11Nov
AI Readiness in Salesforce
This new capability simplifies data management, empowering teams to focus on deriving insights rather than wrestling with data silos.
11Nov
Healthcare Can Prioritize AI Governance
As artificial intelligence gains momentum in healthcare, it’s critical for health systems and related stakeholders to develop robust AI governance programs. AI’s potential to address challenges in administration, operations, and clinical care is drawing interest across the sector. As this technology evolves, the range of applications in healthcare will only broaden.
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.
05Nov
Cybersecurity Regulations for Hospitals
Beyond the 72-hour reporting requirement, which took effect on October 2, 2024, hospitals must implement key cybersecurity measures, such as multifactor authentication and a robust incident response plan, by October 2025. These regulations currently apply only to general hospitals, excluding other healthcare facilities like nursing homes and diagnostic centers.
01Nov
Salesforce Data Cloud One
Salesforce’s new Data Cloud One is designed to extend cloud capabilities by allowing multiple departments—or orgs—to collaborate seamlessly on shared data. With Data Cloud One, each department maintains its own CRM and analytics interface, tailored to its specific needs, while accessing a unified database that serves as the single source of truth. The automated exchange of metadata between departments enables efficient, low-code linking and integration. Also within Data Cloud One, multiple Salesforce orgs can be connected and communicate. As your company grows, your business needs grow as well. You might create different Salesforce orgs for different departments, regions, or brands, or inherit them as part of an acquisition. And data about the same customer can end up stored in multiple orgs. It’s great to have all that data, but it’s more valuable if every part of your business can access a single view of each customer. Standard Salesforce CRM connections let you ingest data from many orgs into Data Cloud where it’s unified in the Data Cloud home org. The home org is the primary org where Data Cloud is provisioned and managed. But connected orgs can’t directly access unified data. To make use of unified data in connected orgs, you have to rely on data actions to trigger flows in connected orgs based on the Data Cloud data, or set up complicated custom-coded solutions. Or you have to provision, set up, and maintain a Data Cloud on every org. At the heart of Cloud One is the Home Org, where all data consolidates, and logical units are grouped into Data Spaces. Through automated metadata sharing, other departments (companion orgs) can directly access approved functions within their Cloud One application, creating a standardized network for CRM, data management, analytics, and security. New AI-powered features are also integrated. Role of Salesforce Data Cloud Data Cloud One makes accessing a single Data Cloud across multiple orgs a snap. Orgs connected through a Data Cloud One companion connection are called companion orgs. On top of ingesting data through a standard connection, users in companion orgs also have access to a subset of Data Cloud functionality in the Data Cloud One app. Companion org users can see a complete view of their customers from unified profiles, build custom flows on unified data, directly access calculated insights, and optimize business processes for their use case by powering CRM platform features with Data Cloud. Salesforce Data Cloud One When users set up Data Cloud One, they see a list of Data Spaces available to them. Once authenticated, they gain access to details on shared data, as well as analysis and CRM functionalities. Each user automatically receives three Companion Connections, included in the Salesforce Cloud package, with options to add more as needed. Data Cloud One Architecture In the past, each department worked with its own data set, configurations, users, and security protocols, making inter-departmental data sharing time-consuming and requiring custom code. Data Cloud One simplifies this by allowing companion orgs to connect through a streamlined, automated system, enabling smoother collaboration across departments. Benefits of Data Cloud One When connecting an org to Data Cloud, you can choose between a standard connection and a Data Cloud One companion connection. Let’s compare the access of orgs with each connection. Access Orgs with a Standard Connection Orgs with a Data Cloud One Companion Connection Access to Data Cloud data None Access to Data Cloud metadata, objects, and records in shared data spaces. Data spaces are logical partitions of data within Data Cloud. You can invest in enhanced data security by using Data Cloud data spaces to organize and govern shared data. Access to Data Cloud features None