Analytics Archives - gettectonic.com

06Oct

Ethical AI Implementation

AI technologies are rapidly evolving, becoming a practical solution to support essential business operations. However, creating true business value from AI requires a well-balanced approach that considers people, processes, and technology. Ethical AI Implementation. AI encompasses various forms, including machine learning, deep learning, predictive analytics, natural language processing, computer vision, and automation. To leverage AI’s competitive advantages, companies need a strong foundation and a realistic strategy aligned with their business goals. “Artificial intelligence is multifaceted,” said John Carey, managing director at AArete, a business management consultancy. “There’s often hype and, at times, exaggeration about how ‘intelligent’ AI truly is.” Business Advantages of AI Adoption Recent advancements in generative AI, such as ChatGPT and Dall-E, have showcased AI’s significant impact on businesses. According to a McKinsey Global Survey, global AI adoption surged from around 50% over the past six years to 72% in 2024. Some key benefits of adopting AI include: Prerequisites for AI Implementation Successfully implementing AI can be complex. A detailed understanding of the following prerequisites is crucial for achieving positive results: 13 Steps for Successful AI Implementation Common AI Implementation Mistakes Organizations often stumble by: Key Challenges in Ethical AI Implementation Human-related challenges often present the biggest hurdles. To overcome them, organizations must foster data literacy and build trust among stakeholders. Additionally, challenges around data management, model governance, system integration, and intellectual property need to be addressed. Ensuring Ethical AI Implementation To ensure responsible AI use, companies should: Ethical AI implementation requires a continuous commitment to transparency, fairness, and inclusivity across all levels of the organization. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

October 6, 2024in AI Tools, Artificial Intelligence, Data, Generative AI, Salesforce, Technology

Salesforce for K-12 and Higher Education

04Oct

Technology to Showcase the Value of Education

How Can Technology Convince Students of the Value of Higher Education? With fewer high school graduates choosing college, technology has a unique role in reigniting students’ belief in higher education. Imagine a high school student eagerly checking the mail and finding an acceptance letter from their dream college, ready to start a journey filled with opportunities, lifelong friends, and a promising future. Just a couple of decades ago, that was a common story. Today, many high schoolers aren’t looking for acceptance letters at all, uncertain if college is the best or even most practical path to success. Higher education now faces a new challenge: proving its worth to students who are increasingly weighing their options. Universities no longer simply wait for students to apply—they need to actively demonstrate that the investment will pay off. Enrollment Data Signals a Shift Away from College Once seen as a distinctive achievement, college attendance has become less of a given. In 1980, only 49% of high school graduates went on to higher education. By 2009, that number had surged to over 70%, but has since declined; by 2022, just 62% of graduates were heading straight to college. Now, with the “enrollment cliff”—a projected decrease in college-aged students due to lower birth rates—looming, colleges face intense competition to attract students. Personalization Is Key to Connecting with Students The days of “Dear applicant” are over. Today’s digital-native students want a personalized approach that speaks directly to them. If they don’t feel personally addressed through email, text, video, or even traditional mail, they may tune out and explore other options. Universities must build meaningful connections to engage students and keep their attention through every stage of the student journey. Student lifecycle management platforms, like Salesforce’s Education Cloud, have become essential tools for higher education institutions. By tracking and analyzing a student’s data—academic performance, extracurricular interests, and social behaviors—these platforms create personalized experiences that engage students from admission to graduation. Salesforce Education Cloud, for example, uses AI and robust data analytics to create a comprehensive student profile, enabling colleges to send tailored communications, schedule regular check-ins, and even reach out to parents. This personalized approach fosters a sense of connection that encourages students to enroll and stay engaged throughout their academic journey. Comprehensive Lifecycle Management and Student Support Beyond admissions, student lifecycle platforms offer extensive features that address other critical areas, from helping students who are academically struggling to managing alumni relationships and fundraising. With years of experience in supporting institutions nationwide, CDW Education partners with colleges to implement these technologies, strengthening their ability to attract, engage, and retain students. In an era when students have more educational choices than ever, colleges must actively communicate the value of a college degree and make that message resonate with each individual. By investing in technology that personalizes the student experience, higher education institutions can create a compelling case for the unique value they offer. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

