Data Access Archives - gettectonic.com

07Nov

Salesforce and Firmable

Firmable Launches Salesforce Integration to Enhance CRM Workflows Firmable has unveiled its latest integration with Salesforce, further expanding its CRM ecosystem to support over 20,000 Salesforce users across Australia. By embedding its extensive Australian dataset directly into Salesforce, Firmable empowers businesses to optimize workflows, improve productivity, and elevate their sales and marketing efforts. This integration adds to Firmable’s suite of CRM solutions, which also includes compatibility with platforms like HubSpot, making its rich dataset an integral part of daily business operations. Key Benefits of the Firmable-Salesforce Integration A Comprehensive Solution for Australian Businesses Firmable’s integration with Salesforce brings unparalleled ease of use and precision to CRM workflows. By embedding its rich Australian data into everyday tools, businesses can streamline lead generation, enhance customer engagement, and boost sales effectiveness. 🔔🔔 Follow us on LinkedIn 🔔🔔 Ready to transform your sales and marketing strategies? Firmable is now available for trial or purchase at firmable.com. 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

November 7, 2024in Data

06Nov

Types of Health Informatics

managing healthcare data is complex and resource-intensive. Health informatics addresses this challenge by merging health data with IT systems to streamline healthcare operations and analytics.

November 6, 2024in Data, Salesforce Health and Life Sciences Solutions, Technology

Cohesity Data Explore

Cohesity has introduced Data Explore, a new feature in its Gaia generative AI platform, aimed at simplifying data search within backups for any employee. The update, launched this week, adds keyword search capabilities and data visualization through topic word clouds, enhancing user access to valuable information. Previously, users could interact with Gaia’s conversational AI interface to ask questions about stored data. Data Explore now extends this by enabling users to browse frequent keywords within data sets and receive search suggestions to help refine their queries. This addition is particularly valuable for users who may not know exactly what to ask when exploring backup data. As part of the update, Gaia’s support for file storage systems has also expanded. Gaia now integrates with both on-premises and cloud-based file servers, such as Dell Technologies’ PowerScale and NetApp systems, in addition to existing support for Microsoft 365 services like Outlook, SharePoint, and OneDrive. This enhanced search functionality reflects a broader trend among backup vendors to deliver greater utility from stored data, according to Simon Robinson of TechTarget’s Enterprise Strategy Group. He noted that tools making data accessible to non-experts bring businesses closer to the goal of actionable insights. “You don’t need to be a corporate librarian to use this stuff,” Robinson said. Data Explore’s semantic indexing, similar to internet search engines, aids users by automatically surfacing keywords, questions, and suggestions, making backup data more searchable and actionable. According to Krista Case, an analyst at Futurum Group, this helps reduce AI hype by grounding Gaia in practical use cases, facilitating faster insights for end users. Since Gaia’s launch as a SaaS add-on for Cohesity Data Cloud, its features have evolved to offer deeper insights beyond simple chatbot interactions. Greg Statton, Cohesity’s VP of AI solutions, shared that the platform aims to be more than a support agent for backup queries. The vision is to provide advanced AI tools that enhance data discovery, flag abnormal events, and reduce alert fatigue, giving IT administrators actionable intelligence that is more contextually aware of their tasks. Ultimately, Cohesity’s Data Explore feature exemplifies generative AI’s potential in unlocking business value from backup data. By making this data accessible and understandable, Cohesity is helping organizations achieve the long-awaited promise of deriving value from stored data – a milestone Robinson believes backup vendors are now on the verge of realizing. 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

October 21, 2024in AI Tools, Data, Enterprise, Generative AI

17Oct

Deploying Salesforce Einstein Copilot

Best Practices for Safely Deploying Salesforce Einstein Copilot When deploying Salesforce Einstein Copilot, following best practices ensures a secure, efficient, and effective integration of AI into your workflows. Here are the key steps to safely deploy Einstein Copilot: By adhering to these best practices, you can ensure a smooth, secure, and successful deployment of Salesforce Einstein Copilot, enhancing your team’s productivity while maintaining data integrity and security. 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

