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Exam Number : Salesforce-CDP
Exam Name : Salesforce Customer Data Platform (CDP)
Vendor Name : Salesforce
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Salesforce-CDP Exam Format | Salesforce-CDP Course Contents | Salesforce-CDP Course Outline | Salesforce-CDP Exam Syllabus | Salesforce-CDP Exam Objectives

Exam Specification:

- Exam Name: Salesforce Customer Data Platform (CDP)
- Exam Code: Salesforce-CDP
- Exam Duration: 90 minutes
- Exam Format: Multiple-choice and multiple-select questions

Course Outline:

1. Introduction to Salesforce Customer Data Platform (CDP)
- Understanding the role and benefits of a Customer Data Platform
- Overview of Salesforce CDP and its key features
- Exploring use cases and business scenarios for CDP implementation

2. CDP Architecture and Data Model
- Understanding the architecture and components of Salesforce CDP
- Exploring the data model and data sources in CDP
- Designing and configuring data ingestion and transformation processes

3. Data Governance and Privacy in CDP
- Implementing data governance practices in CDP
- Ensuring data privacy and compliance with regulatory requirements
- Managing consent and preferences for customer data

4. Segmentation and Audience Management
- Creating and managing customer segments in CDP
- Defining target audiences and customer personas
- Personalizing customer experiences based on segmentation

5. Customer Journey Orchestration
- Designing and automating customer journeys in CDP
- Mapping customer touchpoints and interactions
- Implementing journey analytics and optimization

6. Data Analytics and Insights
- Analyzing customer data and generating insights
- Implementing data visualization and reporting capabilities
- Utilizing machine learning and AI for data analysis

7. Integration and Data Exchange
- Integrating CDP with other Salesforce products and third-party systems
- Implementing data synchronization and data exchange processes
- Designing and configuring API integrations for data flow

8. CDP Implementation and Deployment
- Planning and executing CDP implementation projects
- Managing data migration and data quality processes
- Ensuring system scalability and performance

Exam Objectives:

1. Understand the role and benefits of a Customer Data Platform.
2. Design and configure the architecture and data model in Salesforce CDP.
3. Implement data governance and ensure data privacy in CDP.
4. Create and manage customer segments for targeted marketing efforts.
5. Design and automate customer journeys in CDP.
6. Analyze customer data and generate insights using CDP.
7. Integrate CDP with other systems and implement data exchange processes.
8. Plan and execute CDP implementation projects.

Exam Syllabus:

The exam syllabus covers the following topics (but is not limited to):

- Introduction to Salesforce CDP
- CDP architecture and data model
- Data governance and privacy in CDP
- Segmentation and audience management
- Customer journey orchestration
- Data analytics and insights
- Integration and data exchange
- CDP implementation and deployment

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Salesforce’s Einstein Copilot AI Will Soon Analyze Unstructured Data

Salesforce announced expanded capabilities of its generative AI assistant Einstein Copilot, enhanced integrations with Apple offerings and more today at the Salesforce World Tour New York 2023 event. The addition of the Data Cloud Vector Database to the Salesforce Data Cloud will allow both the Salesforce Data Cloud and Einstein Copilot to handle unstructured data.

Salesforce announced several other enhancements to its business software, particularly within Data Cloud for Advertisers. These products could be useful for a wide variety of teams, including IT, sales, customer service, marketing and commerce.

Jump to:

AI enhancements to Salesforce Data Cloud Einstein Copilot

A major enhancement to Salesforce Data Cloud is Data Cloud Vector Database, coming in a pilot program in February 2024. Data Cloud Vector Database is integrated vector database support that allows for the use of a wide variety of data types. Unstructured data — e.g., PDFs, email, audio and social media content — will be combined with structured data — e.g., purchase history, customer support cases and product inventory.

More must-read AI coverage

Einstein Copilot, Salesforce’s generative AI assistant, will be able to use unstructured data to respond to questions or perform analysis; it will access this data through Salesforce Data Cloud. Einstein Copilot will be generally available in February 2024.

“This transforms every piece of data — from emails to social media posts to audio — into actionable insights using AI, CRM, automation, AI, Einstein Copilot, and analytics,” said Rahul Auradkar, executive vice president and general manager of Unified Data Services and Einstein at Salesforce, in a press release.

Possible use cases of Einstein Copilot include:

  • Customer service: Einstein Copilot’s unstructured data will be able to be used for customer service. The example Salesforce gave is of a chatbot pulling answers from articles for a customer visiting a self-service page.
  • IT teams: Einstein Copilot can be used to help IT teams uncover problems in unstructured content produced in machine operations, such as logs, sensor readings or image and audio records.
  • Sales reps: Einstein Copilot can help sales reps get more information about a potential client company before meeting with that company’s representatives.
  • Einstein Copilot Search

    Another enhancement for Salesforce Data Cloud will be Einstein Copilot Search, which will be in pilot in February 2024. Einstein Copilot Search draws from data across Data Cloud to provide smart suggestions for searches. It will be useful for problem-solving tasks performed by sales, customer service, marketing, commerce and IT teams. For example, Einstein Copilot search will be able to link a customer’s emails and phone calls to their formal support ticket history to assist a customer service representative.