October 4, 2024in Data, Salesforce, Salesforce Education Cloud, Technology

03Oct

Sales Incentives Can Boost Morale and Performance

Showing up to work is one thing, but bringing genuine enthusiasm to the job is another. How can you motivate your team to meet and exceed their goals? Sales incentives are a powerful tool to ignite motivation, but they aren’t one-size-fits-all. Figuring out the best structure for your team can lead to more energized, results-driven reps. In this Tectonic insight, we’ll explore different types of sales incentives, how they motivate teams, and best practices for implementing an effective incentive program that drives real results. What are Sales Incentives? Sales incentives are rewards given to sales reps, in addition to their base compensation, for exceptional performance. This often means hitting or exceeding sales targets. While financial bonuses are the most common, incentives can come in many forms, all designed to motivate specific behaviors or outcomes. Types of Sales Incentives Here are five common types of sales incentives to consider: How Sales Incentives Motivate Your Team Sales incentives help reinforce desired behaviors, offering a clear path to rewards. They provide a mutual win: your company increases sales, while reps enjoy additional rewards. Many sales professionals are naturally driven by competition, but incentives give everyone, competitive or not, something tangible to work toward. Incentives also boost employee satisfaction, reduce turnover, and show that you value hard work. This can save your organization the cost and hassle of recruiting and onboarding new talent. Sales Incentives That Actually Work While money is the most popular reward, mixing in creative incentives can add excitement to your program. Consider these options: Best Practices for Implementing Sales Incentives To create an effective sales incentive program, keep these points in mind: Measuring the Impact of Sales Incentives on Performance To assess the effectiveness of your incentive program, track key performance indicators (KPIs) such as: Sales Incentives Can Boost Morale and Performance The key to a successful sales incentive program is simplicity and transparency. By crafting a plan that’s easy to understand and aligned with your team’s motivations, you can drive better performance and improve job satisfaction at the same time. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

October 3, 2024in Data, Technology

03Oct

Tableau Einstein Alliance to Help Partners Drive Success in the Agent Era

Salesforce Unveils Tableau Einstein Alliance to Empower Partners in the AI-Driven Agent Era Salesforce today announced the launch of the Tableau Einstein Alliance, a new partner community designed to create and deliver AI-driven solutions and analytical agents for Tableau Einstein. Built on the Salesforce platform and integrated with Agentforce, this initiative aims to help partners accelerate success in the emerging AI landscape. Tableau Einstein Alliance to Help Partners Drive Success in the Agent Era The Tableau Einstein Alliance offers partners a range of exclusive benefits, including early access to Salesforce’s product roadmaps, in-house AI experts, marketing support, and co-selling opportunities. Through the Alliance, partners will be able to develop agents, apps, and AI-driven solutions, enabling customers to navigate the autonomous AI revolution and rapidly extract value from their data and AI investments. The Alliance is set to launch in February 2025 with 25 founding members, including Tectonic, Capgemini, Deloitte, IBM, and Slalom. Solutions developed within the Alliance will be available on both the Salesforce AppExchange and the forthcoming Tableau Marketplace, offering developers a platform to create, share, and monetize analytical assets. Why It Matters:Partner ecosystems have been crucial in advancing major technological innovations, from cloud computing to software-as-a-service. With the rise of Agentforce, building a dynamic partner community is more critical than ever to drive the next wave of AI and analytics adoption. Salesforce’s Perspective: “Tableau’s success is deeply rooted in our partners’ commitment to our customers. Now, we’re investing in the Tableau Einstein Alliance to cultivate an ecosystem of visionary and innovative partners who will integrate Agentforce into every facet of analytics. The future of data and analytics is here, and our partners are essential to this journey.”— Ryan Aytay, CEO, Tableau Industry Perspectives: “Atrium has championed the vision of unified analytics since Tableau joined the Salesforce ecosystem. We’ve seen the incredible potential of Data Cloud and Tableau Cloud together, and we’re thrilled to help bring Tableau Einstein to market. Its integrated features will offer customers unprecedented productivity.”— Chris Heineken, CEO, Atrium “Tectonic’s “Insight to Action” methodology (i2a) is directly improved by the launch of the Tableau Einstein Alliance. By utilizing automated AI-solutions to power data-driven insights, we are able to deliver additional value to our customers.”— Dan Grossnickle, Tectonic “Tableau Einstein represents the next step in Salesforce’s data platforms and generative AI products. The value for clients from these data-driven insights is immense. We’re excited to help lead the way through the Tableau Einstein Alliance.”— Jean-Marc Gaultier, Head of Group Strategic Initiatives and Partnerships, Capgemini “Deloitte has long benefited from Tableau’s capabilities, and we’re excited to see how this next iteration will further empower our teams with data to drive growth. Integrating key features into tools like Salesforce and Slack will unlock even greater potential for us.”— Moritz Schieder, Tableau Alliance Leader and Director, Deloitte Germany “IBM is eager to leverage Tableau Einstein to deliver more value to our customers, regardless of where they work. As a strategic Agentforce partner and Salesforce customer, we are excited to be part of the next generation of analytics alongside Salesforce.”— Mary Rowe, Global Head of IBM Consulting Salesforce Practice Tableau Einstein Alliance to Help Partners Drive Success in the Agent Era and Tectonic, an insights 2 actions company, is excited to be a part of the innovation. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

October 3, 2024in Data, Generative AI, Salesforce, Salesforce Development Services, Salesforce Tableau

