.

-   
  [ADX Publishing at Scale](/content/case-studies/case-study-cloud-adx-publishing/index.html)  
  Rearc was asked to help a Fortune 500 payments processing company publish data products to the AWS Data Exchange enabling new data-driven revenue streams and broader customer reach.

-   
  [Databricks Clean Rooms](/content/case-studies/databricks-clean-rooms/index.html)  
  Collaborate with partners utilizing Databricks Clean Rooms.

## Tech Stack

### Tools that help us deliver the best results.

- [Delta Sharing](https://delta.io/sharing/)  
- [Databricks Clean Rooms](https://www.databricks.com/product/clean-room)  
- [AWS Clean Rooms](https://aws.amazon.com/clean-rooms/)