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AI Causes Job Flux
10Oct

AI Causes Job Flux

AI Barometer Signals Job Disruption Amid Global Productivity Gains A recent PwC report highlights significant productivity improvements worldwide, but also points to potential job disruption due to artificial intelligence (AI). Described as the “Industrial Revolution of knowledge work,” AI is transforming how workers utilize information, generate content, and deliver results at unprecedented speed and scale. The 2024 AI Jobs Barometer, released by PwC, aims to provide empirical data on the impact of AI on global employment. AI Causes Job Flux but not necessarly job loss. AI Causes Job Flux The analysis involved examining over half a billion job ads across 15 advanced economies, including the U.S., Canada, Singapore, Australia, New Zealand, and several European nations. PwC sought to uncover the effects of AI on jobs, skills, wages, and productivity by monitoring the rise of positions requiring specialist AI skills across various industries and regions. The findings show that AI adoption is accelerating, with workers proficient in AI commanding substantial wage premiums. Broader Workforce Impact Interestingly, the impact of AI extends beyond workers with specialized AI skills. According to PwC, the majority of workers leveraging AI tools do not require such expertise. In many cases, a small number of AI specialists design tools that are then used by thousands of customer service agents, analysts, or legal professionals—none of whom possess advanced AI knowledge. This trend is driven largely by generative AI applications, which can typically be operated using simple, everyday language without technical skills. AI’s Economic Promise AI is leading a productivity revolution. Labor productivity growth has stagnated in many OECD countries over the past two decades, but AI may offer a solution. To better understand its effect on productivity, PwC analyzed jobs based on their “AI exposure,” indicating the extent to which AI can assist with tasks within specific roles. The report found that industries with higher AI exposure are experiencing much greater labor productivity growth. Knowledge-based jobs, in particular, show the highest AI exposure and the greatest demand for workers with advanced AI skills. Sectors such as financial services, professional services, and information and communications are leading the way, with AI-related job shares 2.8x, 3x, and 5x higher, respectively, than other industries. Overall, these sectors are witnessing nearly fivefold productivity growth due to AI integration. AI is also playing a role in alleviating labor shortages. Jobs in customer service, administration, and IT, among others, are still growing but at a slower rate. AI-driven productivity may help fill gaps caused by shrinking working-age populations in advanced economies. Wage Premiums for AI Skills Workers in AI-specialist roles are seeing significant wage premiums—up to 25% on average. Since 2016, demand for these roles has outpaced the growth of the overall job market. The highest wage premiums are found in the U.S. (25%) and the U.K. (14%), with data specialists commanding premiums of over 50% in both countries. Financial analysts, lawyers, and marketing managers also enjoy substantial wage boosts. The Disruption of Job Markets The skills required for AI-exposed jobs are evolving rapidly. PwC’s report reveals that new skills are emerging 25% faster in AI-exposed occupations compared to those less affected by AI. Jobs requiring AI proficiency have grown 3.5 times faster than other roles since 2016, and this trend predates the rise of popular tools like ChatGPT. However, while AI is driving demand for new skills, it is also reducing the need for certain old ones. Jobs in fields like IT, design, sales, and data analysis are seeing slower growth, as tasks in these areas are increasingly automated by AI technologies. The Future of Work The PwC report stresses that AI will not necessarily result in fewer jobs overall, but will change the nature of work. Instead of asking whether AI can replicate existing tasks, the focus should be on how AI enables new opportunities and industries. Tectonic recommends you work on this trail of thought by implementing AI Acceptable Use Policies in your company. Encourage your teams to explore AI tools that increase productivity but clearly outline what is and is not acceptable AI usage. PwC outlines several steps for policymakers, business leaders, and workers to take to ensure a positive transition into the AI era. Policymakers are encouraged to promote AI adoption through supportive policies, digital infrastructure, and workforce development. Business leaders should embrace AI as a complement to human workers, focusing on generating new ways to create value. Meanwhile, workers must build AI-complementary skills and experiment with AI tools to remain competitive in the evolving job market. Ultimately, while AI is disrupting the job landscape, it also presents vast opportunities for those who are willing to adapt. Like past technological revolutions, those who embrace change stand to benefit the most from AI’s transformative power. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 10, 2024in AI Tools, Artificial Intelligence, Data, Generative AI, Salesforce
Fivetrans Hybrid Deployment
10Oct