Access to some Data Cloud features in the Data Cloud One app, such as calculated insights and Data Explorer.Access to platform features powered by Data Cloud, such as Flows. Benefits of Data Cloud One Multi-org users of Data Cloud have long sought an easy way to access a unified Customer 360 and take action across multiple orgs. Now, with the general availability of Data Cloud One, that capability has arrived! Data Cloud One equips multiple orgs with a centralized customer profile and Data Cloud-powered features, all accessed through a single, central Data Cloud. This new tool simplifies the onboarding of multi-org teams, transforming how they collaborate within Data Cloud. A Unified Approach to Data Cloud for Multiple Orgs — with Low-Code Configuration So, what is Data Cloud One? It’s a much-anticipated feature designed to enhance multi-org functionality by connecting an entire organization through a single, centralized Data Cloud that serves as the ultimate source of truth. Here’s what Data Cloud One brings to the table: With Data Cloud One, multi-org teams can quickly and seamlessly adopt a comprehensive, shared customer view and Data Cloud-driven capabilities across departments, revolutionizing collaboration and data access. The quest to be data-driven will quickly become the quest to become Data-Cloud driven, and Tectonic is here to help. 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
30Oct
Intelligent Adoption Framework
Intelligent Adoption Framework Marks a New Era for AI IntegrationAfter a surge of initial excitement, AI has now entered a phase of more thoughtful and strategic adoption, focusing on sustainable progress and measurable results. Following years of hype in which artificial intelligence was hailed as a revolutionary force poised to instantly transform industries, AI is now facing a more tempered reality. As it settles into Gartner’s “Trough of Disillusionment,” organizations are grappling with the reality of high costs and challenges scaling experimental projects. However, this phase of learning is typical for any emerging technology, and the journey to unlock AI’s full potential is far from over. Steve Daly, Senior Vice President of Solutions at New Era Technology, explains: “AI has been around for 70 years, but the recent hype inflated expectations. At $30 per user per month for tools like Microsoft 365 Copilot, they’re appealing for proof-of-concept projects. But once those initial tests are over, many companies struggle to find a clear ROI when scaling.” Cost is not the only barrier to broader AI adoption. Concerns over data security and sharing sensitive information are top priorities for many organizations. Daly adds, “New Era’s robust data and security practice has shifted to offer Copilot Studio, allowing companies to build GenAI solutions with tighter security controls. With Copilot Studio, you can limit access to specific files or libraries, ensuring greater control over sensitive data.” Moving Beyond OverpromisesBuilding confidence in AI requires addressing several factors. First, organizations must tackle security and data control issues, alongside developing a clear business model to justify AI investments. Equally important is maintaining momentum—patience and persistence are key to seeing projects through to success, or determining when to pivot. Daly observes, “We’re seeing many projects lose steam. Around half of AI initiatives stall due to poor security practices and suboptimal data management. Projects must demonstrate progress, and that’s difficult in the innovation phase when you don’t always know what you don’t know.” Introducing Intelligent AdoptionThis is where Copilot Studio and New Era’s Intelligent Adoption Framework come into play. The framework is designed to help organizations chart their AI development journey and ensure investments yield tangible results. Copilot Studio supports IT teams by focusing on the tasks that truly drive value, helping them stay on track toward their goals. The Intelligent Adoption Framework is built around three core pillars: technical redesign, organizational readiness, and user readiness. New Era’s framework leverages its expertise to guide businesses through the steps necessary to define their AI strategy, align their corporate vision, and identify the most valuable use cases for AI adoption. Daly concludes, “It’s not just about purchasing licenses—it’s about creating a roadmap for successful adoption. We’re developing packaged solutions, such as ‘train the trainer’ programs from day one, followed by proof-of-concept demonstrations using Copilot Studio. Our goal is to help customers answer key questions, like when to build a GenAI chatbot, while navigating the complexities of AI adoption and managing the pressures CIOs face from stakeholders.” In this new era of AI, success will be determined not by rushed deployment, but by strategic, intelligent adoption that ensures sustained value over 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 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
