SSO Archives - gettectonic.com - Page 9
Securing SaaS
26May

Securing SaaS

Obsidian Security recently discussed the complexity of enforcing Single Sign-On (SSO) within Salesforce and frequently encountering misconfigurations. Notably, 60% of Obsidian’s customers initially have local access without Multi-Factor Authentication (MFA) configured for Salesforce, highlighting a significant security gap that Obsidian diligently works to secure. Securing SaaS. The Hidden Vulnerability Application owners who manage Salesforce daily often remain unaware of this misconfiguration. Despite their deep knowledge of Salesforce management, local access without MFA presents an overlooked vulnerability. This situation raises concerns about the security of other SaaS applications, especially those without developed expertise or knowledge. If you have concerns about your configuration, Tectonic can help. Attacker Focus and Trends Attackers have historically targeted the Identity Provider (IdP) space, focusing on providers like Okta, Microsoft Entra, and Ping. This strategy offers maximal impact, as compromising an IdP grants broad access across multiple applications. Developing expertise to breach a few IdPs is more efficient than learning the diverse local access pathways of numerous SaaS vendors. Over the past 12 months, nearly 100% of the breaches that required Obsidian’s intervention through CrowdStrike or other incident response partners were IdP-focused. Notably, 70% of these breaches involved subverting MFA, often through methods like SIM swapping. In instances where local access bypasses the IdP, 95% of the time it lacks MFA. Recent discussions around Snowflake have brought attention to “shadow authentication,” defined as unsanctioned means to authenticate a user within an application. Obsidian Security has observed an increase in brute force attacks against SaaS applications via local access pathways over the last two weeks, indicating a growing awareness of this attack vector. Future Expectations Attackers continually seek easy and efficient pathways. Over the next 12 months, local access or shadow authentication is expected to become a major attack vector. Organizations must proactively secure these pathways as attackers shift their focus. What You Can Do How Obsidian Helps Salesforce Security partners offers robust solutions to address these challenges: By leveraging partner capabilities, organizations can enhance their security posture, protecting against evolving threats targeting local access and shadow authentication. The post “The Growing Importance of Securing Local Access in SaaS Applications” appeared first on Obsidian 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

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May 26, 2024in Salesforce, Salesforce Einstein, Snowflake
Cost of Free Analytics
20May

Cost of Free Analytics

Is It Time to Upgrade Your Web Analytics? For years, you might have relied on free web analytics tools, thinking they do the job or resigning yourself to an “it is what it is” mindset. But what if there’s a better way to truly understand your customers and supercharge your marketing efforts? Upgrading to a premium analytics solution could be a game changer for your brand and your peace of mind. What is the Cost of Free Analytics? It’s time to move beyond those so-called free tools (which aren’t really free when you factor in hidden costs) and invest in a robust analytics solution. The right tool can transform your approach—imagine saying goodbye to the hassle of patching together data or juggling disparate reports. With clear, comprehensive insights into customer interactions, you’ll make smarter, data-driven decisions across your business. The Pitfalls of Free Analytics Tools While free analytics tools might seem like a cost-effective choice, they come with significant drawbacks. They often offer limited functionality, delayed or incomplete data, siloed reporting, and compliance risks. Relying on these tools can lead to guesswork and errors, resulting in costly mistakes. Limited Functionality Free analytics tools barely skim the surface of what’s possible with data collection and reporting. They depend on third-party cookies and route your data through their servers, providing you with only partial insights. Essential features like persistent digital identity tracking, profile building, journey mapping, predictive analytics, and machine learning capabilities are typically missing. In contrast, premium tools leverage advanced algorithms and machine learning to unearth valuable data patterns and insights. For instance, a premium tool might reveal that users who view a product page after watching a related video are significantly more likely to make a purchase—information that could greatly influence your marketing strategy. Subpar Data Quality Free tools often lag in delivering real-time data, giving you an outdated snapshot of customer interactions. Timely data is crucial for agile marketing—without it, you risk missing out on opportunities and wasting ad spend. Stale data leads to missed chances and inefficiencies. Reporting Silos and Inaccuracies Free analytics solutions typically don’t integrate data across your organization, resulting in fragmented and siloed information. Different teams may have access to unaligned reports, often requiring multiple tools to piece together insights. This lack of a unified source of truth makes it impossible to get a comprehensive view of customer interactions across various touchpoints. Organizational Inefficiencies Managing free tools can be resource-intensive. They often require extensive tagging and manual upkeep, leading to increased costs and the risk of inaccurate data due to broken or altered tags. This inefficiency can impact long-term business decisions and strategic planning. Compliance Risks Free tools often involve sending your data to external servers, raising concerns about data loss, latency, and compliance with privacy regulations. These tools process your digital engagement and Personally Identifiable Information (PII) on their servers, complicating the task of maintaining regulatory standards and ensuring data security. The True Cost of Free Tools The reality is, “free” isn’t really free. The hidden costs and risks associated with free analytics tools can outweigh their benefits. While premium analytics solutions may seem expensive at first glance, they offer superior insights and performance improvements that provide a competitive edge. With accurate, real-time data and advanced features, investing in a premium tool is a decision that pays off. Remember, the old adage “nothing’s free” rings true—don’t jeopardize your brand’s success with subpar tools that end up costing more in the long run! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 20, 2024in Salesforce
MuleSoft Certifications Now Unified with Salesforce Certifications
09May