Fivetrans Hybrid Deployment

Fivetran’s Hybrid Deployment: A Breakthrough in Data Engineering In the data engineering world, balancing efficiency with security has long been a challenge. Fivetran aims to shift this dynamic with its Hybrid Deployment solution, designed to seamlessly move data across any environment while maintaining control and flexibility. Fivetrans Hybrid Deployment. The Hybrid Advantage: Flexibility Meets Control Fivetran’s Hybrid Deployment offers a new approach for enterprises, particularly those handling sensitive data or operating in regulated sectors. Often, these businesses struggle to adopt data-driven practices due to security concerns. Hybrid Deployment changes this by enabling the secure movement of data across cloud and on-premises environments, giving businesses full control over their data while maintaining the agility of the cloud. As George Fraser, Fivetran’s CEO, notes, “Businesses no longer have to choose between managed automation and data control. They can now securely move data from all their critical sources—like Salesforce, Workday, Oracle, SAP—into a data warehouse or data lake, while keeping that data under their own control.” How it Works: A Secure, Streamlined Approach Fivetran’s Hybrid Deployment relies on a lightweight local agent to move data securely within a customer’s environment, while the Fivetran platform handles the management and monitoring. This separation of control and data planes ensures that sensitive information stays within the customer’s secure perimeter. Vinay Kumar Katta, a managing delivery architect at Capgemini, highlights the flexibility this provides, enabling businesses to design pipelines without sacrificing security. Beyond Security: Additional Benefits Hybrid Deployment’s benefits go beyond just security. It also offers: Early adopters are already seeing its value. Troy Fokken, chief architect at phData, praises how it “streamlines data pipeline processes,” especially for customers in regulated industries. AI Agent Architectures: Defining the Future of Autonomous Systems In the rapidly evolving world of AI, a new framework is emerging—AI agents designed to act autonomously, adapt dynamically, and explore digital environments. These AI agents are built on core architectural principles, bringing the next generation of autonomy to AI-driven tasks. What Are AI Agents? AI agents are systems designed to autonomously or semi-autonomously perform tasks, leveraging tools to achieve objectives. For instance, these agents may use APIs, perform web searches, or interact with digital environments. At their core, AI agents use Large Language Models (LLMs) and Foundation Models (FMs) to break down complex tasks, similar to human reasoning. Large Action Models (LAMs) Just as LLMs transformed natural language processing, Large Action Models (LAMs) are revolutionizing how AI agents interact with environments. These models excel at function calling—turning natural language into structured, executable actions, enabling AI agents to perform real-world tasks like scheduling or triggering API calls. Salesforce AI Research, for instance, has open-sourced several LAMs designed to facilitate meaningful actions. LAMs bridge the gap between unstructured inputs and structured outputs, making AI agents more effective in complex environments. Model Orchestration and Small Language Models (SLMs) Model orchestration complements LAMs by utilizing smaller, specialized models (SLMs) for niche tasks. Instead of relying on resource-heavy models, AI agents can call upon these smaller models for specific functions—such as summarizing data or executing commands—creating a more efficient system. SLMs, combined with techniques like Retrieval-Augmented Generation (RAG), allow smaller models to perform comparably to their larger counterparts, enhancing their ability to handle knowledge-intensive tasks. Vision-Enabled Language Models for Digital Exploration AI agents are becoming even more capable with vision-enabled language models, allowing them to interact with digital environments. Projects like Apple’s Ferret-UI and WebVoyager exemplify this, where agents can navigate user interfaces, recognize elements via OCR, and explore websites autonomously. Function Calling: Structured, Actionable Outputs A fundamental shift is happening with function calling in AI agents, moving from unstructured text to structured, actionable outputs. This allows AI agents to interact with systems more efficiently, triggering specific actions like booking meetings or executing API calls. The Role of Tools and Human-in-the-Loop AI agents rely on tools—algorithms, scripts, or even humans-in-the-loop—to perform tasks and guide actions. This approach is particularly valuable in high-stakes industries like healthcare and finance, where precision is crucial. The Future of AI Agents With the advent of Large Action Models, model orchestration, and function calling, AI agents are becoming powerful problem solvers. These agents are evolving to explore, learn, and act within digital ecosystems, bringing us closer to a future where AI mimics human problem-solving processes. As AI agents become more sophisticated, they will redefine how we approach digital tasks and interactions. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 10, 2024in Data, Enterprise, Salesforce
Marketing Cloud Website Activity Collection
09Oct

Marketing Cloud Website Activity Collection

Leveraging Website Activity Data in Salesforce Marketing Cloud Understanding how users interact with your website is essential for delivering personalized customer experiences. Salesforce Marketing Cloud (SFMC) offers robust tools to capture website activity and transform this data into actionable insights, enhancing your marketing strategies. This guide walks you through the process of collecting website activity data in SFMC. Marketing Cloud Website Activity Collection Before diving into the setup process, it’s important to understand the benefits of collecting website activity data: Now, let’s explore how to set up website activity tracking in Salesforce Marketing Cloud. Set Up Marketing Cloud Website Activity Collection Step 1: Install Salesforce Marketing Cloud Tracking Code To begin collecting website activity, install the Salesforce Marketing Cloud tracking code on your website. Known as the “Web Collect” code, this script captures visitor behavior data and sends it to SFMC. Step 2: Configure Data Extensions After installing the tracking code, set up data extensions in SFMC to store the website activity data you collect. Step 3: Set Up Behavioral Triggers To maximize the value of your data, set up behavioral triggers in SFMC. These triggers can automatically send personalized communications based on specific website actions. Step 4: Leverage Advertising Studio for Retargeting To further enhance your marketing efforts, use Advertising Studio to create retargeting campaigns based on website activity data. Step 5: Monitor and Optimize After setting up website activity tracking, regularly monitor the performance of your campaigns and the quality of your collected data. Final Thoughts Collecting website activity data in Salesforce Marketing Cloud enables you to understand customer behavior better and deliver more personalized experiences. By following these steps—installing the tracking code, configuring data extensions, setting up behavioral triggers, and leveraging retargeting—you can effectively harness website activity data to elevate your marketing efforts. Start implementing these strategies today to unlock the full potential of Salesforce Marketing Cloud and drive deeper engagement and conversions. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 9, 2024in Analytics Builder, Data, Google, Salesforce, Salesforce Marketing Cloud
Smartsheet and AWS Collaborate
09Oct

