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Salesforce Data Cloud
27Feb

Data Cloud March 2025 Release

Cross Cloud Updates for Data Cloud March 2025 Release Enhanced Marketing Cloud Integration Multi-Instance Event Routing Key Marketing Features: Expanded Data Sharing & Collaboration Real-Time Data Processing Event-Triggered Flows (Beta) Server-to-Server Connections Enterprise Tools Sandbox Migration External Data Connectivity Analytics & Security Key Details Feature Availability Editions Notes Multi-Instance Event Routing March 2025 Enterprise+ Action rules required 250-Object Data Shares March 2025 Enterprise+ AI/ML use cases Event-Triggered Flows March 2025 Enterprise+ Beta, add-on required This release delivers:✅ Precision marketing with cross-instance event routing✅ Scalable collaboration via expanded data sharing✅ Instant automation through real-time triggers Note: Beta features governed by Salesforce Beta Terms. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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February 27, 2025in Data, Enterprise, Google, Salesforce, Salesforce Data Cloud, Snowflake

Salesforce and AWS-Agentic Enterprise

Salesforce and AWS: Driving the Future of the Agentic Enterprise As AI-powered agents redefine the way businesses operate, strategic partnerships are playing a pivotal role in harnessing the power of data and artificial intelligence. Salesforce and AWS, two industry leaders, have taken significant steps toward building a smarter, agentic enterprise through their expanded collaboration. One year into this strategic partnership, their joint efforts are delivering transformative AI and data solutions, helping customers like Buyers Edge Platform unlock new efficiencies and capabilities. A Partnership Fueling Agentic AI Salesforce and AWS are aligning their AI and data initiatives to pave the way for advanced agentic systems—autonomous AI agents designed to enhance business operations and customer experiences. Among their notable achievements over the past year are: These innovations are creating an ecosystem that supports the delivery of agentic AI, enabling businesses to streamline operations and tap into new value from their data. “By integrating data and AI capabilities across our platforms, Salesforce and AWS are building a strong foundation for the future of agentic systems,” said Brian Landsman, EVP of Global Business Development and Technology Partnerships at Salesforce. “With a majority of large companies planning to implement agents by 2027, organizations need trusted partners to help them achieve their vision of a smarter enterprise.” Making AI More Accessible Salesforce is simplifying access to AI technology through the AWS Marketplace, offering customers an integrated solution that includes Agentforce—the agentic layer of the Salesforce platform. Agentforce enables businesses to deploy autonomous AI agents across various operations, streamlining workflows and delivering measurable results. Available in 23 countries, Salesforce’s presence on AWS Marketplace offers customers key advantages, including: By removing barriers to adoption, Salesforce and AWS empower companies to focus on leveraging technology for growth rather than navigating complex procurement systems. A New Era of Enterprise Efficiency As businesses increasingly rely on data and AI to remain competitive, the Salesforce-AWS partnership is setting the stage for enterprises to achieve more with agentic systems. These systems allow companies to execute complex tasks with unprecedented efficiency, maximizing ROI on technology investments. “Our partnership with Salesforce empowers mutual customers to realize the full potential of their data and AI investments,” said Chris Grusz, Managing Director of Technology Partnerships at AWS. “Together, we’re delivering immediate, actionable insights with agentic AI, enabling organizations to automate strategically and unlock more value across their operations.” Looking Ahead By seamlessly integrating data and AI capabilities, Salesforce and AWS are not just building technology solutions—they’re reshaping how enterprises operate and thrive in the digital age. As agentic AI becomes an essential part of business strategy, this partnership provides a blueprint for leveraging technology to drive smarter, more agile, and more effective enterprises. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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January 11, 2025in Artificial Intelligence, Data, Enterprise, Salesforce, Salesforce Data Cloud, Technology
Transform Customer Experiences
03Dec