MuleSoft Certifications Now Unified with Salesforce Certifications

MuleSoft Certifications Now Unified with Salesforce Certifications As of May 6, 2024, MuleSoft certifications have been officially integrated into the Salesforce Certification program, with management now handled through Webassessor. This move simplifies the certification process, enabling professionals to manage both their Salesforce and MuleSoft credentials within a single platform, streamlining maintenance and tracking. This article delves into the merging of MuleSoft certifications with Salesforce’s Trailhead platform, highlighting what this means for professionals in both ecosystems. The update offers a significant improvement in managing certifications, particularly for those working across both platforms, as Salesforce has owned MuleSoft since 2018. We’ll cover what this change entails for current certification holders, key dates in the transition, and the new opportunities this unified platform brings—including new certifications. What is MuleSoft? MuleSoft is a leading integration platform that enables businesses to connect applications, data, and devices seamlessly. As an Integration Platform as a Service (iPaaS), MuleSoft facilitates the integration of cloud-based and on-premise applications, ensuring smooth workflows across various systems. Acquired by Salesforce in 2018, MuleSoft powers the integration layer of the Salesforce ecosystem, playing a crucial role in enabling businesses to unify their systems and create connected experiences. With the increasing demand for digital transformation and connected systems, MuleSoft expertise is becoming ever more valuable in the job market. MuleSoft Certifications and Training MuleSoft certifications validate expertise in designing, building, and managing integrations using the Anypoint Platform. Prior to this transition, MuleSoft certifications were handled through the MuleSoft Training portal, which was separate from Salesforce’s broader certification system. While this independent platform was functional, it required separate accounts and processes, making exam registration and certification management more cumbersome. By integrating MuleSoft certifications into Trailhead, Salesforce has simplified this process, offering a unified, more user-friendly experience for managing certifications. Transition Timeline The following key dates marked the transition: What This Means for Current MuleSoft Certification Holders For those already certified through MuleSoft, the migration to Salesforce’s certification system should have occurred automatically. MuleSoft credentials were transferred to their Trailblazer profiles for anyone with existing Webassessor accounts. A confirmation email was sent to ensure that the transition was successful. For those without a Webassessor account, one was created on their behalf, with login details provided via email by April 2024. Certification Maintenance MuleSoft certification holders with maintenance pending as of January 1, 2024, are not required to complete additional tasks through the old system. The expectation is that certification holders will have ample time to familiarize themselves with the new Trailhead process before maintenance requirements are introduced in 2025. New Certifications on Trailhead With the migration, certifications such as the MuleSoft Certified Catalyst Specialist and MuleSoft Certified Hyperautomation Specialist have also been integrated into Trailhead. Though not entirely new, these certifications were part of the legacy MuleSoft program, originally launched in late 2022 and early 2023. Summary The integration of MuleSoft certifications into Salesforce’s Trailhead platform marks a significant step towards a unified, more efficient credentialing process. This transition simplifies certification management, making it easier for professionals to stay current across both platforms. By merging these certifications, Salesforce is empowering professionals to fully leverage the combined capabilities of Salesforce and MuleSoft, further enhancing their skill sets in an increasingly interconnected digital landscape. Content updated September 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 9, 2024in Data, Mulesoft, Salesforce
Constituent Service Toolkit in Public Sector Solutions
10Apr