Smartsheet and AWS Collaborate

Smartsheet and AWS Collaborate to Enhance AI-Driven Decision-Making with New Amazon Q Business Connector October 8, 2024 — During its annual ENGAGE customer conference, Smartsheet (NYSE: SMAR), the enterprise work management platform, announced a partnership with AWS to introduce a new connector that integrates Smartsheet data with Amazon Q Business. This generative AI-powered assistant can answer questions, provide summaries, generate content, and securely complete tasks using data from customers’ enterprise systems. This integration will allow Amazon Q Business users to access insights about their projects and processes managed in Smartsheet, facilitating a cohesive search experience that empowers employees to make informed, data-driven decisions. Smartsheet and AWS Collaborate. As organizations increasingly recognize the importance of data-driven decisions, data silos remain a major hurdle. Research from Salesforce in 2024 indicates that only about 28% of business applications are interconnected. The new connector aims to address this issue by securely merging Smartsheet data with other sources integrated into Amazon Q Business, such as Salesforce, Slack, Microsoft Teams, and AWS. This will benefit over 13 million Smartsheet users globally, including around 85% of the 2024 Fortune 500 companies, allowing them to access their work management data, including sheets, conversations, and files, through AWS’s generative AI-powered assistant. This integration enhances decision-making, productivity, and efficiency. Smartsheet and AWS Collaborate “The Smartsheet connector furthers our strategy to securely integrate Smartsheet with leading enterprise AI tools, allowing customers to work seamlessly across their business applications,” said Ben Canning, SVP of Product Experiences at Smartsheet. “By combining our flexible data model with Amazon Q Business, we’re unlocking access to work management data for our mutual customers, enabling them to focus on achieving business outcomes without worrying about data storage.” For instance, service operations managers can utilize the new connector to manage complex projects more effectively. By posing specific questions to the Amazon Q Business assistant, teams can gain insights from various data sources, including sheets, conversations, and attachments in Smartsheet. The AI assistant conducts thorough searches while respecting access permissions, saving time and enhancing project oversight. This streamlined approach improves client retention, accuracy, and overall service quality. “Generative AI presents a unique opportunity for organizations to transform their internal workflows. The key is securely accessing their own data, regardless of its location or format,” stated Dilip Kumar, Vice President of Amazon Q Business at AWS. “Many enterprises use Smartsheet as their primary collaboration hub, storing billions of rows of data. Allowing Amazon Q Business users to interact with their Smartsheet data in a simple, secure manner boosts productivity, analysis, and decision-making.” “Generative AI is driving a significant shift in how enterprise knowledge is stored, accessed, and utilized,” noted Dion Hinchcliffe, VP of the CIO Practice at The Futurum Group. “This transition offers a chance to redefine what’s possible in data management. A strategic, informed approach to adopting this technology is crucial. By integrating work management data into Amazon Q Business, Smartsheet and AWS are creating a unified AI search experience across their knowledge base, unlocking the true potential of their data.” Empowering Teams to Achieve More with Generative AI Smartsheet is collaborating with industry leaders like AWS to develop AI capabilities that help enterprises manage their critical tasks more strategically and efficiently. Earlier this year, Smartsheet implemented Amazon Q Business internally to enhance knowledge management and boost employee productivity in the cloud. The Smartsheet connector exemplifies how both organizations are delivering powerful AI tools that revolutionize team workflows. Smartsheet continues to integrate generative AI throughout its platform, designed with practicality, transparency, and customer needs in mind. Smartsheet’s AI tools enable organizations to swiftly extract insights from data, create automated processes, generate text and summaries, and accomplish more with the AI assistant. Through the end of December, Smartsheet is offering its entire suite of AI tools to all customers, allowing everyone to leverage AI’s capabilities within the platform. The Smartsheet connector is currently available to Amazon Q Business customers in public preview. About Smartsheet Smartsheet is a modern enterprise work management platform trusted by millions globally, including approximately 85% of the 2024 Fortune 500 companies. As a pioneering leader in its category, Smartsheet delivers powerful solutions that drive performance and foster innovation. Visit www.smartsheet.com for more information. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 9, 2024in AI Tools, Data, Enterprise, Generative AI, Salesforce, Technology
Marketing Cloud and Commerce Cloud Innovations
09Oct

Marketing Cloud and Commerce Cloud Innovations

What Our Dreamforce Marketing Cloud and Commerce Cloud Innovations Mean for You This year’s Dreamforce was nothing short of amazing. It was exciting to reconnect with fellow Trailblazers, exchange brilliant ideas, and showcase the innovations we’ve been crafting at Salesforce. A recurring theme throughout the event was how businesses can leverage data and AI to forge deeper customer-driven relationships by bringing internal teams closer together. These innovations are designed to transform not only how companies engage with customers but also how their teams work together. Marketing Cloud and Commerce Cloud Innovations. Seamless integration between Marketing, Commerce, Sales, and Service teams is crucial for creating unified customer experiences. Often, customers feel as though they are interacting with separate departments rather than one cohesive company—this is largely due to disconnected technology and processes. But thanks to Salesforce’s advancements in unified data, AI, and automation, those days are numbered. Now, departments can collaborate more effectively, delivering hyper-personalized, frictionless experiences across the entire customer lifecycle. Let’s explore the latest Marketing Cloud and Commerce Cloud innovations announced at Dreamforce 2024 and how they can benefit your business. What You’ll Learn Salesforce Marketing Cloud Innovations These four innovations in Marketing Cloud are built on the Salesforce Platform and powered by Data Cloud, offering marketers a seamless view of customer data across the business. This foundation makes it easier to deliver unified customer experiences, improve handoffs between teams, and measure success more effectively. 1. Agentforce Embedded in Marketing Workflows Agentforce for Marketing combines generative and predictive AI to create an end-to-end campaign experience that marketers can launch and optimize with ease. Here’s how it helps: Example: A marketer looking to prevent customer churn can launch a re-engagement campaign. Agentforce will identify the right audience, craft personalized messages, and optimize delivery based on customer behavior. 2. Empowering Small and Medium Businesses The new Marketing Cloud Advanced Edition brings enhanced AI and automation capabilities to SMBs, enabling them to scale personalization and improve productivity: 3. Automating Data Preparation and Analytics with Einstein Marketing Intelligence (EMI) EMI uses AI and Data Cloud to automate the ingestion, transformation, and analysis of marketing data: 4. Einstein Personalization for 1:1 Experiences Einstein Personalization uses AI to recommend products, content, or services based on individual customer preferences: Example: A service agent could offer a discount on a product a customer was recently viewing, creating a seamless, personalized experience. Salesforce Commerce Cloud Innovations As businesses scale and handle increasing amounts of data, managing complex commerce systems can be a challenge. The new Commerce Cloud updates simplify these complexities by extending unified commerce capabilities across the organization. 1. Simplifying Cross-Functional Commerce Tasks By unifying data from across the business, Commerce Cloud enables better cross-functional collaboration: 2. AI-Powered Commerce Agents with Agentforce Commerce Cloud introduces three AI-powered agents to streamline business processes: 3. Streamlining Checkout for a Faster, Easier Experience With new express payment options like Link by Stripe and Amazon Pay, Commerce Cloud Checkout speeds up transactions and improves conversion rates by 14%. Plus, Buy with Prime integration allows shoppers to use their Amazon Prime accounts for a faster checkout experience, complete with trusted delivery and hassle-free returns. The Future of Unified Commerce Salesforce Commerce Cloud offers a unified platform that brings together sales, service, and marketing, providing a 360-degree view of the entire customer journey. This unified commerce approach enables businesses to deliver seamless B2B and B2C experiences, all powered by a single platform. By integrating enterprise-wide data, trusted AI, and automated workflows, Salesforce helps businesses scale personalized, intelligent experiences across every touchpoint. Every interaction becomes an opportunity for growth, setting the standard for success in today’s customer-driven world. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 9, 2024in Data, Enterprise, Salesforce, Salesforce Commerce Cloud, Salesforce Marketing Cloud, Technology
Slack Fuels Productivity
08Oct