28Oct
Salesforce Connected Assets
Salesforce has unveiled Connected Assets, a robust suite of capabilities in Manufacturing Cloud, designed to offer manufacturers a comprehensive, real-time perspective on connected asset data. This includes data on service history, asset status, customer records, and telematics, allowing manufacturers to monitor asset health and performance while proactively addressing maintenance needs to reduce downtime and boost customer satisfaction. Enhanced AI Capabilities for Connected AssetsConnected Assets integrates Salesforce’s advanced AI to empower teams with actionable insights. Sales, customer service, and field teams can now receive real-time alerts and quickly access asset history and health, enabling faster, data-driven support and the delivery of more personalized offers. AI-driven insights and recommendations based on asset condition, service history, and performance data enhance the ability of manufacturers to predict maintenance needs and provide proactive support, including on-site recommendations to field technicians. Innovative Features for Optimized Asset Management Salesforce PerspectiveAchyut Jajoo, SVP and GM of Manufacturing and Automotive, states, “The manufacturing industry is embracing a historic transformation toward AI-enabled modernization. Connected Assets and our sector-specific AI tools in Manufacturing Cloud empower our customers to lead with improved customer experiences, optimized asset performance, and new revenue-generating services. With Agentforce, our customers will soon be able to leverage autonomous agents to monitor connected asset data at scale, enabling them to focus on strategic, high-value initiatives.” Real-World ApplicationKawasaki Engines exemplifies Connected Assets in action, using Manufacturing Cloud to enhance customer relationships by offering proactive support and minimizing equipment downtime. “Salesforce’s Connected Assets will enable us to deliver exceptional service, keeping our customers satisfied and our products operating efficiently,” says Tony Gondick, Senior Manager of IT Business Strategy at Kawasaki Engines. Extending Across IndustriesBeyond Manufacturing Cloud, Connected Assets is also being introduced to Salesforce’s other industry clouds, such as Energy & Utilities, Communications, and Media, allowing a wide range of sectors to tap into the benefits of connected asset management, minimize downtime, and generate new value. 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
28Oct
Necessary Salesforce Admin Skills
In 2023, Salesforce Admins created 230,000 objects, generated over 2.7 billion reports monthly, and performed 1 trillion AI predictions weekly. These figures highlight the critical role of an Admin in the Salesforce ecosystem. However, becoming an expert Salesforce Admin requires more than just technical know-how. A blend of both technical and soft skills is essential to truly excel in this role. Whether you’re new to the role or looking to enhance your skills, learning the right abilities is key to thriving as a Salesforce Admin. In this guide, we’ll cover the essential Salesforce Admin skills you need to effectively manage the platform and drive business success. Key Takeaways 14 Essential Salesforce Admin Skills to Master These are some of the key skills outlined in Salesforce’s “Admin Skills Kit” that will help you secure top Salesforce Admin positions. 1. Communication Strong communication skills are critical for Salesforce Admins, who act as the link between technical teams, stakeholders, and users. You’ll need to explain complex processes clearly so that all parties can understand. Why It Matters: Clear communication ensures users can effectively engage with the platform and make informed decisions based on Salesforce data. How To Improve: Practice simplifying technical concepts, actively listen to others’ needs, and refine your ability to convey information clearly. 2. Problem Solving Challenges will arise in your role, from system errors to user issues. Having strong problem-solving skills allows you to identify the root cause of issues and quickly implement effective solutions. Why It Matters: Efficient problem resolution minimizes downtime and keeps the Salesforce platform running smoothly. How To Improve: Break down problems into manageable parts, brainstorm solutions, and always evaluate the impact of your decisions. 3. Attention to Detail Salesforce admins deal with complex data and processes that require accuracy. From maintaining data integrity to configuring processes, attention to detail is crucial. Why It Matters: Even small errors can result in inaccurate data, security risks, or inefficient processes. How To Improve: Double-check your work, use Salesforce validation tools, and ensure all workflows are correctly configured before launching. 