Constituent Service Toolkit in Public Sector Solutions

Explore the array of tools and components tailored for caseworkers, case managers, and other professionals to comprehend constituents’ needs and deliver exceptional customer service. Constituent Service Toolkit in Public Sector Solutions Public Sector Solutions offers a comprehensive suite of components, tools, and features designed to enhance the efficiency of caseworkers and other staff in addressing constituents’ concerns and issues. These tools provide valuable context for interactions with constituents and streamline actionable tasks, offering flexibility for customization to address diverse scenarios. Constituent Service Toolkit in Public Sector Solutions Whether handling inquiries about business license applications, social service benefits, or managing complaints and child welfare concerns, these tools empower users to efficiently navigate and resolve constituent service issues. Public Sector Solutions goes a step further by presenting a curated selection of these tools on a dedicated Lightning record page, facilitating a seamless start for users in utilizing these resources. Customize the page according to your agency’s specific needs, with limitless possibilities. Constituent Service Toolkit: Elevate customer service for constituents by providing tools that enhance the efficiency and effectiveness of caseworkers, case managers, and other users. Complete Common Service Tasks in Context with Action Launcher: Empower intake agents, caseworkers, and other users to access common service tasks through the Action Launcher Lightning web component. This tool allows users to perform tasks such as identity verification, referral intake, email communication, or call logging with a simple menu selection. Tailor the Action Launcher to meet specific needs and integrate it into frequently accessed record detail pages for quick and context-aware responses to constituent concerns. Protect Constituent Privacy and Reduce Fraud with Identity Verification and Audit Trail: Prioritize constituent privacy by implementing a flow to verify their identity before sharing sensitive information. Agents and service representatives can initiate this flow during phone calls, through messaging channels, or in person. Utilize the Audit Trail to monitor engagement interactions, analyze patterns, and detect potential fraud associated with identity verification. Receive Alerts on Records That Need Action: Stay informed about account and application records requiring attention with the Record Alerts component. Caseworkers, application reviewers, and other users receive notifications about person accounts, business accounts, or individual application records that demand action. The component organizes alerts by categories like type, priority, and severity, allowing users to dismiss or snooze alerts as needed. Deliver Service to Constituents from a Dedicated Account Lightning Record Page: Enhance caseworkers’ efficiency by providing relevant information and service tools through a dedicated Lightning record page for accounts. Key details about constituents are showcased through the Account card and Timeline component. The Action Launcher and Alerts components enable users to initiate common service actions and address pending record alerts. The Interaction Summary tab allows users to document notes from conversations and engagements with constituents. Create Start-to-Finish Automation to Address Service Requests from Constituents with Service Process Studio: Leverage Service Process Studio to design automated processes that efficiently respond to service requests from constituents, from intake to resolution. Utilize data attributes, OmniScript forms, Apex classes, and record-triggered flows to create automation for processing service requests, including tasks like updating a constituent’s address. Integration definitions enable seamless connectivity between service processes and external systems. 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 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

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April 10, 2024in Public Sector Solutions, Salesforce Implementation Services
Where Will AI Take Us?
26Mar

Where Will AI Take Us?

