Data Cloud

Connectors

- Marketing Cloud Email Studio - MobileConnect - MobilePush - Marketing Cloud Data Extensions - SF CRM - Marketing Cloud Personalization - Common Cloud Storage Providers - Commerce Cloud

When does it make sense to use an existing data org?

- The customer has a single line of business. - Customer data is housed in a single Salesforce org. - Primary use cases require OOTB Data Cloud LWCs and search capabilities for service agents.

When does it make sense to use a new home org?

-Multiple Salesforce customer orgs exist. Highly complex enterprise architecture exists. -The Data Cloud administration users are different from the Salesforce admin users. -The existing data org is highly customized.

What can CPD do?

1, Acquire Data: Ingest customer-level data from many sources. 2, Process Data: Clean and Dedupe the data 3. Store: Persistent Data Storage 4. Analytics and decisions: predict and personalize

Prep for Data Cloud

1. Indenify Project Stakeholders 2. Identify Data Source and Integrations 3. Identify Users 4. Document All business requirments 5. Understand System Requirements.

Data Cloud Actions

1. Ingest your raw data: 2. Clean and transform you data 3., Map and model your data 4. Indentify and unify your customer info 5. Select your channels 6. Segment and Activicate your audiences 7. Do your marketing magic 8. Measure your sucess

Configure User Permission for an external SF org conneciton in Data Cloudn

1. Must login into the external SF org that you want to connect to DC 2. Create a new permission set 3.Make sure Session Activation Required is unchecked for the permission. To disable session activation on an existing permission set, select the permission set and click edit properties. Assign the following System and User Permissions.A user must have these system permissions: API EnabledConnect Org to Data CloudCustomize ApplicationManage Custom Permissions View Roles and Role HierarchyView Setup and Configuration A user must have these user permissions: Assign Permission Sets Manage Profiles and Permission Sets Add Assignments and assign this permission set to the user who's connecting your external CRM org to Data Cloud.

Match Rules

1. Select an object: From either: individual contact points (email, app, phone and address) 2. Select your field: Select attributes available based on the object selected 3. Selecting match methods

Typically SF CRM Connector Example 1

1:1

Typically SF CRM Connector Example 2

1:M

Use cases for integratiuon with Google Analytics 360 web engagement data

A Data Cloud segment of any customers who have browsed running shoes on the website in the past seven days but have not yet purchased anything. You may want to activate that audience for personalized omni-channel messaging to influence their behavior to complete the online purchase. A Data Cloud segment of customers who have browsed hiking gear more than three times in the past X days in the San Francisco area. You can target that segment with an in-store promotion for hiking gear to drive them to convert in-store.

Data Model Object (DMO)

A data model object is a grouping of data (made of attributes) that are created from data streams, insights and other sources. DMOs can be standard or can be custom, based on business need. Common stanard DMOs include sales ordrs, party indentification, email engagement and so on. Orgs that do no thave data that fits into a standard model, DC allows to create a model that meets their exact needs. For Data Cloud, mapping your source data to Data Model Objects (DMOs) is a critical step in establishing a standardized way of understanding data that originates from different systems but still references similar types of information, and it's a critical component for being able to identify a unified individual. Schema-enforced Parquet-formatted Iceberg Tables Hydrated by transformations Typed-profile versus engagement

Data Stream

A data source brought in Data Cloud, for example, a Marketing Cloud customer data extension. These data streams can be based on batched data or real-time data streams

Identity Matching

A key component of identity resolution the concept of matching. When tis comes to methods used to identify an individual. Data cloud uses both deterministic (exact) matching such as a matching email address or probabilistic (fuzzy) matching, which uses machiine learning and statistics to identify similar records with a high degree of probability of being matched.

Tableau integration

A native integration with Tableau enriches business intelligence for driving deeper insights using the unified profile. Developers can also take advantage of JavaScript tools for accessing the profile data Java Database Connectivitty (JDBC)

Field

A place where you store a value, like a name or address; using our spreadsheet example, a field would be a column on the spreadsheet.