03Oct

Salesforce and the Customer-Centric Dealership

Building Blocks for a Customer-Centric Dealership For a dealership to thrive, it must be truly customer-centric. As a Salesforce Implementation Partner, we at Tectonic know the key to success lies in prioritizing customer needs at every step. Growth, profitability, and market expansion come from consistently putting customers at the center of your strategies. Tectonic can help you implement Salesforce and the Customer-Centric Dealership. Customers as the Ultimate Scorekeepers Your customers are the true measure of your dealership’s success. Their evaluations extend far beyond pricing—they assess every touchpoint, from your website’s ease of use to the cleanliness of your parking lot, from your voicemail system to post-sale follow-ups. Each interaction shapes their perception. A single negative encounter, such as a poor experience with a parts associate, may not drive them away, but it certainly won’t motivate them to return. Creating positive, seamless interactions is crucial. Optimizing Customer-Centric Processes Are your processes truly serving your customers? Are they complimenting your dealership’s efficiency? Take something as routine as monthly statements. While they may be straightforward for your team, have you considered your customers’ perspectives? They may not even want a statement, or they might need quicker, more accessible responses to their inquiries. As customer expectations rise due to experiences with brands like Amazon and Starbucks, your dealership must ensure its processes meet or exceed those standards. A Customer portal like Salesforce Experience Cloud can put resources at your customers’ fingertips with the click of a button. Treating Customer Data as a Strategic Asset Customer data is one of your dealership’s most valuable assets. Yet, many dealerships struggle to fully utilize this resource. Are you effectively visualizing and leveraging your customer data? This data, gathered over years of operation, can drive strategic decision-making. To maximize its potential, it’s crucial to have a dedicated role—perhaps a Chief Data Officer—focused on managing, updating, and safeguarding this information. A well-managed data strategy unlocks insights that fuel customer-centric improvements. Letting Data Shape Your Processes With Salesforce, you can use customer data to quickly identify inefficiencies and enhance processes. Streamlined operations lead to happier customers and a more engaged team. For instance, if your manufacturer can deliver most parts within 24 hours, why maintain an overstocked inventory? By analyzing your inventory data, Salesforce can help you identify which parts are essential and which are surplus, allowing you to optimize stock levels and ensure smoother operations. Aligning your inventory with actual demand ensures your dealership functions efficiently, keeping both your customers and staff satisfied. Expert Guidance in Leveraging Salesforce for Growth Adopting a customer-centric approach and utilizing Salesforce to analyze and act on your data can transform your dealership. As your Salesforce Implementation Partner, we’re here to help you integrate these solutions to meet and exceed customer expectations while driving growth and profitability. Together, we can build a dealership that not only competes but thrives in today’s competitive market. With the future of AI, the connected car, and more; there has never been a betrter time to add Salesforce to your customer-centric tool box. Reach out to schedule an introductory call and start your journey toward a more customer-centric future. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