Author Jeremy Wagstaff wrote a very thought provoking article on the future of AI, and how much of it we could predict based on the past. This insight expands on that article. Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn. These machines can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Many people think of artificial intelligence in the vein of how they personally use it. Some people don’t even realize when they are using it. Artificial intelligence has long been a concept in human mythology and literature. Our imaginations have been grabbed by the thought of sentient machines constructed by humans, from Talos, the enormous bronze automaton (self-operating machine) that safeguarded the island of Crete in Greek mythology, to the spacecraft-controlling HAL in 2001: A Space Odyssey. Artificial Intelligence comes in a variety of flavors, if you will. Artificial intelligence can be categorized in several ways, including by capability and functionality: You likely weren’t even aware of all of the above categorizations of artificial intelligence. Most of us still would sub set into generative ai, a subset of narrow AI, predictive ai, and reactive ai. Reflect on the AI journey through the Three C’s – Computation, Cognition, and Communication – as the guiding pillars for understanding the transformative potential of AI. Gain insights into how these concepts converge to shape the future of technology. Beyond a definition, what really is artificial intelligence, who makes it, who uses it, what does it do and how. Artificial Intelligence Companies – A Sampling AI and Its Challenges Artificial intelligence (AI) presents a novel and significant challenge to the fundamental ideas underpinning the modern state, affecting governance, social and mental health, the balance between capitalism and individual protection, and international cooperation and commerce. Addressing this amorphous technology, which lacks a clear definition yet pervades increasing facets of life, is complex and daunting. It is essential to recognize what should not be done, drawing lessons from past mistakes that may not be reversible this time. In the 1920s, the concept of a street was fluid. People viewed city streets as public spaces open to anyone not endangering or obstructing others. However, conflicts between ‘joy riders’ and ‘jay walkers’ began to emerge, with judges often siding with pedestrians in lawsuits. Motorist associations and the car industry lobbied to prioritize vehicles, leading to the construction of vehicle-only thoroughfares. The dominance of cars prevailed for a century, but recent efforts have sought to reverse this trend with ‘complete streets,’ bicycle and pedestrian infrastructure, and traffic calming measures. Technology, such as electric micro-mobility and improved VR/AR for street design, plays a role in this transformation. The guy digging out a road bed for chariots and Roman armies likely considered none of this. Addressing new technology is not easy to do, and it’s taken changes to our planet’s climate, a pandemic, and the deaths of tens of millions of people in traffic accidents (3.6 million in the U.S. since 1899). If we had better understood the implications of the first automobile technology, perhaps we could have made better decisions. Similarly, society should avoid repeating past mistakes with AI. The market has driven AI’s development, often prioritizing those who stand to profit over consumers. You know, capitalism. The rapid adoption and expansion of AI, driven by commercial and nationalist competition, have created significant distortions. Companies like Nvidia have soared in value due to AI chip sales, and governments are heavily investing in AI technology to gain competitive advantages. Listening to AI experts highlights the enormity of the commitment being made and reveals that these experts, despite their knowledge, may not be the best sources for AI guidance. The size and impact of AI are already redirecting massive resources and creating new challenges. For example, AI’s demand for energy, chips, memory, and talent is immense, and the future of AI-driven applications depends on the availability of computing resources. The rise in demand for AI has already led to significant industry changes. Data centers are transforming into ‘AI data centers,’ and the demand for specialized AI chips and memory is skyrocketing. The U.S. government is investing billions to boost its position in AI, and countries like China are rapidly advancing in AI expertise. China may be behind in physical assets, but it is moving fast on expertise, generating almost half of the world’s top AI researchers (Source: New York Times). The U.S. has just announced it will provide chip maker Intel with $20 billion in grants and loans to boost the country’s position in AI. Nvidia is now the third largest company in the world, entirely because its specialized chips account for more than 70 percent of AI chip sales. Memory-maker Micro has mostly run out of high-bandwidth memory (HBM) stocks because of the chips’ usage in AI—one customer paid $600 million up-front to lock in supply, according to a story by Stack. Back in January, the International Energy Agency forecast that data centers may more than double their electrical consumption by 2026 (Source: Sandra MacGregor, Data Center Knowledge). AI is sucking up all the payroll: Those tech workers who don’t have AI skills are finding fewer roles and lower salaries—or their jobs disappearing entirely to automation and AI (Source: Belle Lin at WSJ). Sam Altman of OpenAI sees a future where demand for AI-driven apps is limited only by the amount of computing available at a price the consumer is willing o pay. “Compute is going to be the currency of the future. I think it will be maybe the most precious commodity in the world, and I think we should be investing heavily to make a lot more compute.” Sam Altman, OpenAI CEO This AI buildup is reminiscent of past technological transformations, where powerful interests shaped outcomes, often at the expense of broader societal considerations. Consider early car manufacturers. They focused on a need for factories, components, and roads. AI’s rapid