October 17, 2024in Data, Salesforce, Salesforce Einstein

15Oct

Multi AI Agent Systems

Building Multi-AI Agent Systems: A Comprehensive Guide As technology advances at an unprecedented pace, Multi-AI Agent systems are emerging as a transformative approach to creating more intelligent and efficient applications. This guide delves into the significance of Multi-AI Agent systems and provides a step-by-step tutorial on building them using advanced frameworks like LlamaIndex and CrewAI. What Are Multi-AI Agent Systems? Multi-AI Agent systems are a groundbreaking development in artificial intelligence. Unlike single AI agents that operate independently, these systems consist of multiple autonomous agents that collaborate to tackle complex tasks or solve intricate problems. Key Features of Multi-AI Agent Systems: Applications of Multi-AI Agent Systems: Multi-agent systems are versatile and impactful across industries, including: The Workflow of a Multi-AI Agent System Building an effective Multi-AI Agent system requires a structured approach. Here’s how it works: Building Multi-AI Agent Systems with LlamaIndex and CrewAI Step 1: Define Agent Roles Clearly define the roles, goals, and specializations of each agent. For example: Step 2: Initiate the Workflow Establish a seamless workflow for agents to perform their tasks: Step 3: Leverage CrewAI for Collaboration CrewAI enhances collaboration by enabling autonomous agents to work together effectively: Step 4: Integrate LlamaIndex for Data Handling Efficient data management is crucial for agent performance: Understanding AI Inference and Training Multi-AI Agent systems rely on both AI inference and training: Key Differences: Aspect AI Training AI Inference Purpose Builds the model. Uses the model for tasks. Process Data-driven learning. Real-time decision-making. Compute Needs Resource-intensive. Optimized for efficiency. Both processes are essential: training builds the agents’ capabilities, while inference ensures swift, actionable results. Tools for Multi-AI Agent Systems LlamaIndex An advanced framework for efficient data handling: CrewAI A collaborative platform for building autonomous agents: Practical Example: Multi-AI Agent Workflow Conclusion Building Multi-AI Agent systems offers unparalleled opportunities to create intelligent, responsive, and efficient applications. By defining clear agent roles, leveraging tools like CrewAI and LlamaIndex, and integrating robust workflows, developers can unlock the full potential of these systems. As industries continue to embrace this technology, Multi-AI Agent systems are set to revolutionize how we approach problem-solving and task execution. 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 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 Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

October 15, 2024in Artificial Intelligence, Data, Technology

11Oct

Transforming Business with Agentforce Agents

Agents are autonomous software systems that assist users by reasoning, planning, and taking actions based on user input or environmental conditions. These digital assistants combine expert knowledge with access to relevant data to achieve specific tasks or goals, resembling intelligent digital assistants in their function and scope. Agents are poised to become integral to everyday life, reshaping how businesses operate and engage with customers. For instance, a service agent can act as a company’s most knowledgeable support representative, available around the clock. A marketing agent, similar to a self-driving car, can respond to real-time business conditions by proactively adjusting pricing or launching campaigns. This article explores the AI advancements driving the rise of agents and how these systems are transforming businesses while revolutionizing software development. Powered by Large Language Models (LLMs) Agents are powered by large language models (LLMs), which provide two key capabilities: However, LLMs alone have limitations, including: A New Software Paradigm Agents bridge the gap between the language capabilities of LLMs and the practical needs of businesses, introducing a new approach to software. Instead of building full-fledged applications, companies can develop granular building blocks of functionality, referred to as actions, which can be orchestrated by agents. In Salesforce, these actions (such as “Locate Order” or “Change Order Address”) are grouped under functional areas known as topics (e.g., “Order Management”). An agent operates by: The Ultimate Application Composition Platform This new paradigm allows agents to handle requests that weren’t anticipated in advance, solving problems on the fly by composing actions in novel ways. For example, Salesforce’s Agentforce agents can access a wide range of actions across Sales Cloud, Service Cloud, Marketing Cloud, Commerce Cloud, and more. Developers can further extend the agents’ capabilities with custom actions built via code, APIs, or prompt templates. Agents gain essential capabilities through actions, including: Levels of Autonomy Agents can operate at varying levels of autonomy: Regardless of their autonomy, establishing guardrails is essential for maintaining reliability, security, and business practices. Agentforce uses a multi-layered approach to enforce these guardrails, including the Einstein Trust Layer, which secures LLM interactions, and Agentforce Analytics, which provides insights into performance and reliability. Ready-to-Use Agents for Sales and Service Salesforce has introduced prebuilt agents, including: Creating and Customizing Agents with Agentforce Salesforce’s Agentforce empowers users to create, customize, and deploy agents that combine AI, data, and actions. Key components of this platform include: Conclusion: Transforming Business with Agentforce Agents Agents are becoming pervasive, changing how businesses operate by enabling systems to reason, take action, and provide personalized experiences. Agentforce Agents lead this transformation by being: As businesses evolve, Agentforce Agents are at the forefront of creating a more efficient, intelligent future. 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