App

A set of fields, object permissions and functionality to support a busineess process.

Object

A table in the database; in that spreadhseet example, object is a tab on the spreadsheet

Householding

Ability to group together individuals that likely belong to members of the same household, family or other groups like an organization. This is done by analyzing data such as addresses, phone numbers, and other identifying information to identify patterns and relationships that suggest multiple identities belong to the same group.

Streaming insights

Aggreations are not only for bulk data . Real-time data streams can be calculated and aggregated to launch powerful actions to personalized every moment.

Indiviudal object

All data streams with customer information need to have a field mapped to the individual ID field from the individual object in order to use identity resolution.

Contact Point Objects

All have associated objject that can be used for identify resoluion. This information represents specific information about a person that may change or be different in various systems.

Attribute

Also called a field, is a specific piece of data found in a DMO, for example, a customer's first name. This is a similar to data extension field in Marketing CLoud.

Which connection can a Data Aware Specialist setup to ingest data from without needing the Admin to explicitly setup the connection?

Amazon S3

Record

An item you are tracking in your database, if your data is a like a spreadsheet, then a record is a row on the spreadsheet.

Data provisioning

Analytst have made it clear that the single most differentiated feature of such a platform is its ability to provision data embedded with intelligence, create harmonized data packages provisioned for specific endpoints, and design for specifc business personas.

Data Explorer and Profile explorer

Are data vieing tools allowing a view into ingested data and unified profiles.

Create a package in Data Cloud

As an admin, you can package and install your Data Cloud Amazon S3 data streams for distribution. A package is a container for Salesforce Metadata Component that can be either individual configurations or an entire custom Salesforce platform app. After the package is created, you can distribute it to other Salesforce users and orgs via an install link or AppExchange.

Ingestion Patterns

Batch - CRM Connector, Marketing Cloud can ingest and updates data hourly so would follow batch pattern. bullet Near Real-Time - Ingestion API processes small micro-batches of records every 15 minutes so could be considered near real-time. bullet Real-Time - Web & Mobile Connector can process engagement data every 2 minutes so would be a real-time ingestion pattern.

Data Ingestion

Bring in all fields from a data set exactly as they are without modification. hat way, you can always revert back to the original shape of the data should you make a mistake or change business requirements during setup. You can also extend the data set by creating additional formula fields for the purpose of cleaning nomenclature or performing row-based calculations. Each data set is going to be represented by a data stream in Data Cloud.

Data Ingestion

Bring in all fields from a data set exactly as they are without modification. That way, you can always revert back to the orginal shape of the data or change bussiness requirments during setup. You can also extend the set by creating addtional formula fields for the purpose of cleaning or preforming row-based calculations.. Each data set is going to be represented by a data stream in Data Cloud.

Salesforce CRM Connector

CRM org types: Home org: This is the org where it's installed. If the customer is using this org for Sales Cloud or Service Cloud or Loyalty Management, they may use the connector to ingest CRM data from within the Home org. bullet External orgs: These CRM orgs are external to the org where it's installed. Customers may connect to any production external orgs, including other orgs where it may be installed. bullet Sandbox orgs: These are sandbox CRM orgs that are external to the org where it's installed. Customers may connect to any sandbox external orgs.

Which of the following reflects the correct order of the Data Cloud Setup process flow?

Configure Admin user, provision and complete Data Cloud setup, configure additional users & permissions, and connect to relevant Salesforce Clouds

What does "unify" mean as a capability of Data Cloud?

Connect, match, and resolve customer data

Data Streams

Connected Data sources added into your data cloud

What must the Admin user do first when setting up users in Data Cloud?

Create profiles for each user role

Which permission set is required to setup an External Activation Platform?

Customer Data Platform Admin

What 2 scenarios would you recommend when provisioning Data Cloud in an existing CRM Data Org?