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March 26, 2024in Generative AI
Salesforce Education Cloud for Educational Challenges
24Mar

Salesforce Education Cloud for Educational Challenges

Educational institutions today confront a multitude of complex challenges, ranging from disjointed information systems to the need for agility in meeting evolving educational demands. Salesforce Education Cloud presents a unified solution aimed at overcoming these obstacles by enhancing operational efficiencies, boosting student engagement, and ensuring compliance with ever-changing educational standards. Below is an in-depth examination of the prevalent challenges faced by educational institutions and the tailored solutions provided by Salesforce Education Cloud. Key Challenges in the Education Sector Salesforce Education Cloud: Tailored Solutions for Education Salesforce Education Cloud addresses these challenges through a suite of customized features and tools designed to streamline operations, enhance student services, and promote effective communication. Real-World Impact of Salesforce Education Cloud Implementation of Salesforce Education Cloud yields transformative benefits across educational institutions: Conclusion Salesforce Education Cloud offers a comprehensive solution to the diverse challenges faced by educational institutions. By integrating this robust platform, schools, colleges, and universities can enhance operational efficiency, improve student outcomes, and cultivate a collaborative educational environment. Institutions seeking to explore the benefits of Education Cloud or enhance their existing systems are encouraged to consult with a Salesforce Education Cloud Consultant for tailored guidance and implementation strategies. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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March 24, 2024in Salesforce, Salesforce Education Cloud, Salesforce Education Solutions, Salesforce Einstein
Leverage AI and Machine Learning in Your Data Warehouse
08Mar

Exploring Machine Learning with Salesforce

Machine Learning (ML) falls into three main categories: Supervised Learning, Unsupervised Learning, and Reinforcement Learning. Let’s dive into some issues and considerations that might leave you wondering if it’s even worth starting! Not embracing what Professor Stuart Russell called “the biggest event in human history” may be short-sighted. Don’t worry, Salesforce can help. Salesforce and Machine Learning Salesforce has a 20-year history of making complex technologies business-friendly. This extends to Machine Learning, integrating ML capabilities throughout the Salesforce Customer 360 suite, which includes solutions for Marketing, Commerce, Sales, Service, and Analytics, among others. Machine Learning in Action with Salesforce Marketing Imagine you’re in a marketing role. You want to predict the likelihood that a customer will engage with your campaigns to maximize effectiveness. Supervised Learning can help here by predicting subscriber engagement (opens, click-throughs, conversions) using historical data (90 days of engagement metrics). For example, using predictive Engagement Scoring, a Salesforce customer in the travel industry achieved a 66% drop in unsubscribe rates and a 13% revenue increase. You also want to ensure prospective customers can quickly find relevant products. Unsupervised Learning can personalize product assortments throughout the shopper journey by analyzing buying patterns, site browsing tendencies, and relationships between search terms and products. Using AI-powered Predictive Sort, businesses have seen a 9.1% increase in revenue per visitor and a 3.8% increase in conversion rates. Sales For sales teams handling many opportunities, predicting the quality of each Opportunity can help prioritize efforts. Supervised Learning, using historical data of at least 200 Closed/Won and 200 Closed/Lost Opportunities, can provide a prioritized list of Opportunities to maximize revenue potential. A large Salesforce customer in the consumer goods sector increased win rates by 48% by focusing on the best Opportunities. Service Post-sale customer support is crucial. Service agents need to address challenging cases efficiently. Supervised Learning can recommend articles to resolve current cases based on historical data from at least 1000 cases with knowledge base articles. A large electronics company using Salesforce AI-powered solutions saved 5 hours per agent per week, enhancing productivity. Simplifying Complex Technology Salesforce’s rich history of making complex technology accessible allows businesses to realize ML benefits without needing specialized knowledge. Traditional ML involves multiple steps like data collection, transformation, sampling, feature selection, model selection, score calibration, and integrating results. Salesforce simplifies this with a customizable data model, automated feature engineering, and automatic model building and selection. For example, in model selection, Salesforce runs a “model tournament” to choose the best model with varying hyper-parameters, ensuring the most accurate model is selected without requiring user intervention. Conclusion Salesforce abstracts the complexity of ML behind user-friendly interfaces, making it easier for businesses to leverage powerful technology. Whether it’s predicting customer engagement, personalizing shopping experiences, prioritizing sales opportunities, or enhancing customer support, Salesforce’s ML capabilities can drive significant business value. Discover more about how Salesforce can transform your approach to Machine Learning and help you achieve your business 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