October 11, 2024in Data, Enterprise, Salesforce

10Oct

Managing Salesforce Roles and Profiles

How to Set Up Salesforce Roles Salesforce is a powerful platform used by many organizations to streamline operations across departments, from sales and marketing to customer support. With so many users working within the platform, it’s essential to manage access to data securely. Salesforce achieves this through its system of roles and profiles, which define who can see and do what in the system. Salesforce Roles vs. Profiles Roles determine what data users can view. They establish a hierarchy of access, with higher roles having visibility into records owned by those below them. This helps ensure that only authorized users can access sensitive information. Profiles, on the other hand, define what actions users can take within Salesforce, such as creating or editing records. Profiles are assigned when user accounts are created and can be customized to suit specific job functions. Role Hierarchy in Salesforce The role hierarchy in Salesforce is designed to control data access, not mirror the organizational chart. Higher roles can generally view data from roles below them, but access can be restricted based on business needs. Types of Salesforce Profiles Salesforce comes with several standard profiles, and administrators can create custom profiles as needed. Some key profiles include: In addition to profiles, permission sets allow admins to grant users specific permissions without changing their profile. Managing Salesforce Roles and Profiles Setting up Salesforce roles and profiles is crucial for maintaining data security and ensuring users have the correct access for their responsibilities. By efficiently configuring roles and profiles, businesses can tailor the platform to their needs, enhancing both user experience and operational security. 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

October 10, 2024in Salesforce

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

October 7, 2024in Salesforce Data 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 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

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

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 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

October 1, 2024in Data, Enterprise, Salesforce

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 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 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 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 Salesforce

27Sep

Salesforce Einstein Copilot Security

Salesforce Einstein Copilot Security: How It Works and Key Risks to Mitigate for a Safe Rollout With the official rollout of Salesforce Einstein Copilot, this conversational AI assistant is set to transform how sales, marketing, and customer service teams interact with both customers and internal documentation. Einstein Copilot understands natural language queries, streamlining daily tasks such as answering questions, generating insights, and performing actions across Salesforce to boost productivity. Salesforce Einstein Copilot Security However, alongside the productivity gains, it’s essential to address potential risks and ensure a secure implementation. This Tectonic insight covers: Einstein Copilot Use Cases Einstein Copilot enables users to: All of these actions can be performed with simple, natural language prompts, improving efficiency and outcomes. How Einstein Copilot Works Here’s a simplified breakdown of how Einstein Copilot processes prompts: The Einstein Trust Layer Salesforce has built the Einstein Trust Layer to ensure customer data is secure. Customer data processed by Einstein Copilot is encrypted, and no data is retained on the backend. Sensitive data, such as PII (Personally Identifiable Information), PCI (Payment Card Information), and PHI (Protected Health Information), is masked to ensure privacy. Additionally, the Trust Layer reduces biased, toxic, and unethical outputs by leveraging toxic language detection. Importantly, Salesforce guarantees that customer data will not be used to train the AI models behind Einstein Copilot or be shared with third parties. The Shared Responsibility Model Salesforce’s security approach is based on a shared responsibility model: This collaborative model ensures a higher level of security and trust between Salesforce and its customers. Best Practices for Securing Einstein Copilot Rollout Prepare Your Salesforce Org for Einstein Copilot To ensure a smooth rollout, it’s critical to assess your Salesforce security posture and ready your data. Tools like Salesforce Shield can help organizations by: By following these steps, you can utilize the power of Einstein Copilot while ensuring the security and integrity of your data. 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

