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
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
Collaborate with partners utilizing Databricks Clean Rooms.