Set Up Salesforce and Slack Integration

Set Up Salesforce and Slack Integration for Sales Elevate and Salesforce Channels To use Sales Elevate or Salesforce channels in Slack, establish a connection between Salesforce and Slack. This setup allows your team members to access these features seamlessly. You can map Salesforce accounts to corresponding Slack accounts to ensure the right individuals access the right tools. Note: You must have Salesforce Admin permissions to complete the setup in Salesforce. Prepare Your Salesforce Org Before connecting Salesforce and Slack, complete the following steps in Salesforce: Step 1: Create and Configure a Salesforce Integration User An Integration User ensures proper permissions and prevents disconnection if your personal Salesforce account is deactivated or updated. Step 2: Allow the Integration User to Bypass SSO If your organization uses single sign-on (SSO), you’ll need to bypass it for the Integration User to complete authentication. Step 3: Assign Permissions to the Integration User Grant the Integration User access to Salesforce objects and fields used in Slack. Connect Slack to Salesforce With your Integration User ready, connect your Salesforce org to Slack. You can connect up to 25 Salesforce orgs to Slack. Step 1: Request a Connection in Slack Step 2: Approve the Connection in Salesforce Step 3: Activate the Connection in Slack Manually Map Member Accounts If you opt out of automatic mapping, you can manually map accounts: Remove Member Mapping Salesforce Admins can remove and reset member mappings: Assign Access to Salesforce Tools in Slack Manage access to Sales Elevate and Salesforce channels by assigning the Slack Elevate User permission set in Salesforce: This configuration streamlines collaboration, giving your team access to powerful Salesforce tools directly in Slack. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 8, 2024in Salesforce
Veeam Latest Acquisition
08Oct

Veeam Latest Acquisition

Veeam continues its acquisition strategy with the purchase of Alcion, bolstering its capabilities in AI and as-a-service offerings. This acquisition follows Veeam’s investment in Microsoft 365 backup-as-a-service provider Alcion last year, and brings in a team of AI and security specialists. Analysts and Veeam executives see this move as a key step in expanding Veeam’s as-a-service offerings. Earlier this year, the company launched Veeam Data Cloud, a backup-as-a-service solution for Microsoft 365 and Azure workloads. “After years of resisting, Veeam has fully embraced the as-a-service model,” said Christophe Bertrand, an analyst at TheCube Research. Veeam Latest Acquisition The acquisition, which closed in mid-September, marks the second time Veeam has purchased a company founded by Niraj Tolia and Vaibhav Kamra. In 2020, Veeam acquired Kasten, their Kubernetes backup provider. A year ago, Veeam led a million funding round for Alcion, which has since developed AI-driven data protection solutions. Veeam has been active in acquisitions, joining a broader trend in the data protection market. Recently, Commvault acquired Clumio, Cohesity merged with Veritas, and Veeam itself bought Cirrus from CT4, which later became part of the Veeam Data Cloud. Earlier this year, Veeam also acquired Coveware, an incident response vendor. “Veeam hasn’t traditionally been an acquisition-heavy company, but that has changed in recent years,” said Rick Vanover, Veeam’s VP of product strategy. “I expect this trend to continue.” Alcion’s Role at Veeam This acquisition strengthens Veeam’s expertise in the fast-growing as-a-service market. Alcion’s team of fewer than 50 employees, including founders Niraj Tolia and Vaibhav Kamra, joins Veeam, with Tolia stepping in as Veeam’s new CTO. Tolia will lead product strategy and engineering for Veeam Data Cloud, succeeding Danny Allan, who recently became CTO at cybersecurity company Snyk. Alcion, which has hundreds of customers, will offer those customers the opportunity to transition to Veeam Data Cloud. However, Veeam has not finalized the future of Alcion’s product or established a timeline for its integration. “This acquisition brings incredible talent and thought leadership to Veeam, especially from Niraj and the Alcion team,” said Brandt Urban, Veeam’s senior VP of worldwide cloud sales. “Their expertise will help us rapidly enhance Veeam Data Cloud, adding more capabilities and expanding workload coverage.” Analysts, like Bertrand, expect Veeam to broaden its data protection offerings for additional SaaS platforms beyond Microsoft 365, looking toward collaboration and DevOps tools as potential areas for growth. AI and Security at the Forefront Alcion’s AI-powered features allow administrators to optimize backups, detect malware, and respond proactively to threats. According to Krista Case, an analyst at The Futurum Group, Alcion uses AI strategically to adapt backup schedules based on data modification patterns, trigger backups when potential threats are identified, and recommend the best recovery points. “When practitioners talk about cyber resilience, they’re focused on minimizing data loss and downtime—Alcion’s AI capabilities directly address these concerns,” said Case. Veeam has also been integrating AI into its existing products, offering inline malware detection and an Intelligent Diagnostics service. A forthcoming Copilot feature for Microsoft 365 backups will further enhance AI-driven data protection. Veeam Latest Acquisition “AI is a real asset when applied thoughtfully—it’s not just hype,” said Bertrand, adding that users are more interested in AI’s ability to drive outcomes, like detecting threats that could otherwise go unnoticed. Veeam executives echoed the importance of delivering clear, tangible AI benefits. “We keep user outcomes front and center because, otherwise, AI becomes an expensive experiment,” Vanover said. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 8, 2024in Data
dbt Labs and Salesforce
08Oct