Customer data is housed in a single Salesforce Org and Customer is using Loyalty Management and Promotions

Calculated Insights

Data Cloud is capable of performing complex aggregations on unifed data through click-based tools or using SQL.

Marketing Cloud Personalization Connector

Data Cloud provides starter data bundles that give you predefined data sets for email and mobile (including Einstein Engagement data). Because these are all known system tables, these bundles take you all the way from importing the data set as-is to introducing it automatically to the data model layer. Which means within a few clicks, you are ready to get to work on your business use cases. The behavioral, engagement-oriented data sets retrieved by these connectors are refreshed hourly; the profile data sets are refreshed daily. You can also access custom data sets via Marketing Cloud Data Extensions. For example, you can use this connector to ingest ecommerce or survey data that you've already imported into Marketing Cloud. Simply provision your Marketing Cloud instance in Data Cloud after which point you'll see the list of Data Extensions that can be brought in. Depending on how you choose to export your data extension from Marketing Cloud—Full Refresh or New/Updated Data Only—the data will be retrieved by the connector daily for the former option or hourly for the latter option. Keep in mind that unlike the starter data bundles, which both import the data and model the data for you, with this connector you must complete the modeling step yourself, since the data set is custom.

Which tab in the navigation manages the data coming into Data Cloud?

Data Steams

Data Lakehouse Formual

Data Warehouse + Data Lake = Data Lakehouse Data Lake: Vast Pool of raw data, the purpose for which is not yet defined. Data Warehouse: is repository for structured, filtered data that has already been processed for a specific purpose.

Normalized Data

Data is divided into multiple tables, with established relationships to reduce redundancy and inconsistency.

When using the GCS Connector, how frequently is data from Google Cloud Storage synchronized with Data Cloud?

Every 1 hour

Match Methods

Exact: Matching based on an exact match Fuzzy: Matching based on a similar match. Normalized: Matching base don the same exact infor, regardless of formatting. Such as email, phone, and address. The more rules configured the more mapping requirments you need to follow.

Type Converisions

For example: ABS(), MD5(), NUMBER(), PARSEDATE()

Date calculations

For example: DATE(), DATEDIFF(), DAYPRECISION()

Text Manipulation

For example: EXTRACT(), FIND(), LEFT(), SUBSTITUTE()

Logical expression

For example: IF(), AND(), OR(), NOT()

Refresh History Tab

Good resource to validate the data is being retrived at the expected cadence and without error.

Data Ethics

If a customer has not opted in to use their data, do not ingest into Data Cloud Ensure that customers recieve clear benefits in exchange for their data.

Ingestion API

If you want to customize how you connect to other data sources, you can use the Ingestion API to create a connector, upload your schema, and create data streams into your org. These streams can update incrementally or in bulk, depending on how you configure your API requests.

New Google Connector Configuration

Ingest data using google buckets: Land and ingest the flat file data using Google Cloud storage. define google buckets in set-up: register buckets in setup simplify stream definition and managment (credentials for all related data streams can be easily managed from a single location) Google Cloud Storage: Limit and refresh schedules - 5 GCS connections per org are supported - Data and files from GCS buckets are kept in sync hourly with Data Cloud Infastructure

Subject Area

Is a business concept or term used to group similar data objects to aid in data modeling for example, sales orders, loyality or engagement data.

Customer Data Platform (CPD)

Is a place where a company collect and stores data about its customers.

Identity Reconciliation

Is another key component, when two or more identities are matched identity reconciliation dictates the rules by which duplicate attributes ar chosen to represent that unified individual. Data cloud allows you to customize these rules to make sure you're referencing the right attrib utes about each individual.

Individual Object

Is the most important because it has all the personal information you know about your customer.

Unified customer profile

Is the product of Identity resoluation. Its a complete and consisten view of customer or entity that combines data from multiple source.