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March 8, 2024in Data, Technology
AI Training Options
29Feb

AI Training Options

As AI adoption accelerates, AI certifications and courses have proliferated, providing deeper knowledge of this rapidly evolving technology. AI Training Options. Numerous AI certifications cover the basics, so we’ve narrowed the field to 10 of the most diverse and comprehensive programs. AI Training Options Artificial intelligence is poised to become the key technology that drives business transformation and gives companies a competitive edge. According to a recent forecast by the International Data Corporation, global spending on AI—including AI-enabled applications, infrastructure, and related services—will more than double to $632 billion by 2028, growing at a compound annual rate of 29% between 2024 and 2028. AI helps businesses boost productivity by automating processes such as robotics and autonomous vehicles, while also supporting existing workforces with technologies like assisted and augmented intelligence. Companies are integrating AI across various sectors, including finance, healthcare, retail, smart home devices, fraud detection, and security surveillance. Why AI certifications are important: 10 of the best AI certifications and courses: Each certification offers unique benefits, whether you’re a beginner or an experienced professional aiming to stay ahead in AI-driven industries. Content updated September 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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February 29, 2024in Artificial Intelligence, Data, Generative AI, Google, Technology
AI Adoption Not Even Across the Board
07Feb

AI Adoption Not Even Across the Board

Reflecting on AI’s potential and its challenges, McElheran calls for a balanced approach: “To fully harness AI’s benefits, we need a realistic, evidence-based approach that accounts for both the advantages and the societal costs associated with adoption.”

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February 7, 2024in Data, Technology
Unfolding AI Revolution
19Jan

Unfolding AI Revolution

Ways the AI Revolution is Unfolding The transformative potential of artificial intelligence (AI) is being explored by James Manyika, Senior VP of Research, Technology, and Society at Google, and Michael Spence, Nobel laureate in economics and professor at NYU Stern School of Business, in their recent article, “The Coming AI Economic Revolution: Can Artificial Intelligence Reverse the Productivity Slowdown?” Published in Foreign Affairs, the article outlines the conditions necessary for an AI-powered economy to thrive, including policies that augment human capabilities, promote widespread adoption, and foster organizational innovation. Manyika and Spence highlight AI’s potential to reverse stagnating productivity growth in advanced economies, stating, “By the beginning of the next decade, the shift to AI could become a leading driver of global prosperity.” However, the authors caution that this economic revolution will require robust policy frameworks to prevent harm and unlock AI’s full potential. Here are the key insights from their analysis: 1. The Great Slowdown The rapid advancements in AI arrive at a critical juncture for the global economy. While technological innovations have surged, productivity growth has stagnated. For instance, total factor productivity (TFP), a key contributor to GDP growth, grew by 1.7% in the U.S. between 1997 and 2005 but has since slowed to just 0.4%. This slowdown is exacerbated by aging populations and shrinking labor forces in major economies like China, Japan, and Italy. Without a transformative force like AI, economic growth could remain stifled, characterized by higher inflation, reduced labor supply, and elevated capital costs. 2. A Different Digital Revolution Unlike the rule-based automation of the 1990s digital revolution, AI has shattered previous technological constraints. Advances in AI now enable tasks that were previously unprogrammable, such as pattern recognition and decision-making. AI systems have surpassed human performance in areas like image recognition, cancer detection, and even strategic games like Go. This shift extends the impact of technology to domains previously thought to require exclusively human intuition and creativity. 3. Quick Studies Generative AI, particularly large language models (LLMs), offers exceptional versatility, multimodality, and accessibility, making its economic impact potentially transformative: Applications range from digital assistants drafting documents to ambient intelligence systems that automate homes or generate health records based on patient-clinician interactions. 4. Creative Instruction Despite its promise, AI has drawn criticism for issues like bias, misinformation, and the potential for job displacement. Critics highlight that AI systems may amplify societal inequities or produce unreliable outputs. However, research suggests that AI will primarily augment work rather than eliminate it. While about 10% of jobs may decline, two-thirds of occupations will likely see AI enhancing specific tasks. This shift emphasizes collaboration between humans and intelligent machines, requiring workers to develop new skills. Studies, such as MIT’s Work of the Future task force, reinforce that automation will not lead to a jobless future but rather to evolving roles and opportunities. 5. With Us, Not Against Us The full benefits of AI will not materialize if its deployment is left solely to market forces. Proactive measures are necessary to maximize AI’s positive impact while mitigating risks. This includes fostering widespread adoption of AI in ways that empower workers, enhance productivity, and address societal challenges. Policies should prioritize accessibility and equitable diffusion to ensure AI serves as a force for inclusive economic growth. 6. The Real AI Challenge Generative AI has the potential to spark a productivity renaissance at a time when the global economy urgently needs it. Yet, Manyika and Spence caution that AI could exacerbate existing economic disparities if not guided effectively. They argue that focusing solely on existential threats overlooks the broader risks posed by inequitable AI deployment. Instead, a positive vision is needed—one that prioritizes AI as a tool for global economic progress, equitable growth, and generational prosperity. “Harnessing the power of AI for good will require more than simply focusing on potential damage,” the authors conclude. “It will demand effective measures to turn that vision into reality.” The unfolding AI revolution offers immense opportunities, but realizing its full potential requires thoughtful action. By addressing risks and fostering innovation, AI could reshape the global economy for the better. 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