dbt Labs and Salesforce

dbt Labs, a leader in analytics engineering, announced at Coalesce 2024 a groundbreaking partnership with Salesforce to integrate Salesforce Data Cloud’s AI, automation, and analytics capabilities with dbt Labs’ expertise in data transformation and metrics management. This collaboration aims to deliver a seamless, trustworthy, and comprehensive data experience for users. “Together, Salesforce and dbt Labs are redefining what’s possible with data,” said Ryan Segar, Chief Customer Officer at dbt Labs. “By integrating our solutions, we’re helping customers accelerate their analytics development journey, delivering powerful, flexible data insights that drive better business outcomes.” The partnership offers Salesforce Data Cloud, Tableau, and Agentforce users access to dbt Labs’ robust data transformation pipeline, ensuring high data accuracy, quality, and reliability. An independent metrics layer from dbt Labs will allow Salesforce and Tableau users to define, manage, and standardize key business metrics, providing consistent and comparable insights across platforms. This supports confident, data-driven decision-making directly within the flow of work. New integrations include the ability to connect dbt Semantic Layer with Tableau Pulse, export metrics from dbt Cloud to Tableau Cloud, and leverage dbt models within Tableau and Einstein. Future integrations will explore features such as alignment with Tableau Semantics and enabling instant Tableau analytics from the dbt Cloud console. Ali Tore, Senior Vice President of Advanced Analytics at Salesforce, emphasized the benefits of this collaboration: “By combining the strengths of dbt with Salesforce Data Cloud, we’re empowering customers with AI-powered insights built on a foundation of trusted, reliable data. This integration unlocks the full potential of their data to drive impactful business outcomes.” With over 50,000 teams already using dbt, Salesforce customers can now leverage advanced data modeling techniques trusted by leading global organizations. This partnership offers scalable, robust data modeling directly within Salesforce Data Cloud, benefiting both technical and non-technical users alike. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 8, 2024in Data, Salesforce, Salesforce Data Cloud
Data Cloud Model
08Oct

Data Cloud Model

While many Salesforce products like Sales Cloud, Service Cloud, Education Cloud, Health Cloud, and various industry clouds are built on a common ‘core’ platform that shares the same datastore (an Oracle relational database), Salesforce Data Cloud operates on (Data Cloud Model) a distinct architecture and technology stack. This insight explores the data models and related concepts that underpin the platform. Data Cloud Architecture and Storage Starting with the storage layer, Salesforce Data Cloud integrates multiple services: This combination enables Data Cloud to provide a petabyte-scale data store, overcoming the scalability and performance constraints of traditional relational databases. The physical architecture of Data Cloud is represented as a set of data objects, which form the foundation for how data is ingested, harmonized, and activated within the platform. Key Data Cloud Objects Data Source A Data Source is the initial data layer in Data Cloud, representing an external platform or system from which your data originates. Data Sources can include: Data Stream A Data Stream is an entity extracted from a Data Source, such as ‘Orders’ from Commerce Cloud, ‘Contacts’ from Sales Cloud, or ‘Subscribers’ from Marketing Cloud. Once a Data Source is connected to Data Cloud, Data Streams provide access to these entities and require assignment to a category: Profile, Engagement, or Other. A single Data Source can contain multiple Data Streams. Data Source Object (DSO) Data Streams are ingested into Data Source Objects (DSOs), which serve as temporary staging stores containing data in its raw, native format (e.g., CSV files). Minor transformations can be applied to fields during data ingestion. Data Lake Object (DLO) The next step in the data flow is the Data Lake Object (DLO). DLOs are typed, schema-based, materialized views that reside in the data lake (Amazon S3) and are generally stored as Apache Parquet files. This format, along with Apache Iceberg’s abstraction layer, supports efficient data storage and retrieval. DLOs are the first objects available for inspection and preparation of data, including field mapping and additional transformations. Data Model Object (DMO) Unlike DSOs and DLOs, which use a physical data store, Data Model Objects (DMOs) provide a virtual, non-materialized view into the data lake. Queries against a DMO return results based on the current data snapshot in DLOs, without storing them. DMOs can aggregate attributes from different Data Streams, Calculated Insights, and other sources. DMOs inherit their category from the first DLO mapped to them, and only DLOs with the same category can be mapped to the DMO. Like Salesforce objects, DMOs offer a canonical data model with pre-defined attributes (standard objects), and you can also create custom DMOs (custom objects). DMOs can have one-to-one or many-to-one relationships with other DMOs. Currently, there are 89 standard DMOs in Data Cloud, and this number is growing to support more use cases. DMOs are organized into various subject areas, including: Data Spaces Data Spaces offer logical partitions, allowing data to be segregated between different brands, regions, or departments, without the need for multiple Data Cloud instances. They also align with a Software Development Lifecycle (SDLC), enabling you to stage and test Data Objects in separate environments without affecting production data. Data Sources, Data Streams, and DLOs can be shared across Data Spaces, while DMOs and other platform features are isolated based on user permissions. Final Thoughts With the drop in storage costs and advancements in technology, companies now have vast datasets at their disposal. Every customer interaction, whether it’s a purchase, an email open, or a web page view, can be captured and stored. When properly organized, this data allows businesses to understand customers better, predict their needs, personalize interactions, and much more. However, one of Salesforce’s challenges is that its original platform, built over 20 years ago, was designed for a different era and struggles with handling voluminous, “big” data. Salesforce Data Cloud addresses these limitations with a modern architecture that overcomes the constraints of relational databases. Data Cloud is poised to become the backbone of the Salesforce platform, supporting the data needs of customers and products for the next two decades. If you’re interested in learning how to implement and integrate Salesforce Data Cloud in your organization, following best practices, reach out today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 8, 2024in Data, Google, Salesforce, Salesforce Data Cloud, Snowflake, Technology, Unified Knowledge
Revolution Customer Service with Agentforce
08Oct