October 3, 2024in Data, Google, Salesforce, Salesforce Experience Cloud

03Oct

Supercharged Sales and Service Excellence

When sales and service teams are seamlessly aligned, organizations can transform every service interaction into a powerful opportunity to drive revenue and build customer loyalty. By delivering contextual, personalized offers at the right time, businesses can turn each customer touchpoint into a chance to solve problems, create value, and enhance engagement. With the help of real-time data and AI, we move beyond treating customer interactions as isolated events. Instead, we focus on understanding the unique needs and preferences of each customer, whether they’re reaching out for support, visiting a store, or engaging online. Every touchpoint becomes an opportunity to deliver tailored solutions, strengthen loyalty, and increase revenue. These examples are just a glimpse of the solutions we help our clients deploy. With our deep expertise in AI implementation and industry-specific insights, Tectonic is ideally positioned to guide you through activating AI agents that build on your successes. Our extensive experience across diverse sectors enables us to identify the most impactful opportunities for AI, ensuring tailored solutions that align with your business strategy. Tectonic’s proven approach ensures AI agents are deployed efficiently and effectively, driving ROI and delivering measurable results. Agentforce: Open, Extensible, and Transformative Agentforce is designed to foster smooth interactions between agents created on the platform and external agents and applications. With integration into Salesforce Data Cloud, it enables real-time data access for better, faster decision-making. Tectonic can help facilitate this interconnectivity across various channels and platforms, ensuring seamless operations. In a society that prioritizes digital, artificial intelligence is changing sales and service tactics. Adopting AI agents is crucial for business leaders to keep ahead of the competition and develop more effective and efficient methods of customer and employee support. AI agents are not just upgrades—they are transformative forces that redefine what’s possible. They empower organizations to move from envisioning possibilities to realizing a future of enhanced sales performance, streamlined operations, and unmatched customer satisfaction, all powered by AI. Salesforce’s Agentforce: Scaling Your Workforce with Autonomous AI Agents Agentforce provides fully customizable autonomous AI agents that can integrate with enterprise data and take action across sales, service, marketing, and commerce. The Agent Builder allows users to create agents that automate any business process, in any industry, using existing Salesforce tools such as workflows, Apex code, and prompt templates. Leading companies like The Adecco Group, BACA Systems, OpenTable, Saks, and Wiley are already leveraging Agentforce Service Agents to deliver faster, more personalized customer responses while improving operational efficiency. Salesforce (NYSE: CRM), the world’s #1 AI CRM, has announced the general availability of Agentforce. This new platform layer enables businesses to create and deploy AI agents that autonomously take action across any business function. Unlike traditional chatbots and copilots, Agentforce agents possess advanced reasoning abilities to make decisions and take actions such as resolving customer issues, qualifying sales leads, and optimizing marketing efforts. These agents operate independently—triggered by changes in data, business rules, pre-built automations, or external signals from APIs. Agentforce includes out-of-the-box agents that can be easily customized and deployed with low-code or no-code tools, working around the clock across any channel. The first of these, the Agentforce Service Agent, outperforms traditional chatbots by handling a wide range of tasks—from simple to complex—using pre-built topics and actions for customer support. These agents are fully customizable to serve various industries, such as retail with order management or financial services with billing and payment support. “Agentforce is redefining business possibilities, ushering in an era of AI-driven abundance and limitless workforces that enhance every employee’s capabilities, strengthen customer relationships, and fuel unprecedented growth,” said Marc Benioff, Chair and CEO of Salesforce. “Built on Salesforce’s trusted, fully customizable platform—integrating enterprise data, metadata, AI models, workflows, security, and applications—Agentforce is everything AI was meant to be.” The Power of Agentforce With Agentforce, there’s no need for DIY AI. Unlike other platforms that require complex integrations and custom builds, Agentforce is natively built into the Salesforce Platform. Customers can instantly convert their existing Flows, prompt templates, Apex code, and APIs into agent actions, seamlessly connecting to enterprise data and security models. With the added power of native tools like Data Cloud, Slack, and MuleSoft, Agentforce offers a streamlined and efficient approach to scaling your workforce with AI. The new Agent Builder empowers Salesforce admins and developers to easily create AI agents with natural language instructions and guardrails, enabling even more customization and control. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

October 3, 2024in Agentforce Platform, Artificial Intelligence, Data, Enterprise, Google, Hyperforce, Mulesoft, Salesforce, Salesforce Data Cloud

02Oct

Marketing Cloud and Generative AI

Generative AI and Salesforce: Revolutionizing Digital Marketing with Einstein AI Generative AI is a form of Artificial Intelligence that learns from existing content to generate new, creative outputs. Salesforce has long been at the forefront of AI innovation, primarily through its Einstein assistant, which has evolved to offer increasingly sophisticated solutions over time. Artificial Intelligence: Key Concepts Before diving into Salesforce’s AI capabilities, let’s clarify some foundational concepts. Artificial Intelligence (AI) refers to the creation of intelligent systems that can learn and reason autonomously. Within AI, Machine Learning (ML) plays a crucial role by enabling computers to learn from data and improve over time without explicit programming. ML models fall into two broad categories: Deep Learning and Neural Networks A more advanced subset of ML is Deep Learning, which uses neural networks to process large amounts of data and make autonomous decisions. Deep Learning powers technologies like voice assistants (e.g., Alexa or Siri), which can recognize speech and execute tasks. A specific application within Deep Learning is Generative AI, capable of autonomously creating new content based on learned patterns from vast datasets. Another critical AI system is the Foundational Model, which is trained on enormous amounts of unstructured data from across the web, including text, images, and videos. These models offer a wide range of capabilities, such as generating text, answering questions, creating designs, or solving complex problems. Salesforce Marketing Cloud and AI Salesforce has utilizeded AI through its Einstein platform, which has evolved over time to offer a variety of data-driven tools. For example, Sent Time Optimization uses customer data to determine the best time to send emails to maximize engagement. AI Tools in Salesforce Marketing Cloud Salesforce offers several AI-powered tools for Marketing Cloud to help businesses leverage data for personalization and efficiency: The Einstein Trust Layer: AI in Salesforce CRM Einstein is the first generative AI model integrated into a CRM, and Salesforce refers to its AI process as the Einstein Trust Layer. Here’s how it works: Marketing Applications of Salesforce AI Tools Salesforce’s AI tools can be applied across omnichannel marketing campaigns to hyper-personalize communication, increasing conversion rates and customer engagement. Predictive analytics also allow businesses to optimize cross-selling and upselling, offering tailored product recommendations based on customer behavior. Chatbots powered by AI further enhance productivity by interacting in natural language, collecting leads, suggesting products, and resolving customer inquiries. Salesforce’s Commitment to AI in Digital Marketing Salesforce has been a pioneer in AI, continually expanding its capabilities through Einstein. With the latest AI tools for Marketing Cloud, businesses can now interact with customers more precisely, boost engagement, and optimize purchase predictions—paving the way for a new era in digital marketing. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