Transform Customer Experiences

How to Transform Customer Experiences with AI and Sub-Second E2E Real-Time Data Sync Introducing Data Cloud’s Sub-Second E2E Real-Time FeatureDeliver hyper-personalized experiences in real time, no matter how or where customers engage with your brand. Exceptional customer experiences hinge on unifying interactions across every touchpoint. Yet, fragmented data dispersed across systems, channels, and clouds often stands in the way. Salesforce Data Cloud eliminates these silos by delivering a synchronized, real-time customer data ecosystem, enabling brands to create personalized, seamless experiences instantly—regardless of how or where customers connect. We’re excited to announce that the Sub-Second E2E Real-Time feature in Salesforce Data Cloud is now available. This innovation processes and analyzes data as it’s generated, empowering brands to make immediate, data-driven decisions. Combined with Einstein Personalization—which leverages advanced machine learning (ML) and rules-based automation—businesses can deliver individualized experiences across all channels, driving deeper engagement and improved outcomes. What is Sub-Second Real-Time? Sub-second real-time refers to the ability to process and deliver data or responses in less than one second, ensuring ultra-low latency and near-instantaneous results. This capability is critical for applications requiring immediate data updates, such as live analytics, responsive user interfaces, and time-sensitive decision-making. The Sub-Second E2E Real-Time feature empowers industries like fraud detection, predictive maintenance, and real-time marketing with instant insights. By synchronizing data across systems, channels, and clouds, Data Cloud ensures a unified, real-time customer view, giving businesses a competitive edge. Real-World Examples of Sub-Second Real-Time in Action 1. Real-Time Web Personalization Imagine a user browsing a website. As they interact with products, Data Cloud instantly captures this activity and updates their customer profile. Using Einstein Personalization, the system processes this data in milliseconds to tailor their browsing experience. For instance, personalized product recommendations can appear as the user clicks, leveraging insights from their behavior across platforms such as websites, point-of-sale systems, mobile apps, and other data sources. This seamless personalization is made possible by Data Cloud’s integrations, including zero-copy ingestion from major data warehouses like Snowflake, Databricks, and Redshift. The result? A continuously updated, 360-degree customer view that enhances every touchpoint. 2. Real-Time Support with Agentforce Now, consider a customer engaging in a live chat for assistance. As they browse, their actions are captured and updated in real time. When they initiate a chat, whether through Agentforce AI agents or human support, the agent has immediate access to their full activity history, updated within milliseconds. This enables the agent to provide tailored responses and solutions, ensuring a frictionless and engaging customer support experience. Why Sub-Second Real-Time Matters From personalization to support, the Sub-Second E2E Real-Time feature in Data Cloud ensures every customer interaction feels relevant, timely, and connected. By bridging the gap between data silos and intelligent automation, businesses can unlock new opportunities to exceed customer expectations—at scale and in real time. Explore how Salesforce Data Cloud can transform your customer experience today. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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December 3, 2024in Agentforce Platform, Data, Google, Salesforce, Salesforce Data Cloud, Snowflake
Salesforce Data Cloud and Zero Copy
28Sep

Salesforce Data Cloud and Zero Copy

As organizations across industries gather increasing amounts of data from diverse sources, they face the challenge of making that data actionable and deriving real-time insights. With Salesforce Data Cloud and zero copy architecture, organizations can streamline access to data and build dynamic, real-time dashboards that drive value while embedding contextual insights into everyday workflows. A session during Dreamforce 2024 with Joanna McNurlen, Principal Solution Engineer for Data Cloud at Salesforce, discussed how zero copy architecture facilitates the creation of dashboards and workflows that provide near-instant insights, enabling quick decision-making to enhance operational efficiency and competitive advantage. What is zero copy architecture?Traditionally, organizations had to replicate data from one system to another, such as copying CRM data into a data warehouse for analysis. This approach introduces latency, increases storage costs, and often results in inconsistencies between systems. Zero copy architecture eliminates the need for replication and provides a single source of truth for your data. It allows different systems to access data in its original location without duplication across platforms. Instead of using traditional extract, transform, and load (ETL) processes, systems like Salesforce Data Cloud can connect directly with external databases, such as Google Cloud BigQuery, Snowflake, Databricks, or Amazon Redshift, for real-time data access. Zero copy can also facilitate data sharing from within Salesforce to other systems. As Salesforce expands its zero copy partner network, opportunities to easily connect data from various sources will continue to grow. How does zero copy work?Zero copy employs virtual tables that act as blueprints for the data structure, enabling queries to be executed as if the data were local. Changes made in the data warehouse are instantly visible across all connected systems, ensuring users always work with the latest information. While developing dashboards, users can connect directly to the zero copy objects within Data Cloud to create visualizations and reports on top of them. Why is zero copy beneficial?Zero copy allows organizations to analyze data as it is generated, enabling faster responses, smarter decision-making, and enhanced customer experiences. This architecture reduces reliance on data transformation workflows and synchronizations within both Tableau and CRM Analytics, where organizations have historically encountered bottlenecks due to runtimes and platform limits. Various teams can benefit from the following capabilities: Unlocking real-time insights in Salesforce using zero copy architectureZero copy architecture and real-time data are transforming how organizations operate. By eliminating data duplication and providing real-time insights, the use of zero copy in Salesforce Data Cloud empowers organizations to work more efficiently, make informed decisions, and enhance customer experiences. Now is the perfect time to explore how Salesforce Data Cloud and zero copy can elevate your operations. Tectonic, a trusted Salesforce partner, can help you unlock the potential of your data and create new opportunities with the Salesforce platform. Connect with us today to get started. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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September 28, 2024in Data, Google, Salesforce, Salesforce Data Cloud, Snowflake
Agentforce - AI's New Role in Sales and Service
23Sep