    Expanded Salesforce and Apple partnership

    Apple Messaging, Apple Pay and augmented reality will be accessible directly in certain Salesforce products. Salesforce and Apple have had a strategic partnership since 2018.

    Specifically, Apple Messages for Business in Service Cloud, generally available today with Salesforce’s Service Cloud Digital Engagement, will let businesses set up live chat experiences with customers for customer service, product recommendations, tracking shipments or setting up appointments. Customers can pay for services and products with Apple Pay within the Messenger app.

    Augmented reality with Apple’s ARKit will be available within the Salesforce Field Service mobile app in the summer of 2024. With it, field technicians can capture 3D renderings of real locations to make planning and installations easier.

    The Salesforce Field Service iOS widget will be available for iPhones in the summer of 2024. It provides a quick view of key account information in Salesforce Field Service.

    AWS partnership and more Salesforce news

    At Salesforce World Tour New York 2023, Salesforce’s AWS partnership was highlighted and other news was announced.

    Details about Salesforce’s partnership with AWS

    Salesforce reiterated the company’s partnership with AWS announced in November 2023, in which Salesforce expanded its use of AWS in multiple ways:

  • Salesforce began offering products on AWS Marketplace.
  • Some Einstein Studio Copilot capabilities will be able to be integrated with Amazon SageMaker and Amazon Bedrock.
  • Amazon Connect Chat came to Salesforce’s Service Cloud Digital Engagement.
  • Amazon Connect forecasting was added to Salesforce Service Cloud Omnichannel.
  • Salesforce’s app builder Heroku will receive powerful new capabilities from AWS services that allow it to become a factory for generative AI-first apps.
  • News about Trailblazer Career Marketplace, Unlimited Edition+, Data Cloud for Advertisers

    Salesforce opened a new jobs site for careers within the Salesforce ecosystem called Trailblazer Career Marketplace, which is open today to Salesforce partners.

    Salesforce announced Unlimited Edition+, a package of Salesforce technologies for companies interested in getting into generative AI, data and CRM. UE+ is now in general availability.

    New integrations are coming to Data Cloud for Advertisers. Data Cloud for Advertisers will be able to connect to Google Display & Video 360 for personalized ads across channels. Data Cloud for Advertisers will be able to connect to LinkedIn, letting advertisers target specific groups of professionals using Marketing Cloud, Sales Cloud and Service Cloud product usage data from their own apps and LinkedIn.

    Note: TechRepublic is covering the Salesforce World Tour New York 2023 event virtually.

    Salesforce announces updated unstructured data capabilities for its AI and CRM platform

    Salesforce Inc. today announced major updates to its Data Cloud, part of the company’s Einstein 1 Platform, which will allow companies to ingest unstructured data such as PDFs, emails, audio and social media content and connect them with artificial intelligence-powered experiences.

    All of these improvements are aimed at greatly improving Einstein Copilot, Salesforce’s generative AI assistant, currently in beta mode, so it can use an organization’s structured and unstructured data.

    Data Cloud acts as a pool of a company’s metadata-enabled objects in one place, allowing all the information that an enterprise has to be accessed by services and products, including Einstein Copilot, using a hyperscale engine. This reduces the amount of data fragmentation across enterprise data stacks between cloud, social and mobile and provides access to information all in one place. Now that Data Cloud has access to unstructured data as well as structured data, enterprise customers have reach that they didn’t before.

    That matters because real-time relevant data is crucial for producing compelling customer experience and driving accurate AI answers and insightful analysis for customer relationship management systems. However, most information about what’s happening in the real world is tied up in unstructured formats, Rahul Auradkar, executive vice president and general manager of unified data services and Einstein, told SiliconANGLE in an interview.

    “Even though data is essentially the foundation for having accurate and effective engagement through CRM and AI, 90% of enterprise data is unstructured data,” said Auradkar. “And this could be emails, it could be PDFs, it could be notes that you wrote to yourself, audio transcripts, video, transcripts, social media posts. But it can’t be effectively used.”

    This new capability is made possible with a new vector database support that enhances Salesforce’s ability to handle diverse data types. Now both structured and unstructured data are automatically converted into formats across the Einstein 1 Platform through Data Cloud that can be used for analysis, greater comprehension, insights and more.

    “In the past, there was no there were no mature large language models — now they have mature LLMs,” said Auradkar. “So they can take that unstructured data that refers to all the knowledge articles and all the interactions and send it to the LLM. I can now reason over data that is both structured and unstructured — and ask questions of it that has meaning behind it, where before I needed to carefully structure my queries.”

    As a result of making these data types available in Data Cloud, and further to Copilot, AI agents can be built that understand what’s happening from knowledge sources better than ever before. For example, a self-service Einstein Copilot-powered chatbot for customers could pull relevant details out of unstructured sources to answer questions by using information from audio and articles linked to customer data that wasn’t available before.