October 2, 2024in AI Tools, Artificial Intelligence, Data, Generative AI, Salesforce, Salesforce Marketing Cloud

01Oct

Salesforce Data Cloud Innovations Announced

Salesforce Data Cloud Drives Customer Experience Transformation with New Data and AI Innovations Salesforce has unveiled new innovations within its Data Cloud, enhancing the way organizations transform customer experiences by leveraging data and AI. Key advancements include expanded support for unstructured data, enabling native processing of audio and video content—such as webinars and calls—to unlock deeper insights into customer behavior. A standardized semantic data model ensures both Agentforce Agents and humans can consistently interpret and use data, while improved search capabilities enhance information discovery by factoring in customer context. Real-time data activations allow organizations to respond instantly to evolving customer needs, and new data security and governance features safeguard operations and prevent data exposure. “In this new era of AI and Agents, customer data and metadata are the new gold for the enterprise,” said Rahul Auradkar, EVP and GM for Data Cloud at Salesforce. “More companies are using Data Cloud to unify all their data—from customer interactions and product usage to IoT and social media data—gaining deeper insights across all touchpoints. Because Data Cloud is foundational to Salesforce, companies can act on this data to deliver personalized, meaningful customer experiences.” Data Cloud integrates with Salesforce Customer 360, Agentforce, Flow, and analytics, providing a trusted data foundation for personalized experiences and real-time analytics. It powers data-driven actions and workflows while securely enabling AI across all Salesforce applications. Leveraging zero-copy technology and MuleSoft connectors, Data Cloud can ingest data from hundreds of sources, including data lakes and warehouses. Integrated into the Salesforce Platform, this metadata seamlessly flows into Salesforce applications, governed by set policies. This gives every team a 360-degree customer view, driving AI, automation, and analytics without compromising security. Data Cloud also enhances Agentforce, providing contextual insights and guiding next-best steps, like automating follow-up emails or sharing detailed chat summaries with human agents. Tableau Semantics bridges the gap between AI and employees, ensuring they operate with consistent data definitions. The following new Data Cloud features will be available across various release stages: For more information, visit www.salesforce.com. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

October 1, 2024in Data, Enterprise, Mulesoft, Salesforce, Salesforce Data Cloud, Technology

01Oct

Data Governance in Salesforce

Use Case Highlights Introduction Salesforce is a powerful platform for building strong customer relationships. However, to maximize the value of your data, a strategic approach is essential. Unmanaged data can lead to inconsistencies, security vulnerabilities, and compliance issues, making it difficult to rely on Salesforce data for strategic decision-making. This data governance insight looks into data governance for Salesforce and highlights top tools that integrate seamlessly with the platform. While these tools are not exclusively built for Salesforce, they offer powerful features that enhance the accuracy, security, and regulatory compliance of your data. Implementing a data governance strategy with the right tools unlocks the hidden potential of your Salesforce data. Imagine making decisions based on reliable information, streamlining workflows, and maximizing data value—all possible with clean, trustworthy data at your fingertips. Disclaimer: The specific third-party security solutions mentioned in this insight are for informational purposes only and do not constitute endorsements by Tectonic. 6 Data Governance Tools for Salesforce Users Understanding the Importance of Data Governance in Salesforce Salesforce, a cornerstone for managing customer relationships, thrives on a rich data repository. However, unmanaged data growth can lead to inconsistencies, security vulnerabilities, and compliance hurdles, hindering the data’s potential to drive strategic decisions. Data governance goes beyond data management. It establishes principles and practices to ensure your Salesforce data is: Why is data governance crucial for Salesforce? Data governance transforms data from a potential liability into a strategic asset, driving informed decisions, fostering trust, and empowering your organization to achieve its goals. Key Challenges in Salesforce Data Governance Implementing robust data governance within Salesforce presents challenges: Evaluating Data Governance Tools for Salesforce Choosing the right data governance tool for Salesforce requires careful evaluation: Comparing Top Data Governance Solutions for Salesforce When comparing top data governance solutions, assess factors like features, pricing, scalability, and customer reviews. A comparison table can offer a quick overview of key features and differences between solutions. Product Key Features Pricing Collibra Centralized platform, business glossary management, data lineage tracking, access controls Starting at $170,000/year Dataedo Collaborative data catalog, data documentation, quality rules, improved data literacy Starting at $18,000/year Alation Data discovery and intelligence platform, searchable data catalog, business terms & data lineage Starting at $60,000/year OneTrust Data Governance AI-driven discovery & classification, integrated catalog, governance policy management Contact for pricing Talend Data Fabric Data quality checks, automated metadata management, data inventory & Trust Score, stewardship workflows Starting at $12,000/year Informatica Axon AI-powered discovery & quality assessment, stewardship communication, curated marketplaces, common dictionary Contact for pricing Data Governance in Salesforce This table provides a snapshot of key features and pricing, helping organizations make informed decisions based on their needs and budget. Reach out to Tectonic if you need assistance. Tectonic’s Remarks This insight has provided the knowledge to harness the true potential of your Salesforce data. Data governance is no longer a distant concept but a powerful practice that every organization must embrace. Success lies in selecting the right data governance solution. Consider your specific needs—whether it’s robust data lineage tracking offered by tools like Collibra and Talend, user-friendly interfaces from Dataedo and Alation, or cost-effectiveness. Several tools explored in this insight also offer strong security features to safeguard your customer data. Tools like Informatica Axon can assist with data discovery and quality assessment, empowering data stewards. By embracing data governance and leveraging the right tools, you can transform Salesforce data from a raw resource into a strategic asset. This newfound data clarity fuels informed decision-making, fosters customer trust, and drives your organization toward achieving its goals. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