Agentforce – AI’s New Role in Sales and Service

From Science Fiction to Reality: AI’s Game-Changing Role in Service and Sales AI for service and sales has reached a critical tipping point, driving rapid innovation. At Dreamforce in San Francisco, hosted by Salesforce we explored how Salesforce clients are leveraging CRM, Data Cloud, and AI to extract real business value from their Salesforce investments. In previous years, AI features branded under “Einstein” had been met with skepticism. These features, such as lead scoring, next-best-action suggestions for service agents, and cross-sell/upsell recommendations, often required substantial quality data in the CRM and knowledge base to be effective. However, customer data was frequently unreliable, with duplicate records and missing information, and the Salesforce knowledge base was underused. Building self-service capabilities with chatbots was also challenging, requiring accurate predictions of customer queries and well-structured decision trees. This year’s Dreamforce revealed a transformative shift. The advancements in AI, especially for customer service and sales, have become exceptionally powerful. Companies now need to take notice of Salesforce’s capabilities, which have expanded significantly. Agentforce – AI’s New Role in Sales and Service Some standout Salesforce features include: At Dreamforce, we participated in a workshop where they built an AI agent capable of responding to customer cases using product sheets and company knowledge within 90 minutes. This experience demonstrated how accessible AI solutions have become, no longer requiring developers or LLM experts to set up. The key challenge lies in mapping external data sources to a unified data model in Data Cloud, but once achieved, the potential for customer service and sales is immense. How AI and Data Integrate to Transform Service and Sales Businesses can harness the following integrated components to build a comprehensive solution: Real-World Success and AI Implementation OpenTable shared a successful example of building an AI agent for its app in just two months, using a small team of four. This was a marked improvement from the company’s previous chatbot projects, highlighting the efficiency of the latest AI tools. Most CEOs of large enterprises are exploring AI strategies, whether by developing their own LLMs or using pre-existing models. However, many of these efforts are siloed, and engineering costs are high, leading to clunky transitions between AI and human agents. Tectonic is well-positioned to help our clients quickly deploy AI-powered solutions that integrate seamlessly with their existing CRM and ERP systems. By leveraging AI agents to streamline customer interactions, enhance sales opportunities, and provide smooth handoffs to human agents, businesses can significantly improve customer experiences and drive growth. Tectonic is ready to help businesses achieve similar success with AI-driven innovation. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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September 23, 2024in Agentforce Platform, AI Tools, Data, Enterprise, Generative AI, Google, Marketing Automation, Salesforce, Salesforce Financial Services Solutions, Salesforce for Nonprofits, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Salesforce Implementation Services, Salesforce Manufacturing Automotive Energy, Salesforce Optimization, Salesforce Public Sector Solutions, Snowflake
Account Planning With Salesforce
25Sep

