---
schema_version: "1"
id: 75eff83200bbd970f72ce128b06ce4f588f1099155e466840ed1a67c6d05239a
title: Unstructured Data Workflow
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/data/264-0-0/c360_a_unstructured_data_workflow.md
canonical_url: https://help.salesforce.com/s/articleView?id=data.c360_a_unstructured_data_workflow.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: 6e2b6940ea1d5686bb6acfe49ae2761f2cfc7b6feadbee1181a48ec436a9115e
description: Regardless of your use case for unstructured data, there's a general workflow to ingest and process it in Data 360.
products:
  - Data 360
release: "264"
---
# Unstructured Data Workflow

Regardless of your use case for unstructured data, there's a general workflow to ingest and process it in Data 360.

### Required Editions

<table class="slds-table slds-table_bordered slds-max-medium-table_stacked slds-m-bottom_small edition"><colgroup><col></colgroup><tbody><tr class=""><td class="slds-cell-wrap" style="vertical-align:top;">Available in: <strong>All Editions</strong> supported by Data 360. See <a href="https://help.salesforce.com/s/articleView?id=data.c360_a_dc_editions.htm&amp;language=en_US" target="_blank">Data 360 edition availability</a>.</td></tr></tbody></table>

<table class="slds-table slds-table_bordered slds-max-medium-table_stacked slds-m-bottom_small permission">
        <colgroup>
          <col style="width:50%">
          <col style="width:50%">
        </colgroup>
        <thead class="slds-text-title_caps ">
          <tr class="">
            <th scope="colgroup" class="slds-cell-wrap" colspan="2" style="text-align:left;vertical-align:top;" id="d206780e61">User Permissions
              Needed</th>
          </tr>
        </thead>
        <tbody>
          <tr class="">
            <td data-label="User Permissions Needed" class="slds-cell-wrap" style="vertical-align:top;" headers="d206780e61 ">To set up Data 360</td>

            <td class="slds-cell-wrap" style="vertical-align:top;" headers="d206780e61 ">
              <p>System admin profile OR </p>
              <p style="margin-bottom:0;">Data Cloud Architect</p>
            </td>

          </tr>
          <tr class="">
            <td data-label="User Permissions Needed" class="slds-cell-wrap" style="vertical-align:top;" headers="d206780e61 ">To ingest unstructured data and create search indexes</td>

            <td class="slds-cell-wrap" style="vertical-align:top;" headers="d206780e61 ">
              <p>One of these permission sets: </p><a name="c360_a_unstructured_data_workflow__ul_apx_qfx_q2c"><!-- --></a>
              <ul id="c360_a_unstructured_data_workflow__ul_apx_qfx_q2c">
                <li>Data Cloud Architect</li>

              </ul>
            </td>

          </tr>
        </tbody>
      </table>

#### See Also

- [Document AI](https://help.salesforce.com/s/articleView?id=data.c360_a_document_ai.htm&release=264.0.0&type=5 "Document AI in Data 360 uses large language models (LLMs) to extract structured data from unstructured documents such as invoices, resumes, lab reports, and purchase orders.")

## Step 1: Set up Data 360 In Your Org

Before you can connect unstructured data, verify that Data 360 is provisioned and enabled in your org.

See [Get Started with Data 360](https://help.salesforce.com/s/articleView?id=data.c360_a_product_considerations.htm&release=264.0.0&type=5 "Before you begin with Data 360, review the checklist, considerations, and product navigation.").

## Step 2: Ingest Unstructured Data

Depending on your use case, Data 360 has connectors purpose built for ingesting unstructured data from third-party applications or sources. You can also use the Salesforce CRM connector to ingest knowledge article data.

Some connectors, such as those for Amazon S3, Azure, or Google Cloud Storage, require file notification pipelines. Review the documentation for each connector.

Refer to the Unstructured Data Reference for more information.

## Step 3: Process Data

Use Document AI in Data 360 to read and import unstructured or semi-structured data from documents like invoices, resumes, lab reports, and purchase orders. Using AI, Data 360 extracts data from those documents into Data Lake Objects (DLO), which represent schemas for the extracted data. From this point, your data is available for search index processing and retrieval from automation flows or AI agent actions.

See [Document AI](https://help.salesforce.com/s/articleView?id=data.c360_a_document_ai.htm&type=5&language=en_US).

## Step 4: Create a Search Index

After setting up an unstructured data connection, you create a vector search index or a hybrid search index using either Data 360 defaults or the advanced builder. The search index helps validate that outputs are finely tuned to your users' intents and contexts.

See [Create a Vector Search Index with Advanced Setup](https://help.salesforce.com/s/articleView?id=data.c360_a_search_index_create_vector_index_config.htm&release=264.0.0&type=5 "When you create a vector search index configuration for a data model object, Data 360 breaks up the referenced data into semantically related chunks and generates searchable vectors. Your RAG and agent workflows use these vectors to find and return semantically similar items when they run queries. To get more granular control over your search index configuration, use the advanced setup, which guides you through each step of the process.") or [Create a Hybrid Search Index with Advanced Setup](https://help.salesforce.com/s/articleView?id=data.c360_a_hybridsearch_index_create.htm&release=264.0.0&type=5 "Configure a hybrid search index for a data model object (DMO) or an unstructured data model object (UDMO) to provide relevant information to generative AI applications. Data 360 breaks up the referenced data into semantically related chunks and generates searchable vectors, and then generates a vector index and a keyword index.").

## Step 5: Use Unstructured Data in a Workflow

Using unstructured data in Salesforce improves your AI agent, automation, and analytics workflows, improving customer experiences and operational efficiency. Based on your use case, consider these resources.

- Use Query API to [Run Vector Search Queries](https://help.salesforce.com/s/articleView?id=data.c360_a_search_index_query.htm&release=264.0.0&type=5 "Use the Query API to run vector searches in Data 360. Use these examples as starting points.") or to [Run Hybrid Search Queries](https://help.salesforce.com/s/articleView?id=data.c360_a_hybridsearch_index_query.htm&release=264.0.0&type=5 "Use Query API to run hybrid searches in Data 360. Use these examples as starting points.").
- Retrieval Augmented Generation (RAG) in Data 360 is a framework for grounding large language model (LLM) prompts. By augmenting prompts with accurate, current, and pertinent information, RAG improves the relevance and value of LLM responses for users. See [Using Retrieval Augmented Generation](https://help.salesforce.com/s/articleView?id=data.c360_a_rag_overview.htm&release=264.0.0&type=5 "Retrieval Augmented Generation (RAG) in Data 360 is a framework for grounding large language model (LLM) prompts. By augmenting the prompt with accurate, current, and pertinent information, RAG improves the relevance and value of LLM responses for users.").
- Bring the power of conversational AI to your business with Agentforce. Build intelligent, trusted, and customizable AI agents and empower your users to get more done with Salesforce. See [Agentforce Agents](https://help.salesforce.com/s/articleView?https://help.salesforce.com/s/articleView?id=ai.copilot_intro.htm&type=5id=ai.data_library_parent.htm&type=5&language=en_US).