    Marketers could take advantage of unstructured data from survey data to build better campaigns and then use that to have an AI assistant iterate their email mailer templates to better target their audiences. Preparing for sales meetings could be done more swiftly by having the Copilot listen to the audio or read unstructured data from a customer’s 10-K or past email interactions.

    Even information technology and operations teams would benefit greatly from unstructured data fed through Data Cloud, such as machine logs, sensor readings, images and audio recordings, the company says. Using Tableau, Salesforce’s interactive data visualization tool, the data could be analyzed and Einstein Copilot could provide insights into anomalies and statistical variances in the data points, using semantic similarity that would help engineers discover problems with software or equipment.

    Image: Salesforce Your vote of support is important to us and it helps us keep the content FREE. One click below supports their mission to provide free, deep, and relevant content.   Join their community on YouTube Join the community that includes more than 15,000 #CubeAlumni experts, including CEO Andy Jassy, Dell Technologies founder and CEO Michael Dell, Intel CEO Pat Gelsinger, and many more luminaries and experts.

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    Unstructured data comes to Salesforce Data Cloud - here's why it matters

    Parker Harris

    The Data Cloud has rightly been one of Salesforce’s biggest product focuses this year. As the company’s World Tour series of events hit New York yesterday, the latest news was that it will soon be able to handle unstructured data via the Data Cloud Vector Database. 

    This provides integrated vector database support that means that unstructured data, such as emails, audio, social content etc, can be combined with structured data, such as purchase histories or product inventories. 

    As per the official announcement, a use case exemplar might be: 

    For example, customer service leaders will enhance efficiency and customer satisfaction by utilizing a platform that proactively presents relevant knowledge articles to service agents the moment a case is created. This allows for quick identification of similar cases and the integration of automation, thereby reducing case resolution time and improving the overall customer experience.

    The Einstein Copilot generative AI assistant will also be able to tap into unstructured data. Also announced in New York was Einstein Copilot Search, which will use structured and unstructured data from the Data Cloud to provide suggestions for searches. As a use case exemplar, Salesforce pitches that it would be able to link a customer’s emails and phone calls to their formal support ticket history to assist a customer service representative.

    Data, data everywhere

    According to stats from Forrester Research, some 90% of enterprise data exists in unstructured form, rendering it inaccessible for business applications and AI models. The research firm also predicts that the volume of such unstructured data will double next year. 

    Getting on top of the data problem is crucial, said Salesforce co-founder and Chief Technology Officer Parker Harris:

    Your data is disconnected. Your APIs are disconnected. You've got a bunch of different apps, they're not connected. You've got vendors who don't work with each other that aren't connected. You've got low productivity. That is not what you want. That's not the AI experience that you want.

    The Salesforce solution to this is the Einstein 1 platform, first announced back in September at Dreamforce in San Francisco. Harris explained: 

    It’s integrated. It's one platform. You might think of [Salesforce] as multiple platforms. We've done a lot of acquisitions over the world. One of my main focuses is to make sure they bring all that together, that it's integrated into one platform, that it's AI-first, it's automated, that it's low code, no code all the way to pro code. It's everything. And that it is completely open.  

    So whether you're using Sales or Service or Marketing or Commerce, whatever application you're using, or you build applications on their platform, it's all powered by metadata. You've got the Data Cloud, not as some separate data cloud, not off to the side where you're like, ‘I got all my data here, come and get it’. No, your data is there.

    You need that data to hand, he went on: 

    You want that data to be there to power your CRM interactions, to personalize that marketing email, personalize that customer service interaction so that agent know who he or she is talking to. And you want the AI to be right there too, not off to the side, not [have to] switch over to some other AI interface. The AI needs to have that data. You want the AI to do some things for you, to make you more productive, to maybe write that email response to a customer or summarize the customer support issue. All of that working together, but powered by metadata. 

    All this matters because the AI revolution is a data revolution, argued Patrick Stokes, Salesforce SVP of Product Management: 

    You cannot have great AI without great data. They have islands of disconnected data. They have data all over the place. They have it in in their CRM, they might have it in their ERP, we've got it in all sorts of different places. But we've also got all sorts of different types of data. We've got something that they would call structured data, which is data that you would typically find in a database or a spreadsheet, but we've also got something called unstructured data. Unstructured data is things like PDFs, knowledge articles, chat scripts, transcripts, social media content, audio recordings - this is all unstructured data. They want to get access to that data. We'd like to have that data to provide context for their AI. 

    Data Cloud now works with unstructured data. Now you can connect all of your unstructured data to Data Cloud and they use a vector database to effectively index all of that data and make it available for automation, for search and ultimately for Einstein copilot.

    Data Cloud Vector Database and Einstein Copilot Search will both be in pilot in February next year, just as Einstein Copilot enters general availability. 

    My take

    An important addition to the Data Cloud story that clearly resonated with the Salesforce audience at Dreamforce in September. 


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