4. Learner’s Mindset Salesforce evolves constantly, with frequent updates and new features. A learner’s mindset helps you stay on top of these changes and continuously improve your skills. Why It Matters: The more you know, the more value you bring. Keeping up with updates ensures you’re using the latest tools to benefit your organization. How To Improve: Engage with Salesforce communities, complete Trailhead modules, and attend webinars to stay current. 5. User Management As an Admin, you’ll be responsible for managing users, creating profiles, setting roles and permissions, and ensuring proper access to data. Why It Matters: Proper user management boosts productivity while ensuring data security. How To Improve: Learn the ins and outs of Salesforce profiles, roles, and permission sets, and practice managing users in a sandbox environment. 6. Security Management In today’s digital age, data security is a top priority. Salesforce Admins are responsible for safeguarding organizational data from unauthorized access or breaches. Why It Matters: Poor security can lead to data leaks, damaging the company’s reputation and finances. How To Improve: Master security settings, understand field-level permissions, and stay informed on two-step verification and audit tracking. 7. Business Analysis Admins need to understand the business needs of their organization. Business analysis skills help you gather requirements, understand workflows, and tailor Salesforce to meet those needs. Why It Matters: The better you understand the business, the more effectively you can customize Salesforce to add value. How To Improve: Collaborate with stakeholders to identify pain points and design solutions that address specific business needs. 8. Data Analysis Working with large data sets is a regular part of being a Salesforce Admin. Knowing how to analyze data and generate insights is essential. Why It Matters: Data analysis drives informed decision-making, streamlines workflows, and improves communication. How To Improve: Familiarize yourself with Salesforce’s reporting tools, dashboards, and data export features. 9. Data Management Effective data management is critical to maintaining a well-functioning Salesforce system. This involves data transfers, cleaning, deduplication, and archiving. Why It Matters: Clean and organized data supports accurate reporting and better decision-making. How To Improve: Learn best practices for data imports, validation rules, and data maintenance tools like Data Loader. 10. Designer’s Mindset Admins with a designer’s mindset can create user-friendly interfaces and workflows that enhance the system’s usability. Why It Matters: A well-designed interface improves the user experience, making work more efficient and enjoyable. How To Improve: Use the Lightning App Builder to create custom page layouts and optimize user flows. 11. Change Management When implementing new processes or updates, effective change management is key. This includes communication, ensuring smooth transitions, and training users on new features. Why It Matters: Proper change management ensures high adoption rates and a smooth transition to new features or updates. How To Improve: Develop communication plans, conduct training, and gather user feedback during transitions. 12. Process Automation Salesforce’s automation capabilities allow admins to streamline repetitive tasks. Automation skills help you create workflows, approval processes, and automated communications. Why It Matters: Automating repetitive tasks saves time and ensures that critical business processes are followed consistently. How To Improve: Learn how to use Flows, Process Builder, and Workflow Rules to automate business operations. 13. Product Management A product management mindset helps Admins align the platform with users’ and stakeholders’ needs, ensuring Salesforce delivers value to the organization. Why It Matters: Meeting evolving business needs ensures you continue to add value as an Admin. How To Improve: Collect user feedback, prioritize requests, and align updates with overall business goals. 14. Project Management Salesforce Admins often lead projects such as implementing new features or migrating data. Strong project management skills are essential to execute these tasks effectively. Why It Matters: Good project management ensures that goals are met on time and within budget. How To Improve: Get comfortable with project management tools, scheduling, resource management, and stakeholder communication. Conclusion The role of a Salesforce Admin combines both technical and soft skills like communication,
27Oct
Aura Components and Salesforce Development
Aura Components have transformed the way developers design user interfaces in Salesforce.
