Harness Zero Copy information sharing from Salesforce Knowledge Cloud to Amazon Redshift for Unified Analytics – Half 2

Within the period of digital transformation and data-driven determination making, organizations should quickly harness insights from their information to ship distinctive buyer experiences and achieve aggressive benefit. Salesforce and Amazon have collaborated to assist prospects unlock worth from unified information and speed up time to insights with bidirectional Zero Copy information sharing between Salesforce Knowledge Cloud and Amazon Redshift.

Within the Half 1 of this collection, we mentioned how one can configure information sharing between Salesforce Knowledge Cloud and prospects’ AWS accounts in the identical AWS Area. On this publish, we talk about the structure and implementation particulars of cross-Area information sharing between Salesforce Knowledge Cloud and prospects’ AWS accounts.

Answer overview

Salesforce Knowledge Cloud gives a point-and-click expertise to share information with a buyer’s AWS account. On the AWS Lake Formation console, you’ll be able to settle for the datashare, create the useful resource hyperlink, mount Salesforce Knowledge Cloud objects as information catalog views, and grant permissions to question the dwell and unified information in Amazon Redshift. Cross-Area information sharing between Salesforce Knowledge Cloud and a buyer’s AWS accounts is supported for 2 deployment eventualities: Amazon Redshift Serverless and Redshift provisioned clusters (RA3).

Cross-Area information sharing with Redshift Serverless

The next structure diagram depicts the steps for establishing a cross-Area datashare between a Knowledge Cloud occasion in US-WEST-2 with Redshift Serverless in US-EAST-1.

Cross-Area information sharing arrange consists of the next steps:

1. The Knowledge Cloud admin identifies the objects to be shared and creates a Knowledge Share within the information cloud provisioned within the US-WEST-2
2. The Knowledge Cloud admin hyperlinks the Knowledge Share with the Amazon Redshift Knowledge Share goal. This creates an AWS Glue Knowledge Catalog view and a cross-account Lake Formation useful resource share utilizing the AWS Useful resource Entry Supervisor (RAM) with the shopper’s AWS account in US-WEST-2.
3. The shopper’s Lake Formation admin accepts the datashare invitation in US-WEST-2 from the Lake Formation console and grants default (choose and describe) permissions to an AWS Identification and Entry Administration (IAM) principal.
4. The Lake Formation admin switches to US-EAST-1 and creates a useful resource hyperlink pointing to the shared database within the US-WEST-2 Area.
5. The IAM principal can log in to the Amazon Redshift question editor in US-EAST-1 and creates an exterior schema referencing the datashare useful resource hyperlink. The info might be queried by means of these exterior tables.

Cross-Area information sharing with a Redshift provisioned cluster

Cross-Area information sharing throughout Salesforce Knowledge Cloud and a Redshift provisioned cluster requires further steps on prime of the Serverless arrange. Based mostly on the Amazon Redshift Spectrum concerns, the provisioned cluster and the Amazon Easy Storage Service (Amazon S3) bucket should be in the identical Area for Redshift exterior tables. The next structure depicts a design sample and steps to share information with Redshift provisioned clusters.

Steps 1–5 within the arrange stay the identical throughout Redshift Serverless and provisioned cluster cross-Area sharing. Encryption should be enabled on each Redshift Serverless and the provisioned cluster. Listed under are the extra steps:

6. Create a desk from datashare information with the CREATE TABLE AS SELECT Create a datashare in Redshift serverless and grant entry to the Redshift provisioned cluster.
7. Create a database within the Redshift provisioned cluster and grant entry to the goal IAM principals. The datashare is prepared for question.

The brand new desk must be refreshed periodically to get the most recent information from the shared Knowledge Cloud objects with this resolution.

Concerns when utilizing information sharing in Amazon Redshift

For a complete listing of concerns and limitations of knowledge sharing, check with Concerns when utilizing information sharing in Amazon Redshift. A few of the essential ones for Zero Copy information sharing consists of:

• Knowledge sharing is supported for all provisioned RA3 occasion sorts (ra3.16xlarge, ra3.4xlarge, and ra3.xlplus) and Redshift Serverless. It isn’t supported for clusters with DC and DS node sorts.
• For cross-account and cross-Area information sharing, each the producer and client clusters and serverless namespaces should be encrypted. Nevertheless, they don’t have to share the identical encryption key.
• Knowledge Catalog multi-engine views are usually out there in business Areas the place Lake Formation, the Knowledge Catalog, Amazon Redshift, and Amazon Athena can be found.
• Cross-Area sharing is accessible in all LakeFormation supported areas.

Stipulations

The stipulations stay the identical throughout same-Area and cross-Area information sharing, that are required earlier than continuing with the setup.

Configure cross-Area information sharing

The steps to create a datashare, create a datashare goal, hyperlink the datashare goal to the datashare, and settle for the datashare in Lake Formation stay the identical throughout same-Area and cross-Area information sharing. Discuss with Half 1 of this collection to finish the setup.

Cross-Area information sharing with Redshift Serverless

In case you’re utilizing Redshift Serverless, full the next steps:

1. On the Lake Formation console, select Databases within the navigation pane.
2. Select Create database.
3. Below Database particulars¸ choose Useful resource hyperlink.
4. For Useful resource hyperlink title, enter a reputation for the useful resource hyperlink.
5. For Shared database’s area, select the Knowledge Catalog view supply Area.
6. The Shared database and Shared database’s proprietor ID fields are populated manually from the database metadata.
7. Select Create to finish the setup.
   