Revolution Customer Service with Agentforce

Agentforce stole the spotlight at Dreamforce, but it’s not just about replacing human workers. Equally significant for Service Cloud was the focus on how AI can be leveraged to make agents, dispatchers, and field service technicians more productive and proactive. Join a conversation to unpack the latest Sales Cloud innovations, with a spotlight on Agentforce for sales followed by a Q&A with Salesblazers. During the Dreamforce Service Cloud keynote, GM Kishan Chetan emphasized the dramatic shift over the past year, with AI moving from theoretical to practical applications. He challenged customer service leaders to embrace AI agents, highlighting that AI-driven solutions can transform customer service from delivering “good” benefits to achieving exponential growth. He noted that AI agents are capable of handling common customer requests like tech support, scheduling, and general inquiries, as well as more complex tasks such as de-escalation, billing inquiries, and even cross-selling and upselling. In practice, research by Valoir shows that most Service Cloud customers are still in the early stages of AI adoption, particularly with generative AI. While progress has accelerated recently, most companies are only seeing incremental gains in individual productivity rather than the exponential improvements highlighted at Dreamforce. To achieve those higher-level returns, customers must move beyond simple automation and summarization to AI-driven transformation, powered by Agentforce. Chetan and his team outlined four key steps to make this transition. “Agentforce represents the Third Wave of AI—advancing beyond copilots to a new era of highly accurate, low-hallucination intelligent agents that actively drive customer success. Unlike other platforms, Agentforce is a revolutionary and trusted solution that seamlessly integrates AI across every workflow, embedding itself deeply into the heart of the customer journey. This means anticipating needs, strengthening relationships, driving growth, and taking proactive action at every touchpoint,” said Marc Benioff, Chair and CEO, Salesforce. “While others require you to DIY your AI, Agentforce offers a fully tailored, enterprise-ready platform designed for immediate impact and scalability. With advanced security features, compliance with industry standards, and unmatched flexibility. Our vision is bold: to empower one billion agents with Agentforce by the end of 2025. This is what AI is meant to be.” In contrast to now-outdated copilots and chatbots that rely on human requests and strugglewith complex or multi-step tasks, Agentforce offers a new level of sophistication by operating autonomously, retrieving the right data on demand, building action plans for any task, and executing these plans without requiring human intervention. Like a self-driving car, Agentforce uses real-time data to adapt to changing conditions and operates independently within an organizations’ customized guardrails, ensuring every customer interaction is informed, relevant, and valuable. And when desired, Agentforce seamlessly hands off to human employees with a summary of the interaction, an overview of the customer’s details, and recommendations for what to do next. Deploy AI agents across channelsAgentforce Service Agent is more than a chatbot—it’s an autonomous AI agent capable of handling both simple and complex requests, understanding text, video, and audio. Customers were invited to build their own Service Agents during Dreamforce, and many took up the challenge. Service-related agents are a natural fit, as research shows Service Cloud customers are generally more prepared for AI adoption due to the volume and quality of customer data available in their CRM systems. Turn insights into actionLaunching in October 2024, Customer Experience Intelligence provides an omnichannel supervisor Wall Board that allows supervisors to monitor conversations in real time, complete with sentiment scores and organized metrics by topics and regions. Supervisors can then instruct Service Agent to dive into root causes, suggest proactive messaging, or even offer discounts. This development represents the next stage of Service Intelligence, combining Data Cloud, Tableau, and Einstein Conversation Mining to give supervisors real-time insights. It mirrors capabilities offered by traditional contact center vendors like Verint, which also blend interaction, sentiment, and other data in real time—highlighting the convergence of contact centers and Service Cloud service operations. Empower teams to become trusted advisorsSalesforce continues to navigate the delicate balance between digital and human agents, especially within Service Cloud. The key lies in the intelligent handoff of customer data when escalating from a digital agent to a human agent. Service Planner guides agents step-by-step through issue resolution, powered by Unified Knowledge. The demo also showcased how Service Agent can merge Commerce and Service by suggesting agents offer complimentary items from a customer’s shopping cart. Enable field teams to be proactiveSalesforce also announced improvements in field service, designed to help dispatchers and field service agents operate more proactively and efficiently. Agentforce for Dispatchers enhances the ability to address urgent appointments quickly. Asset Service Prediction leverages AI to forecast asset failures and upcoming service needs, while AI-generated prework briefs provide field techs with asset health scores and critical information before they arrive on site. Setting a clear roadmap for adopting Agentforce across these four areas is an essential step toward helping customers realize more than just incremental gains in their service operations. Equally important will be helping customers develop a data strategy that harnesses the power of Data Cloud and Salesforce’s partner ecosystem, enabling a truly data-driven service experience. Investments in capabilities like My Service Journeys will also be critical in guiding customers through the process of identifying which AI features will deliver the greatest returns for their specific needs. Agentforce leverages Salesforce’s generative AI, like Einstein GPT, to automate routine tasks, provide real-time insights, and offer personalized recommendations, enhancing efficiency and enabling agents to deliver exceptional customer experiences. Agentforce is not just another traditional chatbot; it is a next-generation, AI-powered solution that understands complex queries and acts autonomously to enhance operational efficiency. Unlike conventional chatbots, Agentforce is intelligent and adaptive, capable of managing a wide range of customer issues with precision. It offers 24/7 support, responds in a natural, human-like manner, and seamlessly escalates to human agents when needed and redefining customer service by delivering faster, smarter, and more effective support experiences. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM

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October 8, 2024in Data, Enterprise, Generative AI, Salesforce, Unified Knowledge
Weekly Opportunity Report
08Oct

Weekly Opportunity Report

Building a Weekly Opportunity Report with Different Criteria for Various Opportunity Types An individual was attempting to create a weekly opportunity report using complex filter logic to accommodate different criteria for various types of opportunities. Initially, they tried using the standard “Gifts with Payments” report type but faced challenges due to the nature of the opportunities. Some opportunities needed to be included based on the Close Date, while others were based on the GL Post Date. Since some opportunities have multiple payments, they wanted to use the GL Post Date from the payment record. However, not all opportunities have payment records, such as in-kind gifts. When they filtered by the Payment GL Post Date, it excluded all in-kind gifts, even though this filter was not relevant to them. The in-kind gifts matched the logic for the Close Date (e.g., 2 AND NOT 4 AND NOT 6 AND 8), but they were still being excluded. Here’s the challenge they faced: They also highlighted that the General Ledger Post Date and Payment GL Post Date are custom fields populated manually. The individual is looking for a solution to resolve this issue, allowing them to generate a report that properly includes opportunities based on the necessary criteria while keeping in-kind gifts in the report. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 8, 2024in Salesforce
Coveo and Salesforce Data Cloud
07Oct

Coveo and Salesforce Data Cloud

Coveo Integrates with Salesforce Data Cloud for Enhanced Data Access Coveo has officially integrated with Salesforce Data Cloud, providing companies with improved access to a broad range of data across the Salesforce ecosystem. This integration enhances the capabilities of Salesforce’s Service Cloud, Commerce Cloud, and Experience Cloud by offering secure access to a wide array of enterprise data sources and engagement data from Coveo-powered search experiences. By leveraging Coveo’s advanced indexing and security features, the integration enables enterprises to seamlessly inject external content into Salesforce experiences through Data Cloud. It also delivers comprehensive analytics across both platforms, allowing businesses to track interactions and touchpoints more effectively. “Coveo has worked closely with Salesforce on a global scale for over a decade,” said Laurent Simoneau, president and CTO of Coveo. “The integration of Coveo with Salesforce creates a powerful synergy, particularly beneficial for large enterprises with complex content ecosystems. Coveo’s robust indexing and relevance capabilities, combined with Salesforce Data Cloud, provide secure access to external data sources, boosting performance and delivering added value across all Salesforce Clouds. This integration sets a new standard for unifying enterprise data and elevating the customer experience.” Kishan Chetan, executive vice president and general manager of Service Cloud at Salesforce, emphasized the impact on service interactions: “Providing precise answers during service interactions is crucial for reducing service costs and improving customer satisfaction, especially for large enterprises managing vast amounts of content and diverse customer bases. Coveo’s ability to connect to extensive content sources and enhance relevance is a key enabler for enterprises with complex search needs in Service Cloud.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 7, 2024in Salesforce Data Cloud
Salesforce Agentforce Integration
07Oct