25Oct
Transform Customer Experience
In today’s AI-driven business environment, customer experience (CX) has evolved from being a buzzword to a critical factor in determining success. It’s no longer enough for businesses to offer high-quality products or excellent service alone—today’s customers are always online, engaged, and seeking the most convenient, relevant, and enjoyable experiences. This is where Salesforce Data Cloud becomes a game-changer, providing the tools needed to meet modern customer expectations. Transforming Customer Experience with Salesforce Data Cloud Salesforce enables businesses to collect, integrate, and leverage critical customer information within its ecosystem, offering an all-encompassing view of each customer. This unified customer data allows organizations to forecast visitor trends, assess marketing impact, and predict customer behavior. As data-driven decision-making becomes increasingly central to business strategy, Salesforce Data Cloud and its Customer Data Platform (CDP) features provide a significant competitive edge—whether in e-commerce, fintech, or B2B industries. Data Cloud is more than just your traditional CDP. It’s the only data platform native to the world‘s #1 AI CRM. This means that marketers can quickly access and easily action on unified data – from across the entire business – to drive growth and increase customer lifetime value. Data Cloud’s Role in Enhancing CX By unifying data in one place, Salesforce Data Cloud enables organizations to access real-time customer insights. This empowers them to track customer activity across channels like email, social media, and online sales, facilitating targeted marketing strategies. Businesses can analyze customer behavior and deliver personalized messaging, aligning marketing, sales, and customer service efforts to ensure consistency. With these capabilities, Salesforce customers can elevate the CX by delivering the right content, at the right time, to the right audience, ultimately driving customer satisfaction and growth. New Features of Salesforce Data Cloud Salesforce continues to evolve, introducing cutting-edge features that reshape customer interaction: To fully maximize these features, partnering with a Salesforce Data Cloud consultant can help businesses unlock the platform’s full potential and refine their customer engagement strategies. Agentic AI Set to Supercharge Business Processes Salesforce’s vision extends beyond customer relationship management with the integration of Agentic AI through its Customer 360 platform. According to theCUBE Research analysts, this signals a shift toward using AI agents to automate complex business processes. These AI agents, built on Salesforce’s vast data resources, promise to revolutionize how companies operate, offering customized, AI-driven business tools. “If they can pull this off, where it becomes a more dynamic app platform, more personalized, really focused on those processes all the way back to the data, it’s going to be a clear win for them,” said Strechay. “They’re sitting on cloud; they’re sitting on IaaS. That’s a huge win from that perspective.” AI agents create a network of microservices that think and act independently, involving human intervention only when necessary. This division of labor allows businesses to capture expertise in routine tasks while freeing human workers to focus on more complex decision-making. However, the success of these AI agents depends on access to accurate and reliable data. As Gilbert explained, “Agents can call on other agents, and when they’re not confident of a step in a process or an outcome, they can then bounce up to an inbox for a human to supervise.” The goal isn’t to eliminate humans but to capture their expertise for simpler processes. Empowering Developers and Citizen Creators At the core of this AI-driven transformation is Salesforce’s focus on developers. The platform’s low-code tools allow businesses to easily customize AI agents and automate business processes, empowering both experienced developers and citizen creators. With simple language commands or goal-setting, companies can build and train these AI agents, streamlining operations. “It’s always going to be about good data—that’s the constant,” Bertrand said. “The second challenge is how to train agents and humans to work together effectively. While some entry-level jobs may be replaced, AI will continue to evolve, creating new opportunities in the future.” Is Salesforce Data Cloud the Right Fit for Your Business? Salesforce Data Cloud offers comprehensive capabilities for businesses of all sizes, but it’s essential to assess whether it aligns with your specific needs. The platform is particularly valuable for: For businesses that fit these scenarios, working with Salesforce’s partner ecosystem or a Data Cloud consultant can help ensure successful integration and optimization. What’s New in Salesforce’s Latest Release? The latest Salesforce Spring Release introduced several exciting features, further enhancing Salesforce Data Cloud: These updates reflect Salesforce’s commitment to providing innovative, data-driven solutions that enhance customer experiences and drive business success. 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
23Oct
Scaling Generative AI
Many organizations follow a hybrid approach to AI infrastructure, combining public clouds, colocation facilities, and on-prem solutions. Specialized GPU-as-a-service vendors, for instance, are becoming popular for handling high-demand AI computations, helping businesses manage costs without compromising performance. Business process outsourcing company TaskUs, for example, focuses on optimizing compute and data flows as it scales its gen AI deployments, while Cognizant advises that companies distinguish between training and inference needs, each with different latency requirements.
23Oct
Ready for AI Agents
Brands that can effectively integrate agentic AI into their operations stand to gain a significant competitive edge. But as with any innovation, success will depend on balancing the promise of automation with the complexities of trust, privacy, and user experience.