Basic Data

It is personal information about a subscriber like full name. This data can be unique or nonunique to specific individual, for example a subscriber zip code or shared email address. Know basic data is specific information that biusinesses store in the customer relationship managment (CRM) platform, like phone numbers and email addresses. Pseudonymous basic data would be the IP address associated with the email address when a custom logs into thir account

Reconciliation List of Rules

Last Updated This rule specifies that the most recently updated value must be selected for inclusion in the unified individual profile. It's worth considering what data gets updated most regularly—would it be customer service data or perhaps Marketing Cloud preference data? Most Frequent This rule specifies that the most frequently occurring value must be selected for inclusion in the unified individual profile. Source Sequence This rule allows you to sort your data sources in order of most to least preferred for inclusion. Basically it allows you to select based on your confidence in the data source. As an example, you can specify that the system use Marketing Cloud data first and S3 data last.

Typically SF CRM Connector Example 3

M:1

Data Modeling

Map the data streams to the data modle in order to create a harmonized view across sources.

Behavorial Data

Marketers begin attributing characteristics to a customer, getting to know them better. This happens over time, as they gather more and more basic and interaction data.

Which Permission Set manages the overall segmentation strategy and identifies the target campaigns?

Marketing manager

Salesforce CRM Data

Once you authenticate your Sales and Service Cloud instance you can choose one object per data stream to connect to you Data Clound account, either by selecting form a list of available object or searching. The data is refreshed hourl,y and once a week there's also a full refresh of the data.

Datorama Integration

Reference the data cloud unifed data model in datorama to accelarate time to value in building anaytical and predicitive models for marketing and advertizing campaigns

Customer Data Platform Data Aware Specialist: Permission Set

Responsible for creating data streams, mapping data to the data model, creating indentity resolution rulesets for unitifed profiles, and for creating calculated insights.

Customer Data Platform Marketing Specialist: Permission set

Responsible for creating segments in Customer Data Platform.

Customer Data Platform Marketing Manager: Permission Set

Responsible for the overall segmentation strategy, including creating activation targets, activations, and 'Customer Data Platform Marketing Specialist' permission.

Customer Data Platform Admin: Permission Set

Resposible for the setup of application, user provisioning and assigning permission sets within the system. This role has access to SF Sales Cloud and Service Cloud, in addition to other integrated system within the core cloud platform. The admins executes day to day configuration, support maintences, and improvement and perform regular internal system audits.

Pre-built Connectors

Salesforce Clouds, such as CRM, Marketing Cloud, B2C Commerce, and Marketing Cloud Personalization. bullet External sources, such as external file storage (Google Cloud Storage, Amazon S3). bullet API and mobile connectors, such as Ingestion API, Web, and Mobile SDK.

Org

Short your organization the place where all your data configuration and customization lives.

Google Cloud Connector: Implementation Steps

Step 1: Create a Connection Step 2: Create a Data Stream Step 3: Monitor

Subject Area (A Business Goal)

Subject areas or data models according to business goals.

What does "connect" mean as a capbility?

Synchronize data from external data sources and transform data when needed.

Amazon S3 Connector

The Amazon S3 connector lets you ingest data from S3 buckets as well as activate data to S3.The process for setting up S3 connections is different than other connectors. Rather than having an administrator configure the connector within Data Cloud's setup, Amazon S3 connections for data ingestion are configured individually at the data stream level. This means that a single Data Cloud account can connect to multiple S3 buckets if needed. This also means that S3 connections can be made by any user with access to create a Data Source, such as a Data Aware Specialist. Additionally, it means that connection information must be provided each time a new Data Stream is created.

MuleSoft

The MuleSoft Anypoint platform contains dozens of pre-configured connectors for common platforms to easily and quickly transfer data from systems outside of Salesforce into Data Cloud. Consume or activate data to any cloud and any application. Build a trust-based, first-party data asset. Provide transparency and security for data gathered from individuals who provide consent for its use and receive value in exchange.