September 27, 2024in Data, Enterprise, Salesforce, Salesforce Data Cloud, Salesforce Einstein

22Sep

How to Achieve AI Democratization

AI democratization empowers non-experts by placing AI tools in the hands of everyday users, enabling them to harness the technology’s potential without requiring specialized technical skills. Today, IT leaders are increasingly focused on expanding AI’s benefits across the enterprise. The growing number of AI-based tools is making this more achievable. In some respects, democratization extends the concept of low- and no-code development—allowing non-developers to create software—into the realm of AI. However, it’s also about ensuring data is accessible and fostering data literacy throughout the organization. This doesn’t mean every employee needs to write machine learning scripts. Instead, it means business professionals should understand AI’s potential, identify relevant use cases, and apply insights to drive business outcomes. Achieving AI democratization is feasible, thanks to decentralized governance models and the emergence of AI-focused services. However, as with any new technology, democratization brings both benefits and challenges. How to Achieve AI Democratization AI is no longer reserved for experts. Tools like Google Colab and Microsoft’s Azure OpenAI Service have simplified AI development, enabling more employees to participate by writing and sharing code for various projects. To maximize the impact, enterprises must train business users on the basics of AI and how it can enhance their daily work. According to Arpit Mehra, Practice Director at Everest Group, decentralized governance models can help organizations build strategies for data and technology learning. Key strategies include: Arun Chandrasekaran, VP and Analyst at Gartner, also advises companies to focus on intelligent applications in areas such as customer engagement and talent acquisition, which can provide specialized training. Benefits and Challenges of AI Democratization AI democratization can significantly expand an organization’s capabilities. By placing AI in the hands of more employees, businesses reduce barriers to adoption, cut costs, and create highly accurate AI models. “Making AI more accessible broadens the scope of what businesses can achieve,” said Michael Shehab, PwC U.S. Technology and Innovation Leader. AI democratization also helps companies address IT talent shortages by upskilling employees and enabling them to integrate AI into their workflows. This approach improves productivity, allowing businesses to more easily spot trends and patterns within large data sets. However, challenges also arise. If AI is implemented without proper oversight, the technology is susceptible to bias. Poor training could lead to decision-making based on inaccurate or skewed data. Business leaders must ensure they understand who is using AI tools and establish standards for responsible use. Without careful testing, AI applications can automate mistakes that go unnoticed but may cause significant issues. Ed Murphy, SVP and Head of Data Science at 1010data, emphasizes the importance of testing to prevent these errors. To mitigate risks, organizations should invest in upskilling and reskilling employees. A well-defined training plan will enable nontechnical teams to participate in AI adoption and deployment effectively. Mehra from Everest Group also suggests exploring MLOps technologies to simplify AI development and streamline processes. Ultimately, AI democratization will benefit businesses that recognize AI’s potential beyond a small group of experts. While the benefits are clear, organizations must remain vigilant about the risks to ensure successful AI integration and reap the rewards of their efforts. 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