October 1, 2024in Data, Enterprise, Salesforce

30Sep

Cortex Framework Integration with Salesforce (SFDC)

Cortex Framework: Integration with Salesforce (SFDC) This insight outlines the process of integrating Salesforce (SFDC) operational workloads into the Cortex Framework Data Foundation. By integrating Salesforce data through Dataflow pipelines into BigQuery, Cloud Composer can schedule and monitor these pipelines, allowing you to gain insights from your Salesforce data. Cortex Framework Integration with Salesforce explained. Prerequisite: Before configuring any workload integration, ensure that the Cortex Framework Data Foundation is deployed. Configuration File The config.json file in the Cortex Framework Data Foundation repository manages settings for transferring data from various sources, including Salesforce. Below is an example of how Salesforce workloads are configured: jsonCopy code”SFDC”: { “deployCDC”: true, “createMappingViews”: true, “createPlaceholders”: true, “datasets”: { “cdc”: “”, “raw”: “”, “reporting”: “REPORTING_SFDC” } } Explanation of Parameters: Parameter Meaning Default Value Description SFDC.deployCDC Deploy CDC true Generates Change Data Capture (CDC) processing scripts to run as DAGs in Cloud Composer. SFDC.createMappingViews Create mapping views true Creates views in the CDC processed dataset to show the “latest version of the truth” from the raw dataset. SFDC.createPlaceholders Create placeholders true Creates empty placeholder tables if they aren’t generated during ingestion, ensuring smooth downstream reporting deployment. SFDC.datasets.raw Raw landing dataset (user-defined) The dataset where replication tools land data from Salesforce. SFDC.datasets.cdc CDC processed dataset (user-defined) Source for reporting views and target for records processed by DAGs. SFDC.datasets.reporting Reporting dataset for SFDC “REPORTING_SFDC” Name of the dataset accessible for end-user reporting, where views and user-facing tables are deployed. Salesforce Data Requirements Table Structure: Loading SFDC Data into BigQuery The Cortex Framework offers several methods for loading Salesforce data into BigQuery: CDC Processing The CDC scripts rely on two key fields: You can adjust the CDC processing to handle different field names or add custom fields to suit your data schema. Configuration of API Integration and CDC To configure Salesforce data integration into BigQuery, Cortex provides the following methods: Example Configuration (settings.yaml): yamlCopy codesalesforce_to_raw_tables: – base_table: accounts raw_table: Accounts api_name: Account load_frequency: “@daily” Data Mapping and Polymorphic Fields Cortex Framework supports mapping data fields to the expected format. For example, a field named unicornId in your source system would be mapped to AccountId in Cortex with the string data type. Polymorphic Fields: Fields whose names vary but have the same structure can be mapped in Cortex using [Field Name]_Type, such as Who_Type for the Who.Type field in the Task object. Modifying DAG Templates You can customize DAG templates as needed for CDC or raw data processing. To disable CDC or raw data processing from API calls, set deployCDC=false in the configuration file. Setting Up the Extraction Module Follow these steps to set up the Salesforce to BigQuery extraction module: Cloud Composer Setup To run Python scripts for replication, install the necessary Python packages depending on your Airflow version. For Airflow 2.x: bashCopy codegcloud composer environments update my-composer-instance –location us-central1 –update-pypi-package apache-airflow-providers-salesforce>=5.2.0 Security and Permissions Ensure Cloud Composer has access to Google Secret Manager for retrieving stored secrets, enhancing the security of sensitive data like passwords and API keys. Conclusion By following these steps, you can successfully integrate Salesforce workloads into Cortex Framework, ensuring a seamless data flow from Salesforce into BigQuery for reporting and analytics. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 30, 2024in Data, Google, Salesforce