APIs

The Streaming API (Appliarion Program Interface) can be used to send real-time event information to Data Cloud, such as engagement information from your website or mobile application. It uses a fire-and-forget pattern to synchronize micro-batches of updates between the source system and Data Cloud in near-real time. Data is processed asynchronously approximately every 15 minutes. For systems without a pre-built connector, the Bulk API provides a way for data to be prepared in large batches of up to 150Mb at a time by external platforms and sent to Data Cloud for ingestion.

Interationaction Data

The actions people take and how they interact with each other and brands. Do they click on a link? Known interaction data results from the actions they take from a known data point, like their email inbox. Anonymous interaction data comes when its not possible to tell who took the action, like clickiing a wbepage link where the visitor hasn't logged in.

Identify you account functional domain

The functional domain refers to the Salesforce's public cloud infrastructure where your instance is located. This information is helpful to provide when troubleshooting any potential issues with support. (Similar to knowing your MID in Marketing Cloud). From Data Cloud Setup, click Setup Home.

The Customer 360 Data Model

The standard Data Cloud model that helps with the interoperability of data across applications. The Customer 360 Data Model reduces the complexities of integratng data across cloud applications by providing standarized data interoperabillity guidliness. It can be adopted and extendedto create data lakes, generate analytics, train machine learning models, build a single view of the customer, and more. The Customer 360 Data Model is organized into subject areas that represent a major business concept, like customer information, product, or engagement data.

Web and Mobile Connector

This connector captures online data form websites and mobible apps. Data Cloud offers canonical data mappings for both web and mobile instances to facilitate ingestion, which you can then query and activate across both moible and email.

B2C Commerce Connector

This connector ingests data from a B2C Commerce instance and creates a B2C Commerce data stream.

Cloud Storage Connector

This options creates data stream from data stored on the Amazon Web Services S3. The connect accommodates custom data sets and you have the option to retrive data hourly, daily, weekly or monthly. As with custom data sets, the connector completes the import step and you subsequently map the data into the model.

Data Source Configuation in Data Cloud

To connect data sources, review the admin tasks that must be completed first. Set Up an Azure Storage Service ConnectionAfter you create your Data Cloud instance, you can set up an Azure Storage Service Connection. Set Up a B2C Commerce ConnectionAfter you create your Data Cloud instance, you can set up a B2C Commerce Connection. Then you can control the scope of data ingestion from B2C Commerce. The B2C Commerce connector only supports connections to production instances of B2C Commerce. Set Up an External Activation PlatformReach more customers by connecting an external activation platform to Data Cloud. Install an external activation platform from AppExchange or a packaged URL. Set Up a Google Cloud Storage ConnectionAfter you create your Data Cloud instance, you can set up a Google Cloud Storage (GCS) Connection. Set Up Ingestion API ConnectorAs an admin in Data Cloud, set up an Ingestion API connector source to bring in data from external sources. Set Up a Connection to Marketing Cloud PersonalizationAfter you create your Data Cloud instance, connect to Marketing Cloud Personalization (formerly Interaction Studio) to enrich customer profiles with user profile data and events. Set Up Marketing Cloud Connection in Data CloudAfter you create your Data Cloud instance, you can control the scope of data ingestion and activation from Marketing Cloud and other sources. Before integrating Marketing Cloud with Data Cloud, make sure that your Marketing Cloud user's default business unit (BU) is set to the Enterprise ID (EID). You also can set up your data sources to tell Data Cloud where to pull data, also known as ingest, from for data mapping and segments. Data Cloud only supports Marketing Cloud Enterprise 2.0 account connections. Set Up the Salesforce CRM ConnectionSet up a connection between Data Cloud and a Salesforce CRM org to control the scope of data ingestion, data action targets, and activation from Salesforce CRM. To connect Data Cloud to Salesforce CRM, your Salesforce org must have API access. Set Up the Salesforce Interactions SDKTo set up the Salesforce Interaction SDK in Data Cloud, the Customer Data Cloud admin, the developer, and the data aware specialist all work together. The Custome

Relationships between standard objects are automatically defined when the key field that is shared between the objects is mapped in both places.