September 22, 2024in Salesforce

22Sep

Tableau Einstein is Here

Tableau Einstein marks a new chapter for Tableau, transforming the analytics experience by moving beyond traditional reports and dashboards to deliver insights directly within the flow of a user’s work. This new AI-powered analytics platform blends existing Tableau and Salesforce capabilities with innovative features designed to revolutionize how users engage with data. The platform is built around four key areas: autonomous insight delivery through AI, AI-assisted development of a semantic layer, real-time data access, and a marketplace for data and AI products, allowing customers to personalize their Tableau experience. Some features, like Tableau Pulse and Tableau Agent, which provide autonomous insights, are already available. Additional tools, such as Tableau Semantics and a marketplace for AI products, are expected to launch in 2025. Access to Tableau Einstein is provided through a Tableau+ subscription, though pricing details remain private. Since being acquired by Salesforce in 2019, Tableau has shifted its focus toward AI, following the trend of many analytics vendors. In February, Tableau introduced Tableau Pulse, a generative AI-powered tool that delivers insights in natural language. In July, it also rolled out Tableau Agent, an AI assistant to help users prepare and analyze data. With AI at its core, Tableau Einstein reflects deeper integration between Tableau and Salesforce. David Menninger, an analyst at Ventana Research, commented that these new capabilities represent a meaningful step toward true integration between the two platforms. Donald Farmer, founder of TreeHive Strategy, agrees, highlighting that while the robustness of Tableau Einstein’s AI capabilities compared to its competitors remains to be seen, the platform offers more than just incremental add-ons. “It’s an impressive release,” he remarked. A Paradigm Shift in Analytics A significant aspect of Tableau Einstein is its agentic nature, where AI-powered agents deliver insights autonomously, without user prompts. Traditionally, users queried data and analyzed reports to derive insights. Tableau Einstein changes this model by proactively providing insights within the workflow, eliminating the need for users to formulate specific queries. The concept of autonomous insights, represented by tools like Tableau Pulse and Agentforce for Tableau, allows businesses to build autonomous agents that deliver actionable data. This aligns with the broader trend in analytics, where the market is shifting toward agentic AI and away from dashboard reliance. Menninger noted, “The market is moving toward agentic AI and analytics, where agents, not dashboards, drive decisions. Agents can act on data rather than waiting for users to interpret it.” Farmer echoed this sentiment, stating that the integration of AI within Tableau is intuitive and seamless, offering a significantly improved analytics experience. He specifically pointed out Tableau Pulse’s elegant design and the integration of Agentforce AI, which feels deeply integrated rather than a superficial add-on. Core Features and Capabilities One of the most anticipated features of Tableau Einstein is Tableau Semantics, a semantic layer designed to enhance AI models by enabling organizations to define and structure their data consistently. Expected to be generally available by February 2025, Tableau Semantics will allow enterprises to manage metrics, data dimensions, and relationships across datasets with the help of AI. Pre-built metrics for Salesforce data will also be available, along with AI-driven tools to simplify semantic layer management. Tableau is not the first to offer a semantic layer—vendors like MicroStrategy and Looker have similar features—but the infusion of AI sets Tableau’s approach apart. According to Tableau’s chief product officer, Southard Jones, AI makes Tableau’s semantic layer more agile and user-friendly compared to older, labor-intensive systems. Real-time data integration is another key component of Tableau Einstein, made possible through Salesforce’s Data Cloud. This integration enables Tableau users to securely access and combine structured and unstructured data from hundreds of sources without manual intervention. Unstructured data, such as text and images, is critical for comprehensive AI training, and Data Cloud allows enterprises to use it alongside structured data efficiently. Additionally, Tableau Einstein will feature a marketplace launching in mid-2025, which will allow users to build a composable infrastructure. Through APIs, users will be able to personalize their Tableau environment, share AI assets, and collaborate across departments more effectively. Looking Forward As Tableau continues to build on its AI-driven platform, Menninger and Farmer agree that the vendor’s move toward agentic AI is a smart evolution. While Tableau’s current capabilities are competitive, Menninger noted that the platform doesn’t necessarily set Tableau apart from competitors like Qlik, MicroStrategy, or Microsoft Fabric. However, the tight integration with Salesforce and the focus on agentic AI may provide Tableau with a short-term advantage in the fast-changing analytics landscape. Farmer added that Tableau Einstein’s autonomous insight generation feels like a significant leap forward for the platform. “Tableau has done great work in creating an agentic experience that feels, for the first time, like the real deal,” he said. Looking ahead, Tableau’s roadmap includes a continued focus on agentic AI, with the goal of providing each user with their own personal analyst. “It’s not just about productivity,” said Jones. “It’s about changing the value of what can be delivered.” Menninger concluded that Tableau’s shift away from dashboards is a reflection of where business intelligence is headed. “Dashboards, like data warehouses, don’t solve problems on their own. What matters is what you do with the information,” he said. “Tableau’s push toward agentic analytics and collaborative decision-making is the right move for its users and the market as a whole.” 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

September 22, 2024in Data, Enterprise, Generative AI, Salesforce

Data Access

Salesforce and Firmable

Deploying Salesforce Einstein Copilot

Multi AI Agent Systems

Managing Salesforce Roles and Profiles

How to Achieve AI Democratization

Recent Posts

Native Salesforce App to Simplify Event Management

Generative AI in CX

From Generative AI to Agentic AI

Python-Based Reasoning

Salesforce Foundations

Contact Us

Be in touch today — and start your business on a path to success.

Category

Archives