30Sep

Predictive Analytics in Salesforce

Predictive Analytics in Salesforce: Enhancing Decision-Making with AI In an ever-changing business environment, companies seek tools to forecast trends and anticipate challenges, enabling them to remain competitive. Predictive analytics, powered by Salesforce’s AI capabilities, offers a cutting-edge solution for these needs. In this guide, we’ll explore how predictive analytics works and how Salesforce empowers businesses to make smarter, data-driven decisions. What is Predictive Analytics? Predictive analytics uses historical data, statistical modeling, and machine learning to forecast future outcomes. With the vast amount of data organizations generate—ranging from transaction logs to multimedia—unifying this information can be challenging due to data silos. These silos hinder the development of accurate predictive models and limit Salesforce’s ability to deliver actionable insights. The result? Missed opportunities, inefficiencies, and impersonal customer experiences. When organizations implement proper integrations and data management practices, predictive analytics can harness this data to uncover patterns and predict future events. Techniques such as logistic regression, linear regression, neural networks, and decision trees help businesses gain actionable insights that enhance planning and decision-making. Einstein Prediction Builder A key component of the Salesforce Einstein Suite, Einstein Prediction Builder enables users to create custom AI models with minimal coding or data science expertise. Using in-house data, businesses can anticipate trends, forecast customer behavior, and predict outcomes with tailored precision. Key Features of Einstein Prediction Builder Note: Einstein Prediction Builder requires an Enterprise or Unlimited Edition subscription to access. Predictive Model Types in Salesforce Salesforce employs various predictive models tailored to specific needs: Building Custom Predictions Salesforce supports custom predictions tailored to unique business needs, such as forecasting regional sales or calculating appointment attendance rates. Tips for Building Predictions Prescriptive Analytics: Turning Predictions into Actions Predictive insights are only as valuable as the actions they inspire. Einstein Next Best Action bridges this gap by providing context-specific recommendations based on predictions. How Einstein Next Best Action Works Data Quality: The Foundation of Accurate Predictions The effectiveness of predictive analytics depends on the quality of your data. Poor data—whether due to errors, duplicates, or inconsistencies—can skew results and undermine trust. Best Practices for Data Quality Modern tools like DataGroomr can automate data validation and cleaning, ensuring that predictions are based on trustworthy information. Empowering Smarter Decisions with Predictive Analytics Salesforce’s AI-driven predictive analytics transforms decision-making by providing actionable insights from historical data. Businesses can anticipate trends, improve operational efficiency, and deliver personalized customer experiences. As predictive analytics continues to evolve, companies leveraging these tools will gain a competitive edge in an increasingly dynamic marketplace. Embrace the power of predictive analytics in Salesforce to make faster, more strategic decisions and drive sustained success. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 30, 2024in Data, Enterprise, Salesforce, Salesforce Einstein

28Sep

Benefits of AI in Banking

Artificial intelligence (AI) is rapidly gaining traction in the banking and finance sector, with generative AI (GenAI) emerging as a transformative force. Financial institutions are increasingly adopting AI technologies to automate processes, cut operational costs, and boost overall productivity, according to Sameer Gupta, North America Financial Services Organization Advanced Analytics Leader at EY. While traditional machine learning (ML) techniques are commonly used for fraud detection, loan approvals, and personalized marketing, banks are now advancing to incorporate more sophisticated technologies, including ML, natural language processing (NLP), and GenAI. Gupta notes that EY is observing a growing trend of banks using ML to enhance credit approvals, improve fraud detection, and refine marketing strategies, leading to greater efficiency and better decision-making. A recent survey by Gartner’s Jasleen Kaur Sindhu reveals that 58% of banking CIOs have either deployed or plan to deploy AI initiatives in 2024, with this number expected to rise to 77% by 2025. “This indicates not only the growing importance of AI but also its fundamental role in shaping how banks operate and deliver value to their customers,” Sindhu said. “AI is becoming essential to the success of banking institutions.” Here are five key benefits of AI applications in banking: Despite the benefits, concerns about AI in banking persist, particularly regarding data privacy, bias, and ethics. AI can inadvertently extract personal information and raise privacy issues. Regulatory challenges and the potential for AI systems to perpetuate biases are also major concerns. As AI technology evolves, banks are investing in robust governance frameworks, continuous monitoring, and adherence to ethical standards to address these risks. Looking ahead, AI is expected to revolutionize banking by delivering personalized services, enhancing customer interactions, and driving productivity. Deloitte forecasts that GenAI could boost productivity by up to 35% in the top 14 global investment banks, generating significant additional revenue per employee by 2026. 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 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, 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

September 28, 2024in Artificial Intelligence, Data, Generative AI, Technology

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 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 28, 2024in Data, Google, Salesforce, Salesforce Data Cloud, Snowflake