CRM Analytics Limits

When using CRM Analytics, keep these limits in mind. API Call Limits These limits apply to all supported editions. API Call Limit Maximum concurrent CRM Analytics API calls per org 100 Maximum CRM Analytics API calls per user per hour 10,000 Dataset Row Storage Allocations per License In Salesforce org, your total row storage limit for all registered datasets combined depends on your license combination. Each license allocates a different number of rows. Baseline Row Allocation Allocated Rows CRM Analytics Plus 10 billion CRM Analytics Growth 100 million Sales Analytics 25 million Service Analytics 25 million Event Monitoring Analytics 50 million B2B Marketing Analytics 25 million CRM Analytics for Financial Services Cloud 25 million CRM Analytics for Health Cloud 25 million Extra Data Rows license 100 million Your total row storage limit is a combination of your active licenses. For example: Because the CRM Analytics Plus license includes the Sales Analytics and Service Analytics licenses, your total row allocation remains 10 billion. Similarly, the CRM Analytics Growth license includes the Sales Analytics and the Service Analytics licenses, so your total row allocation remains 100 million. However, if you obtain another Sales Analytics or Services Analytics license, your row limit increases by 25 million for each added license. Dataset Row Limits Each dataset supports up to 2 billion rows. If your Salesforce org has less than 2 billion allocated rows, each dataset supports up to your org’s allocated rows. Dataset Field Limits Value Limit Maximum number of fields in a dataset 5,000 (including up to 1,000 date fields) Maximum number of decimal places for each value in a numeric field in a dataset (overflow limit) 17 decimal placesWhen a value exceeds the maximum number of decimal places, it overflows. Both 100,000,000,000,000,000 and 10,000,000,000,000,000.0 overflow because they use more than 17 decimal places. A number also overflows if it’s greater (or less) than the maximum (or minimum) supported value. 36,028,797,018,963,968 overflows because its value is greater than 36,028,797,018,963,967. -36,028,797,018,963,968 overflows because it’s less than -36,028,797,018,963,967.When a number overflows, the resulting behavior in CRM Analytics is unpredictable. Sometimes CRM Analytics throws an error. Sometimes it replaces a numeric value with a null value. And sometimes mathematical calculations, such as sums or averages, return incorrect results. Occasionally, CRM Analytics handles numbers up to 19 digits without overflowing because they are within the maximum value for a 64-bit signed integer (263 – 1). But numbers of these lengths aren’t guaranteed to process.As a best practice, stick with numbers that are 17 decimal places or fewer. If numbers that would overflow are necessary, setting lower precision and scale on the dataset containing the large numbers sometimes prevents overflow. If your org hasn’t enabled the handling of numeric values, the maximum number of decimal places for each value in a numeric field in a dataset is 16. All orgs created after Spring ’17 have Null Measure Handling enabled. Maximum value for each numeric field in a dataset, including decimal places 36,028,797,018,963,967For example, if three decimal places are used, the maximum value is 36,028,797,018,963.967 Minimum value for each numeric field in a dataset, including decimal places -36,028,797,018,963,968For example, if five decimal places are used, the minimum value is -36,028,797,018,9.63968 Maximum number of characters in a field 32,000 Data Sync Limits If you extract more than 100 objects in your dataflows, contact Salesforce Customer Support before you enable data sync. Value Limit Maximum number of concurrent data sync runs 3 Maximum number of objects that can be enabled for data sync, including local and remote objects 100 Maximum amount of time each data sync job can run for local objects 24 hours Maximum amount of time each data sync job can run for remote objects 12 hours Data sync limits for each job:Marketo Connector (Beta)NetSuite ConnectorZendesk Connector Up to 100,000 rows or 500 MB per object, whichever limit is reached first Data sync limits for each job:Amazon Athena ConnectorAWS RDS Oracle ConnectorDatabricks ConnectorGoogle Analytics ConnectorGoogle Analytics Core Reporting V4 ConnectorOracle Eloqua ConnectorSAP HANA Cloud ConnectorSAP HANA Connector Up to 10 million rows or 5 GB per object, whichever limit is reached first Data sync limits for each job*:AWS RDS Aurora MySQL ConnectorAWS RDS Aurora PostgresSQL ConnectorAWS RDS MariaDB ConnectorAWS RDS MySQL ConnectorAWS RDS PostgreSQL ConnectorAWS RDS SQL Server ConnectorGoogle Cloud Spanner ConnectorMicrosoft Azure Synapse Analytics ConnectorMicrosoft Dynamics CRM ConnectorSalesforce External ConnectorSalesforce Contacts Connector for Marketing Cloud EngagementSalesforce OAuth 2.0 Connector for Marketing Cloud Engagement Up to 20 million rows or 10 GB per object, whichever limit is reached first Data sync limits for each job*:Amazon Redshift ConnectorAmazon S3 ConnectorCustomer 360 Global Profile Data Connector (Beta)Google BigQuery for Legacy SQL ConnectorGoogle BigQuery Standard SQL ConnectorHeroku Postgres ConnectorMicrosoft Azure SQL Database ConnectorSnowflake Input Connector Up to 100 million rows or 50 GB per object, whichever limit is reached first *When using these connectors, Salesforce Government Cloud org data is protected in transit with advanced encryption and can sync up to 10 million rows or 5 GB for each connected object, whichever limit is reached first. Note When using a Salesforce local input connection, CRM Analytics bulk API usage doesn’t count towards Salesforce bulk API limits. Use of the external Salesforce connection and output connection impacts your limits. The dataflow submits a separate bulk API call to extract data from each Salesforce object. The dataflow uses a batch size of 100,000–250,000, depending on whether the dataflow or the bulk API chunks the data. As a result, to extract 1 million rows from an object, the dataflow creates 4–10 batches. Recipe and Dataflow Limits Important In Winter ‘24, recipe runs over 2 minutes are counted against the limit. Previously, the recipe run counts weren’t correct. For more information, see Known Issue – Recipe runs are not counting towards the daily maximum run limit. Value Limit Maximum amount of time each recipe or dataflow can run 48 hours Maximum number of recipes 1,000 Maximum number of dataflows definitions (with data sync enabled) 100 Maximum number of dataflow and recipe runs in a rolling

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September 25, 2023in Data, Google, Google Analytics, Salesforce, Salesforce Government Cloud, Snowflake
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