18Oct
Recent advancements in AI
Recent advancements in AI have been propelled by large language models (LLMs) containing billions to trillions of parameters. Parameters—variables used to train and fine-tune machine learning models—have played a key role in the development of generative AI. As the number of parameters grows, models like ChatGPT can generate human-like content that was unimaginable just a few years ago. Parameters are sometimes referred to as “features” or “feature counts.” While it’s tempting to equate the power of AI models with their parameter count, similar to how we think of horsepower in cars, more parameters aren’t always better. An increase in parameters can lead to additional computational overhead and even problems like overfitting. There are various ways to increase the number of parameters in AI models, but not all approaches yield the same improvements. For example, Google’s Switch Transformers scaled to trillions of parameters, but some of their smaller models outperformed them in certain use cases. Thus, other metrics should be considered when evaluating AI models. The exact relationship between parameter count and intelligence is still debated. John Blankenbaker, principal data scientist at SSA & Company, notes that larger models tend to replicate their training data more accurately, but the belief that more parameters inherently lead to greater intelligence is often wishful thinking. He points out that while these models may sound knowledgeable, they don’t actually possess true understanding. One challenge is the misunderstanding of what a parameter is. It’s not a word, feature, or unit of data but rather a component within the model‘s computation. Each parameter adjusts how the model processes inputs, much like turning a knob in a complex machine. In contrast to parameters in simpler models like linear regression, which have a clear interpretation, parameters in LLMs are opaque and offer no insight on their own. Christine Livingston, managing director at Protiviti, explains that parameters act as weights that allow flexibility in the model. However, more parameters can lead to overfitting, where the model performs well on training data but struggles with new information. Adnan Masood, chief AI architect at UST, highlights that parameters influence precision, accuracy, and data management needs. However, due to the size of LLMs, it’s impractical to focus on individual parameters. Instead, developers assess models based on their intended purpose, performance metrics, and ethical considerations. Understanding the data sources and pre-processing steps becomes critical in evaluating the model’s transparency. It’s important to differentiate between parameters, tokens, and words. A parameter is not a word; rather, it’s a value learned during training. Tokens are fragments of words, and LLMs are trained on these tokens, which are transformed into embeddings used by the model. The number of parameters influences a model’s complexity and capacity to learn. More parameters often lead to better performance, but they also increase computational demands. Larger models can be harder to train and operate, leading to slower response times and higher costs. In some cases, smaller models are preferred for domain-specific tasks because they generalize better and are easier to fine-tune. Transformer-based models like GPT-4 dwarf previous generations in parameter count. However, for edge-based applications where resources are limited, smaller models are preferred as they are more adaptable and efficient. Fine-tuning large models for specific domains remains a challenge, often requiring extensive oversight to avoid problems like overfitting. There is also growing recognition that parameter count alone is not the best way to measure a model’s performance. Alternatives like Stanford’s HELM and benchmarks such as GLUE and SuperGLUE assess models across multiple factors, including fairness, efficiency, and bias. Three trends are shaping how we think about parameters. First, AI developers are improving model performance without necessarily increasing parameters. A study of 231 models between 2012 and 2023 found that the computational power required for LLMs has halved every eight months, outpacing Moore’s Law. Second, new neural network approaches like Kolmogorov-Arnold Networks (KANs) show promise, achieving comparable results to traditional models with far fewer parameters. Lastly, agentic AI frameworks like Salesforce’s Agentforce offer a new architecture where domain-specific AI agents can outperform larger general-purpose models. As AI continues to evolve, it’s clear that while parameter count is an important consideration, it’s just one of many factors in evaluating a model’s overall capabilities. To stay on the cutting edge of artificial intelligence, contact Tectonic today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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
18Oct
Amazon DynamoDB to Salesforce Data Cloud
