This put up is co-authored by Rajkumar Irudayaraj, Sr. Director of Product, Salesforce Knowledge Cloud.
In in the present day’s ever-evolving enterprise panorama, organizations should harness and act on knowledge to gasoline analytics, generate insights, and make knowledgeable selections to ship distinctive buyer experiences. Salesforce and Amazon have collaborated to assist prospects unlock worth from unified knowledge and speed up time to insights with bidirectional Zero Copy knowledge sharing between Salesforce Knowledge Cloud and Amazon Redshift.
In a earlier put up, we confirmed how Zero Copy knowledge federation empowers companies to entry Amazon Redshift knowledge throughout the Salesforce Knowledge Cloud to counterpoint buyer 360 knowledge with operational knowledge. This two-part sequence explores how analytics groups can entry buyer 360 knowledge from Salesforce Knowledge Cloud inside Amazon Redshift to generate insights on unified knowledge with out the overhead of extract, rework, and cargo (ETL) pipelines. On this put up, we cowl knowledge sharing between Salesforce Knowledge Cloud and prospects’ AWS accounts in the identical AWS Area. Half 2 covers cross-Area knowledge sharing between Salesforce Knowledge Cloud and prospects’ AWS accounts.
What’s Salesforce Knowledge Cloud?
Salesforce Knowledge Cloud is a knowledge platform that unifies your entire firm’s knowledge into Salesforce’s Einstein 1 Platform, giving each crew a 360-degree view of the shopper to drive automation, create analytics, personalize engagement, and energy trusted synthetic intelligence (AI). Salesforce Knowledge Cloud creates a holistic buyer view by turning volumes of disconnected knowledge right into a unified buyer profile that’s simple to entry and perceive. This unified view helps your gross sales, service, and advertising groups construct customized buyer experiences, invoke data-driven actions and workflows, and safely drive AI throughout all Salesforce purposes.
What’s Amazon Redshift?
Amazon Redshift is a quick, totally managed, petabyte-scale knowledge warehouse service that makes it easy and cost-effective to effectively analyze all of your knowledge utilizing your current enterprise intelligence (BI) instruments. It’s optimized for datasets starting from a number of hundred gigabytes to petabytes and delivers higher price-performance in comparison with different knowledge warehousing options. With a completely managed, AI-powered, massively parallel processing (MPP) structure, Amazon Redshift makes enterprise decision-making fast and cost-effective. Amazon Redshift Spectrum permits querying structured and semi-structured knowledge in Amazon Easy Storage Service (Amazon S3) with out having to load the information into Redshift tables. Redshift Spectrum integration with AWS Lake Formation permits querying auto-mounted AWS Glue Knowledge Catalog tables with AWS Identification and Entry Administration (IAM) credentials and harnessing Lake Formation for permission grants and entry management insurance policies on Knowledge Catalog views. Salesforce Knowledge Cloud Knowledge sharing with Amazon Redshift leverages AWS Glue Knowledge Catalog assist for multi-engine views and Redshift Spectrum integration with Lake Formation.
What’s Zero Copy knowledge sharing?
Zero Copy knowledge sharing permits Amazon Redshift prospects to question buyer 360 knowledge saved in Salesforce Knowledge Cloud with out the necessity for conventional ETL to maneuver or copy the information. As a substitute, you merely join and use the information in place, unlocking its worth instantly with on demand entry to the newest knowledge. Knowledge sharing is supported with each Amazon Redshift Serverless and provisioned RA3 clusters. Knowledge may be shared with a Redshift Serverless or provisioned cluster in the identical Area or with a Redshift Serverless cluster in a distinct Area. To get an summary of Salesforce Zero Copy integration with Amazon Redshift, please confer with this Salesforce Weblog.
Resolution overview
Salesforce Knowledge Cloud supplies a point-and-click expertise to share knowledge with a buyer’s AWS account. On the Lake Formation console, you possibly can settle for the information share, create the useful resource hyperlink, mount Salesforce Knowledge Cloud objects as knowledge catalog views, and grant permissions to question the reside and unified knowledge in Amazon Redshift.
The next diagram depicts the end-to-end course of concerned for sharing Salesforce Knowledge Cloud knowledge with Amazon Redshift in the identical Area utilizing a Zero Copy structure. This structure follows the sample documented in Cross-account knowledge sharing finest practices and issues.
The information share setup consists of the next high-level steps:
- The Salesforce Knowledge Cloud admin creates the information share goal with the goal account for the information share.
- The Salesforce Knowledge Cloud admin selects the information cloud objects to be shared with Amazon Redshift and creates a knowledge share.
- The Salesforce Knowledge Cloud admin hyperlinks the information share to the information share goal, which invokes the next operations to create a cross-account useful resource share:
- Create a Knowledge Catalog view for the Salesforce Knowledge Cloud Apache Iceberg tables by invoking the Catalog API.
- Use Lake Formation sharing to create a cross-account Knowledge Catalog share.
- Within the buyer AWS account, the Lake Formation admin logs in to the Lake Formation console to just accept the useful resource share, create a useful resource hyperlink, and grant entry permissions to the Redshift function.
- The information analyst launches the Amazon Redshift Question Editor with the suitable function to question the information share and be a part of with native Redshift tables.
Conditions
The next are the conditions to allow knowledge sharing:
- A Salesforce Knowledge Cloud account.
- An AWS account with AWS Glue and Lake Formation enabled.