Salesforce Agentforce Integration

The rise of AI-powered solutions is transforming customer service, support, and automation. For organizations such as nonprofits, national associations, and large enterprises, delivering seamless customer experiences has become crucial. Salesforce’s Agentforce, a next-generation conversational AI tool, plays a vital role in this transformation. Designed to elevate customer support and interaction, Agentforce provides an intelligent and scalable solution for integrating AI chatbots into content management systems (CMS) like WordPress, Drupal, and HubSpot. Salesforce Agentforce Integration. In this detailed feature review, we will dive into the extensive capabilities of Salesforce Agentforce, analyzing its role as a conversational tool, its technical requirements, and the benefits it provides for nonprofits, national associations, and businesses. We’ll also compare its applications across various CMS platforms like Drupal, WordPress, and HubSpot, exploring its potential as a powerful AI assistant for website automation and customer interaction. Salesforce Agentforce: A Technical Perspective Salesforce Agentforce is an advanced AI-driven conversational assistant that seamlessly integrates into the Salesforce environment. By tapping into Salesforce CRM’s vast data resources, Agentforce serves as an intelligent interface, automating everything from initial customer inquiries to more personalized interactions. Utilizing natural language processing (NLP) and machine learning, it continually refines responses and scales interactions, making it an indispensable tool for organizations aiming to enhance customer service workflows. Agentforce integrates smoothly with Salesforce Service Cloud, automating both live chat support and chatbot responses. Additionally, it can connect with third-party platforms, including popular CMS solutions like WordPress, Drupal, and HubSpot, allowing organizations to centralize customer service operations in one interface. Core Features and Technical Architecture of Agentforce Natural Language Understanding (NLU) and Processing (NLP) Agentforce’s NLP capabilities are its backbone, allowing it to understand complex human language and respond contextually. This empowers it to manage initial inquiries as well as more sophisticated support requests. Agentforce’s NLU also enables it to work across different languages, dialects, and industry-specific terminology, making it particularly valuable for global organizations and national associations serving diverse audiences. Machine Learning for Continuous Improvement Agentforce’s machine learning feature enhances its ability to improve accuracy and understanding over time. Each interaction helps the chatbot evolve, making it more effective at delivering relevant, real-time responses. This model integrates directly with Salesforce’s data infrastructure, giving Agentforce access to historical data and interactions to offer highly personalized, context-aware answers. Deep Integration with Salesforce CRM As a Salesforce-native tool, Agentforce can harness CRM data in ways other AI tools cannot. By accessing customer histories, purchase data, and previous interactions, it creates personalized experiences that build customer trust. Nonprofits and associations can use this data to improve donor or member interactions, offering targeted support and outreach. Agentforce can also be tailored to retrieve specific datasets, such as an individual’s support history or ongoing service case updates. Cross-Platform Flexibility and API Integration Agentforce offers flexible APIs that enable integration with third-party systems, including CMS platforms like WordPress, Drupal, and HubSpot. This flexibility ensures that AI-powered chatbots can be deployed on organizational websites, providing a seamless experience for customers, donors, and members alike. Whether it’s a nonprofit using Drupal or a business on WordPress, Agentforce acts as the central hub for support and engagement, offering fluid interactions on top of your CMS. HubSpot users can further leverage Agentforce’s marketing features to align lead generation with personalized, chat-based interactions. Use Cases for Agentforce in Nonprofits, National Associations, and Businesses Nonprofit Organizations For nonprofits managing donor, volunteer, and beneficiary relationships, Agentforce offers scalable, automated support: National Associations National associations can use Agentforce to handle high volumes of inquiries from members and professionals: Businesses For service-based enterprises, Agentforce is essential for customer service: Salesforce Agentforce and CMS Integration: WordPress, Drupal, and HubSpot WordPress and Salesforce Agentforce Integration For WordPress users, Agentforce offers customizable chatbot widgets that enhance customer engagement, handle ecommerce inquiries, and integrate with WooCommerce for product support. Drupal and Agentforce Integration Drupal’s modular architecture allows Agentforce to automate membership management, provide multilingual support, and distribute content for nonprofits and associations. HubSpot and Agentforce Integration HubSpot users benefit from Agentforce’s ability to automate lead nurturing, sales and marketing workflows, and customer support, all while keeping HubSpot and Salesforce CRM data synchronized. Tectonic and Salesforce Agentforce Integration At Tectonic, we understand that adopting AI-powered solutions like Salesforce Agentforce is only the first step toward delivering exceptional customer experiences. We specialize in crafting, training, and implementing tailored AI chatbot solutions that enhance engagement, streamline processes, and drive growth, all while seamlessly integrating with your current website or mobile app. As a full-service digital strategy firm, Tectonic excels in integrating advanced tools like Salesforce Agentforce into platforms like WordPress, Drupal, and HubSpot, ensuring your automation strategies are executed with precision. From custom chatbot implementations to comprehensive digital strategy services, our team is dedicated to optimizing your website for engagement and lead generation. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 7, 2024in Agentforce Platform, AI Tools, Data, Enterprise, Salesforce, Salesforce Service Cloud
Tableau Einstein Alliance
07Oct

Tableau Einstein Alliance

We’re expanding our commitment to the future of data and analytics with the launch of the Tableau Einstein Alliance, an initiative designed to foster an ecosystem of visionary and innovative partners. These partners will help integrate Agentforce across every facet of analytics, positioning our customers to harness the full potential of AI. The future of data-driven insights is here, and our partners play a vital role in this journey. —Ryan Aytay, CEO, Tableau Salesforce Introduces Tableau Einstein Alliance Salesforce recently unveiled the Tableau Einstein Alliance, a new partner community for its Tableau Einstein users. This initiative aims to empower partners to excel in the “agent era” by offering exclusive benefits to support their development and implementation of AI-driven solutions and analytics agents. Members of the Alliance will gain access to product roadmaps, in-house expertise, and dedicated marketing support, as well as opportunities for co-selling. Moreover, Salesforce is offering these partners the ability to leverage the Alliance for building AI agents, apps, and solutions that maximize their clients’ investments in AI and data. What is Tableau Einstein? Launched in September, Tableau Einstein is an AI-powered visual analytics platform designed to scale and enhance data-driven workflows. It seamlessly integrates with Salesforce tools like Agentforce and its privacy framework, providing data professionals with the ability to create semantic models using real-time customer data. Tableau Einstein also features a marketplace where organizations can share analytical assets, and its APIs facilitate seamless collaboration. Teams can easily work together on data models, visualizations, and dashboards in a unified, drag-and-drop interface. Why Tableau Einstein Matters In discussing the platform, Ryan Aytay highlighted its transformative capabilities: “By leveraging high-performance AI to connect data, actions, and humans, autonomous and assistive agents are redefining business efficiency. They ensure that the data foundation you’re already using will continue to support your needs into the future. You no longer need to sift through data silos or be a specialist to access critical insights—data is now accessible to everyone.” With Tableau Einstein, Salesforce is setting a new standard for how businesses can achieve success with AI-powered, data-driven insights. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 7, 2024in Data, Salesforce, Salesforce Tableau

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