28Sep

Data Data Data

With the unprecedented surge in data—expected to grow by 22% this year according to the Salesforce State of Data and Analytics 2023 report—and the rapid evolution of AI, maintaining data quality and security has become more critical than ever. The AI and Information Management 2024 Report highlights that 52% of organizations encountered data quality issues during AI implementation, while 71% expressed serious concerns about data privacy and security in AI deployments. The cornerstone of success in any data-driven initiative is strong data governance, ensuring data quality, trust, and privacy. The report also emphasized that effective data governance maximizes the value of data assets. Beyond compliance and quality control, it democratizes data access across an organization, making it essential for long-term success. This insight explores common challenges undermining Salesforce data quality and outlines how robust data governance can lead to high-quality, reliable data. Challenges to Maintaining Quality Salesforce Data Challenge 1: Data Silos Create Fragmented Customer Information Use Case: In the Consumer Packaged Goods (CPG) sector, nearly half of companies struggle to collect and integrate the massive amount of data required for AI adoption. Data fragmentation across supply chains, product categories, and SKUs creates silos, leading to inconsistent customer information. For instance, sales and marketing teams might work with different data sets, leading to disjointed customer interactions and ineffective campaigns. This results in missed sales opportunities, inefficient resource use, and poor customer experiences, ultimately weakening strategic decision-making and competitiveness. Solution: Implementing an information lifecycle management system can address data fragmentation. It provides a unified view for managing content across repositories, helping companies maintain a holistic customer view. Challenge 2: Poor Data Quality Erodes Trust Use Case: The Office of the National Coordinator for Health Information Technology found that at least 7 out of 100 medical records are mismatched or duplicated. A healthcare organization using Salesforce without proper data governance may face incomplete or inaccurate patient information, resulting in incorrect treatments and inefficient care, which damages patient trust and increases legal risks. Solution: You leverages AI to eliminate duplicate records, ensuring clean and accurate data. It classifies content based on metadata and assigns governance policies to prevent duplication, ensuring high-quality data across systems. Additionally, Backup for Salesforce tools detect suspicious anomalies or potential ransomware activity, proactively preserving data integrity. Challenge 3: Data Growth Increases Cyber Risks Use Case: As 65% of e-commerce organizations aim to become fully data-driven by 2026, increasing data volumes introduce greater risks. Without robust protection strategies, companies face potential data loss and operational disruptions. Solution: Tectonic’s solution offers automatic daily backups and on-demand restores, safeguarding data integrity and minimizing downtime in the event of cyberattacks or data breaches. Building a Strong Data Governance Foundation To overcome these challenges, organizations must adopt a comprehensive approach to data governance. Here are seven essential steps to establish effective Salesforce data governance: Champion Salesforce Data Governance with Tectonic Effective Salesforce data governance requires collaboration across all levels of the organization. With over two decades of experience, Tectonic empowers organizations to enhance their digital operations, mitigate risks, and achieve compliance in a dynamic data landscape. By establishing a strong data governance framework, your organization can confidently navigate the challenges of data growth, security, and quality. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 28, 2024in Salesforce

27Sep

Salesforce AI Evolves with the Generative AI Landscape

Salesforce AI: Powering Customer Relationship Management Salesforce is a leading CRM solution that has long delivered cutting-edge cloud technologies to manage customer relationships effectively. In recent months, the platform has further advanced with the integration of generative AI and AI-powered features, primarily through its AI engine, Einstein. Salesforce AI Evolves with the Generative AI Landscape. To explore how AI operates within the Salesforce ecosystem and how various business teams can leverage these innovations, this guide delves into Salesforce’s AI capabilities, products, and features. Salesforce AI: Transforming CRM Capabilities Salesforce remains a top choice in the CRM software market, offering one of the most comprehensive solutions for managing relationships across departments, industries, and initiatives. Through dedicated cloud platforms, Salesforce enables teams to oversee marketing, sales, customer service, e-commerce, and more, with tools focused on delivering enhanced customer experiences supported by powerful data analytics. With the introduction of generative AI, Salesforce has significantly elevated its native automation, workflow management, data analytics, and assistive capabilities for customer lifecycle management. Einstein Copilot exemplifies this innovation, aiding internal users with tasks such as outreach, analysis, and improving external user experiences. What is Salesforce Einstein? Salesforce Einstein is an AI-driven suite of tools integrated natively into various Salesforce Cloud applications, including Sales Cloud, Marketing Cloud, Service Cloud, and Commerce Cloud. It also operates through assistive technologies like Einstein Copilot. Einstein is built on a multitenant platform and incorporates numerous automated machine learning features to unify organizational data with CRM capabilities. Designed to make intelligent, data-driven decisions, Einstein requires no additional installation, offering a seamless user experience when paired with a compatible subscription plan. 7 Key Features of Salesforce Einstein 7 Applications of Salesforce Einstein Future Trends in Salesforce AI Bottom Line: Salesforce AI Evolves with the Generative AI Landscape Salesforce continues to enhance its AI-powered features, keeping pace with advancements in generative and predictive AI. Whether new to the platform or a seasoned user, Salesforce offers innovative, AI-centric solutions to streamline customer relationship management and business operations. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

September 27, 2024in AI Tools, Data, Einstein 1 Platform, Enterprise, Generative AI, Mulesoft, Salesforce, Salesforce Einstein

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