True

Special Considerations

Understand the primary key (the value that uniquely identifies a row of data) of each data set. Identify any foreign keys in the data set. These ancillary keys in the source may link to the primary key of a different data set. (For example, the sales order details data set contains a product ID that corresponds to the item purchased. This product ID links to a whole separate table with more details about that product, such as color or size. The instance of product ID on the sales order details data set is the foreign key, and the instance of product ID on the product data set is the primary key.) Determine if the data is immutable (not subject to change once a record is sent) or if the data set needs to accommodate updates to existing records. Determine if there are any transformations you would like to apply to the data. (For example, you can use simple formulas to clean up names or perform row-based calculations.) Review the attributes, or fields, coming from each data source. If the same field is tracked across multiple sources, decide which data source is most trusted. You can set an ordered preference of sources later on. Make sure you have the authentication details handy to access each data set. Take note of how often the data gets updated.

Fully Qualified Keys (FQK)

Use Fully Qualified Keys (FQK) to avoid key conflicts when data from different sources are ingested and harmonized in the Data Cloud data model. Each data stream is ingested into Data Cloud with its specific keys and attributes. When multiple data streams are harmonized into a single data model object (DMO), the various keys can conflict and records can have the same key values. Fully qualified keys avoid conflicts by adding key qualifier fields and interpreting the data accurately. A fully qualified key consists of a source key, such as a contact ID from CRM or a subscriber key from Salesforce Marketing Cloud, and a key qualifier.

Data Cloud Admin

Users with this permission set can access all functionality within Data Cloud, including mapping data to the data model and creating data streams, identity resolution rulesets, and calculated insights. To manage and assign users in Setup and access Data Cloud Setup, you must be a Data Cloud Admin and have a Salesforce administrator role that grants access to Salesforce Setup. If you have access to Salesforce Setup, you can set up the application, and access Salesforce Sales and Service clouds and other integrated Salesforce systems.

Data Cloud User

Users with this permission set can view Data Cloud features.

Cross-Device Indentity Managment

Your customers have a complex digital footprint that comes from multiple types of identities created from their interaction with various advertisements, social media platforms, and devices. Data Cloud keeps track of all these identities, and when it has enough information to match these identities together, it adds that information to that individual's Unified Profile.

Google Cloud Storage Connector

an online file-based storage web service on Google Cloud Platform infrastructure. Data Cloud reads from your GCS bucket and periodically performs an automated data transfer of active objects to a Data Cloud-owned staging environment for data consumption. Once an admin configures the connection, it can then be used by other users (data-aware specialists or marketing managers) to ingest or activate the data (without needing to know the GCS credentials).

Calculated insights

are predifned and calculated metrics that can help markertes build segments.

Reconciliation Rules

determine the logic for data selection. For example, if the same email address is available from two data sources, a reconciliation rule helps the unified individual profile know which one to display

Attitudinal or preferential data

gets to the heart of the customer, identifying how they feel and what they believe about certain things, such as how often they want to recieve communications. The best ways to gather attiudinal behavior is to ask customers direcrtly or purchase the information from another party.

Foreign key

is a common link found between data source that builds data relationships-for example a customer ID numebr

Known Data

is information definitively tied to a specific person or family account. It's like an unique subscriber ID such as driver's license, a person's email address, or a family's phone number used when a customer sets up an account

Pseudonymous data

isn't quite so straightforward. It can't be tied to a known person, so there's some guessing involved. If a person visits a website and browses information about beaches then they log in, the business can assume that they might be interested in booking a beach vacation.

Identiy reolutions

where your team creates match and reconcilaition rules to unify indiviudal records