#Data36046 discutindo

If you plan for workshop refer -

 The one you mentioned is paid but there are some thats free for standard plans thats what am looking for

Thanks, @Vishal Soni, @Robbie Duncan, @Kundan Kumar Jha

for sharing your thoughts! 

I agree that Data 360 is becoming an important skill, especially as Agentforce depends on accurate and trusted data.

At the same time, I feel Apex, Flow, LWC, and Integration will continue to play an important role in real-time projects.

Robbie also raised a good point about AI and context engineering. Knowing how to guide and evaluate AI agents will become increasingly valuable. 

My view is that learning one technology is not enough anymore. Understanding how Data 360, Agentforce, and other Salesforce technologies work together will be the real advantage. 

Thanks again for making this a valuable discussion!

Hi @Galla Rajeswari Good question! Data 360 is not just about combining data. It helps businesses use customer data more effectively.

1. Identity Resolution: Combines customer records to create a unified customer profile.
2. Data Graphs: Connect related data and help Agentforce access customer information faster.
3. Segmentation: Helps businesses identify and target the right customers.
4. Real-Time Activation: Helps businesses take action using updated customer data.
5. Agentforce: Provides better customer context, helping agents give more relevant and accurate responses.

In my view, Identity Resolution and Data Graphs are especially useful for Agentforce.

Key Point: Data 360 provides the right customer context, while Agentforce uses that data to answer questions and perform actions.

Great insights, @Vishal Soni Thank you for sharing this helpful roadmap.

I completely agree with your approach. I would just like to add a few points from a practical learning perspective:

• Get hands-on experience with Data Streams, DLOs, and DMOs.
• Practice Data Mapping and Identity Resolution.
• Explore Calculated Insights and Data Graphs.
• Understand how Data 360 supports Agentforce use cases.

I believe building at least one end-to-end project alongside certification preparation can really strengthen practical understanding.

Thanks again for sharing these valuable resources with the community!

Hi @Mounika Aithagoni

You would decide based on these core points:

1. Data Ingestion: Best for data transformation, identity resolution, and unified customer profiles.
2. Zero Copy: Best for accessing large external datasets without duplicating data.
3. Real-Time Data: Zero Copy with live queries can provide access to the latest source data.
4. Performance: Ingestion is useful for frequently processed data. Zero Copy depends on external query performance.
5. Cost: Compare ingestion and storage costs against Zero Copy query costs.
6. Security: Consider data governance, access permissions, and compliance.

My suggestion: Use a hybrid approach based on business requirements. Always validate performance, data freshness, and cost through a POC before finalizing.

Hi @Santhosh Gorantala

This is a common challenge when customer data comes from multiple systems.

I would normally start by checking the match rules and source data quality.

A few things I would suggest:

1. Match Rules: Check whether the rules are too strict. Sometimes small differences in names, emails, or phone numbers prevent matching.
2. Data Quality: Look for missing values, duplicate records, extra spaces, and inconsistent formats.
3. Normalization: Try normalized email and phone matching where applicable.
4. Data Mapping: Make sure Individual, Contact Point Email, and Contact Point Phone are mapped correctly, including their relationships.
5. Ruleset Execution: Check whether the Identity Resolution ruleset completed successfully and review the processing results.
6. Reconciliation Rules: If records are unified but the expected field values aren't showing, check which source is given priority.

Simple Example:

One system has "Santhosh Kumar" and another has "Santosh Kumar". An exact name match may fail, but fuzzy matching could help identify them as the same person. 

My suggestion is to take 2–3 customer records that should match, compare their source values, and test the matching rules step by step. 

One important point: Match rules decide which records get unified, while reconciliation rules decide which field values appear in the unified profile.

Hope this helps! 

Thank you, 

Venkat Yadav.

Hi @Santhosh Gorantala

Good question! I think the main thing is to include only the data that Agentforce actually needs, rather than bringing everything into one Data Graph. 

A few things I would consider:

1. Business Use Case: First, understand what questions the agent needs to answer and what data is required.
2. Relevant Data: Include only necessary objects and fields. Avoid adding unnecessary information.
3. Relationships: Keep relationships simple. Too many related objects can make things complex.
4. Data Volume: Be careful with large datasets and historical records.
5. Performance: Test how quickly Agentforce can retrieve the required information.

For example, if we're building a customer support agent, I would start with Account, Contact, recent Cases, and Orders instead of bringing in the entire customer history.

And yes, adding too many related objects or attributes can increase graph size and potentially impact performance. 

My suggestion would be to start small, test with real-world scenarios, and add more data only when it's actually needed. 

At the end of the day, Agentforce needs the right information at the right time, not every piece of data available. 

Hope this helps! 

Thank you, 

Venkat Yadav.

Hello @Antonio Bianco Ignacio

You can try the following options:

•  Clear the browser cache -> log out & log in again, then check the challenge
•  Check your challenge in incognito mode/Private Window or a different browser. 
•  If you still face the same error, delete and recreate it again, then try to check your challenge, or I recommend that you create a new playground and complete this task there.
•  https://trailhead.salesforce.com/trailblazer-community/feed/0D54S00000C4t16SAB
•  https://trailhead.salesforce.com/trailblazer-community/feed/0D54S00000JeMjKSAV