- Both a Redshift Serverless or a Redshift provisioned cluster with RA3 occasion sorts (ra3.16xlarge, ra3.4xlarge, ra3.xlplus). Knowledge sharing will not be supported for different provisioned occasion sorts like DC2 or DS2 and should be arrange earlier than accessing the information share. In case you don’t have an current provisioned Redshift RA3 cluster, we suggest utilizing a Redshift Serverless namespace for ease of operations and upkeep.
- The Amazon Redshift service should be working in the identical Area the place the Salesforce Knowledge Cloud is working.
- AWS admin roles for Lake Formation and Amazon Redshift:
Create the information share goal
Full the next steps to create the information share goal:
- In Salesforce Knowledge Cloud, select App Launcher and select Knowledge Share Targets.
- Select New and select Amazon Redshift, then select Subsequent.
- Enter the small print for Label, API Identify, and Account for the information share goal.
- Select Save.
After you save these settings, the S3 Tenant Folder worth is populated.
- Select the S3 Tenant Folder hyperlink and replica the verification token.
In case you’re not signed in to the AWS Administration Console, you’ll be redirected to the login web page.
- Enter the verification token and select Save.
The information share goal turns to lively standing.
Create a knowledge share
Full the next steps to create a knowledge share:
- Navigate to the Knowledge Share tab in your Salesforce org.
- Select App Launcher and select Knowledge Shares.
Alternatively, you possibly can navigate to the Knowledge Share tab out of your org’s house web page.
- Select New, then select Subsequent.
- Present a label, identify, knowledge house, and outline, then select Subsequent.
- Choose the objects to be included within the share and select Save.
Hyperlink the information share goal to the information share
To hyperlink the information share goal to the information share, full the next steps:
- On the information share document house web page, select Hyperlink/Unlink Knowledge Share Goal.
- Choose the information share goal you wish to hyperlink to the information share and select Save.
The information share should be lively earlier than you possibly can settle for the useful resource share on the Lake Formation console.
Settle for the information share in Lake Formation
This part supplies the detailed steps for accepting the information share invite and configuration steps to mount the information share with Amazon Redshift.
- After the information share is efficiently linked to the information share goal, navigate to the Lake Formation console.
The information share invitation banner is displayed.
- Select Settle for and create.
The Settle for and create web page exhibits a useful resource hyperlink and supplies the choice to arrange IAM permissions.
- Within the Principals part, select the IAM customers and roles to grant the default permissions (describe and choose) for the information share useful resource hyperlink.
- Select Create.
The useful resource hyperlink created within the earlier step seems subsequent to the AWS Glue database useful resource share on the Lake Formation console.
Question the information share from Redshift Serverless
Launch the question editor for Redshift Serverless and log in as a federated person with the function that has describe and choose permissions for the useful resource hyperlink.
The information share tables are auto-mounted, seem beneath awsdatacatalog, and may be queried as proven within the following screenshot.
Question the information share from the Redshift provisioned cluster
To question the information share from the Redshift provisioned cluster, log in to the provisioned cluster because the superuser.
On an editor tab, run the next SQL assertion to grant an IAM person entry to the Knowledge Catalog:
IAM:myIAMUser is an IAM person that you just wish to grant utilization privilege to the Knowledge Catalog. Alternatively, you possibly can grant utilization privilege to IAMR:myIAMRole for an IAM function. For extra particulars, confer with Querying the AWS Glue Knowledge Catalog.
Log in because the person with the function from the earlier step utilizing short-term credentials.
It’s best to be capable of develop awsdatacatalog and question the information share tables as proven within the following screenshot.
Conclusion
Zero Copy knowledge sharing between Salesforce Knowledge Cloud and Amazon Redshift represents a major development in how organizations can use their buyer 360 knowledge. By eliminating the necessity for knowledge motion, this method gives real-time insights, diminished prices, and enhanced safety. As companies proceed to prioritize data-driven decision-making, Zero Copy knowledge sharing will play an important function in unlocking the total potential of buyer knowledge throughout platforms.
This integration empowers organizations to interrupt down knowledge silos, speed up analytics, and drive extra agile customer-centric methods. To study extra, confer with the next assets:
In regards to the Authors
Rajkumar Irudayaraj is a Senior Product Director at Salesforce with over 20 years of expertise in knowledge platforms and companies, with a ardour for delivering data-powered experiences to prospects.
Jason Berkowitz is a Senior Product Supervisor with AWS Lake Formation. He comes from a background in machine studying and knowledge lake architectures. He helps prospects grow to be 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 & options that assist joint prospects obtain their enterprise and technical goals.
Avijit Goswami is a Principal Options Architect at AWS specialised in knowledge and analytics. He helps AWS strategic prospects in constructing high-performing, safe, and scalable knowledge 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 phase at AWS. She has been engaged with Salesforce Knowledge Cloud over the past 2 years to assist construct built-in buyer experiences throughout Salesforce and AWS. Ife has over 10 years of expertise in know-how. She is an advocate for range and inclusion within the know-how area.
Michael Chess is a Technical Product Supervisor at AWS Lake Formation. He focuses on bettering knowledge permissions throughout the information lake. He’s obsessed with making certain prospects can construct and optimize their knowledge lakes to fulfill stringent safety necessities.
Mike Patterson is a Senior Buyer Options Supervisor within the Strategic ISV phase at AWS. He has partnered with Salesforce Knowledge Cloud to align enterprise goals with progressive AWS options to attain impactful buyer experiences. In his spare time, he enjoys spending time along with his household, sports activities, and out of doors actions.