The useful resource hyperlink seems on the Databases web page on the Lake Formation console, as proven within the following screenshot.

8. Launch Redshift Question Editor v2 for the Redshift Serverless workspace The cross-region information share tables are auto-mounted and seem beneath awsdatacatalog. To question, run the next command and create an exterior schema. Specify the useful resource hyperlink because the Knowledge Catalog database, the Redshift Serverless Area, and the AWS account ID.

   CREATE exterior SCHEMA cross_region_data_share --<<SCHEMA_NAME>>
   FROM DATA CATALOG DATABASE 'cross-region-data-share' --<<RESOURCE_LINK_NAME>>
   REGION 'us-east-1' --<TARGET_REGION>
   IAM_ROLE 'SESSION' CATALOG_ID '<<aws_account_id>>'; --<<REDSHIFT AWS ACCOUNT ID>>

9. Refresh the schemas to view the exterior schema created within the dev database
   
10. Run the present tables command to examine the shared objects beneath the exterior database:

    SHOW TABLES FROM SCHEMA dev.cross_region_data_share --<<schema title>>

    

11. Question the datashare as proven within the following screenshot.

    SELECT * FROM dev.cross_region_data_share.churn_modellingcsv_tableaus3_dlm; --<<change schema title & desk title>>

    

Cross-Area information sharing with Redshift provisioned cluster

This part is a continuation of the earlier part with further steps wanted for information sharing to work when the patron is a provisioned Redshift cluster. Discuss with Sharing information in Amazon Redshift and Sharing datashares for a deeper understanding of ideas and the implementation steps.

1. Create a brand new schema and desk within the Redshift Serverless within the client Area:

   CREATE SCHEMA customer360_data_share;
   CREATE TABLE customer360_data_share. customer_churn as
   SELECT * from dev.cross_region_data_share.churn_modellingcsv_tableaus3__dlm;

   

2. Get the namespace for the Redshift Serverless (producer) and Redshift provisioned cluster (client) by working the next question in every cluster:

   

3. Create a datashare within the Redshift Serverless (producer) and grant utilization to the Redshift provisioned cluster (client). Set the datashare, schema, and desk names to the suitable values, and set the namespace to the patron namespace.

   CREATE DATASHARE customer360_redshift_data_share;
   ALTER DATASHARE customer360_redshift_data_share ADD SCHEMA customer360_data_share;
   ALTER DATASHARE customer360_redshift_data_share ADD TABLE customer360_data_share.customer_churn; 
   GRANT USAGE ON DATASHARE customer360_redshift_data_share 
   TO NAMESPACE '5709a006-6ac3-4a0c-a609-d740640d3080'; --<<Knowledge Share Client Namespace>>

   

4. Log in as a superuser within the Redshift provisioned cluster, create a database from the datashare, and grant permissions. Discuss with managing permissions for Amazon Redshift datashare for detailed steerage.
   

The datashare is now prepared for question.

You possibly can periodically refresh the desk you created to get the most recent information from the information cloud primarily based on your enterprise requirement.

Conclusion

Zero Copy information sharing between Salesforce Knowledge Cloud and Amazon Redshift represents a major development in how organizations can use their buyer 360 information. By eliminating the necessity for information motion, this strategy presents real-time insights, diminished prices, and enhanced safety. As companies proceed to prioritize data-driven decision-making, Zero Copy information sharing will play an important function in unlocking the complete potential of buyer information throughout platforms.

This integration empowers organizations to interrupt down information silos, speed up analytics, and drive extra agile customer-centric methods. To study extra, check with the next sources:

Concerning the Authors

Rajkumar Irudayaraj is a Senior Product Director at Salesforce with over 20 years of expertise in information platforms and companies, with a ardour for delivering data-powered experiences to prospects.

Sriram Sethuraman is a Senior Supervisor in Salesforce Knowledge Cloud product administration. He has been constructing merchandise for over 9 years utilizing large information applied sciences. In his present function at Salesforce, Sriram works on Zero Copy integration with main information lake companions and helps prospects ship worth with their information methods.

Jason Berkowitz is a Senior Product Supervisor with AWS Lake Formation. He comes from a background in machine studying and information lake architectures. He helps prospects turn into data-driven.

Ravi Bhattiprolu is a Senior Accomplice Options Architect at AWS. Ravi works with strategic ISV companions, Salesforce and Tableau, to ship progressive and well-architected merchandise and options that assist joint prospects obtain their enterprise and technical targets.

Avijit Goswami is a Principal Options Architect at AWS specialised in information and analytics. He helps AWS strategic prospects in constructing high-performing, safe, and scalable information lake options on AWS utilizing AWS managed companies and open supply options. Outdoors of his work, Avijit likes to journey, hike, watch sports activities, and hearken to music.

Ife Stewart is a Principal Options Architect within the Strategic ISV section at AWS. She has been engaged with Salesforce Knowledge Cloud during the last 2 years to assist construct built-in buyer experiences throughout Salesforce and AWS. Ife has over 10 years of expertise in expertise. She is an advocate for range and inclusion within the expertise discipline.

Michael Chess is a Technical Product Supervisor at AWS Lake Formation. He focuses on enhancing information permissions throughout the information lake. He’s obsessed with enabling prospects to construct and optimize their information lakes to fulfill stringent safety necessities.

Mike Patterson is a Senior Buyer Options Supervisor within the Strategic ISV section at AWS. He has partnered with Salesforce Knowledge Cloud to align enterprise targets with progressive AWS options to realize impactful buyer experiences. In his spare time, he enjoys spending time together with his household, sports activities, and outside actions.