Ingesting Data from Amazon DynamoDB to Salesforce Data Cloud Salesforce Data Cloud serves as your organization’s digital command center, enabling real-time ingestion, unification, and activation of data from any source. By transforming scattered customer information into actionable insights, it empowers businesses to operate with unparalleled efficiency. Integrating Amazon DynamoDB with Salesforce Data Cloud exemplifies the platform’s capacity to unify and activate enterprise data seamlessly. Follow this step-by-step guide to ingest data from Amazon DynamoDB into Salesforce Data Cloud. Prerequisites Part 1: Amazon DynamoDB Setup 1. AWS Account Setup 2. Create a DynamoDB Table 3. Populate the Table with Data 4. Security Credentials Part 2: Salesforce Data Cloud Configuration 1. Creating the Data Connection 2. Configuring Data Streams Create a New Data Stream Configure the Data Model 3. Data Modeling and Mapping Custom Object Creation Conclusion After completing the setup: This integration underscores Salesforce Data Cloud’s role as a centralized hub, capable of harmonizing diverse data sources, ensuring real-time synchronization, and enabling actionable insights. By connecting Amazon DynamoDB, businesses can unlock the full potential of their data, driving better decision-making and customer experiences. 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
18Oct
Life of a Salesforce Admin in the AI Era
The life of Salesforce admins is rapidly evolving as artificial intelligence (AI) becomes integral to business operations. Let’s examine the Life of a Salesforce Admin in the AI Era. By 2025, the Salesforce admin’s role will expand beyond managing CRM systems to include leveraging AI tools to enhance efficiency, boost productivity, and maintain security. While this future offers exciting opportunities, it also comes with new responsibilities that require admins to adapt and learn. So, what will Salesforce admins need to succeed in this AI-driven landscape? The Salesforce Admin’s Role in 2025 In 2025, Salesforce admins will be at the forefront of digital transformation, helping organizations harness the full potential of the Salesforce ecosystem and AI-powered tools. These AI tools will automate processes, predict trends, and improve overall efficiency. Many professionals are already enrolling in Salesforce Administrator courses focused on AI and automation, equipping them with the essential skills to thrive in this new era. Key Responsibilities in Life of a Salesforce Admin in the AI Era 1. AI Integration and Optimization Admins will be responsible for integrating AI tools like Salesforce Einstein AI into workflows, ensuring they’re properly configured and tailored to the organization’s needs. Core tasks include: 2. Automating Processes with AI AI will revolutionize automation, making complex workflows more efficient. Admins will need to: 3. Data Management and Predictive Analytics Admins will leverage AI to manage data and generate predictive insights. Key responsibilities include: 4. Enhancing Security and Compliance AI-powered security tools will help admins proactively protect systems. Responsibilities include: 5. Supporting AI-Driven Customer Experiences Admins will deploy AI tools that enhance customer interactions. Their responsibilities include: 6. Continuous Learning and Upskilling As AI evolves, so too must Salesforce admins. Key learning areas include: 7. Collaboration with Cross-Functional Teams Admins will work closely with IT, marketing, and sales teams to deploy AI solutions organization-wide. Their collaborative efforts will include: Skills Required for Future Salesforce Admins 1. AI and Machine Learning Proficiency Admins will need to understand how AI models like Einstein AI function and how to deploy them. While not requiring full data science expertise, a solid grasp of AI concepts—such as predictive analytics and machine learning—will be essential. 2. Advanced Data Management and Analysis Managing large datasets and ensuring data accuracy will be critical as admins work with AI tools. Proficiency in data modeling, SQL, SOQL, and ETL processes will be vital for handling AI-powered data management. 3. Automation and Process Optimization AI-enhanced automation will become a key responsibility. Admins must master tools like Salesforce Flow and Einstein Automate to build intelligent workflows and ensure smooth process automation. 4. Security and Compliance Expertise With AI-driven security protocols, admins will need to stay updated on data privacy regulations and deploy tools that ensure compliance and prevent data breaches. 5. Collaboration and Leadership Admins will lead the implementation of AI tools across departments, requiring strong collaboration and leadership skills to align AI-driven solutions with business objectives. Advanced Certifications for AI-Era Admins To stay competitive, Salesforce admins will need to pursue advanced certifications. Key certifications include: Tectonic’s Thoughts The Salesforce admin role is transforming as AI becomes an essential part of the platform. By mastering AI tools, optimizing processes, ensuring security, and continuously upskilling, Salesforce admins can become pivotal players in driving digital transformation. The future is bright for those who embrace the AI-powered Salesforce landscape and position themselves at the forefront of 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
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The Rise of Agentic AI: Balancing Innovation and Trust
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