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January 19, 2024in Artificial Intelligence, Generative AI, Google, Technology
19Sep

Audience Builder Marketing Cloud

Marketing Cloud Audience Builder dynamically generates targeted audiences from contacts stored in your account based on attribute and behavioral values. These audiences can be used to target or exclude contacts from your marketing activities. In today’s world, where a staggering 347.3 billion emails are sent globally every day, email inboxes have become increasingly cluttered. In your specific niche, you’re not the only one trying to reach your target audience; numerous others are vying for their attention. With consumers having a multitude of options, marketers bear the responsibility of positioning themselves in a way that makes it impossible for potential customers to overlook them. Achieving this requires embracing customer-centricity, which involves deeply engaging with different buyer personas by segmenting your contact list based on various parameters such as age, gender, location, interests, preferences, past purchases, browsing history, and position in the sales funnel. However, manually managing this segmentation, especially with a large contact list, can be overwhelming. This is where a dependable tool like Salesforce Marketing Cloud’s Audience Builder proves invaluable. The SFMC Audience Builder empowers marketers to create granular segmentation frameworks based on demographic and behavioral data, making the execution of targeted campaigns effortless. It dynamically generates targeted audiences by utilizing contacts in your account and leveraging behavioral values and stored attributes as guiding parameters. In this overview, we aim to provide a comprehensive understanding of SFMC’s Audience Builder. Key Entities and Terminologies: Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 19, 2023in Data, Salesforce, Salesforce Marketing Cloud
SaaS Data Protection from Own
07Sep

Reporting With Own

In any Salesforce organization, vast amounts of data are generated constantly from sales activities, customer interactions, marketing campaigns, and more. Summarizing and digesting this information quickly is crucial, especially when presenting the big picture to leadership. This is where Salesforce reports come into play. The Salesforce Reports feature enables organizations to analyze, visualize, and summarize data in real time. By pulling data from across your Salesforce environment, reports help consolidate information into easily digestible formats, such as charts, tables, and graphs. Salesforce reports are essential for: How Historical Data Can Improve Reporting in Salesforce While real-time reports are valuable, incorporating historical data can significantly enhance reporting by offering deeper insights into your organization’s long-term performance. Here’s how: Challenges of Reporting with Historical Data in Salesforce While incorporating historical data is smart, Salesforce’s native reporting capabilities impose certain limitations: Don’t Let Salesforce Reporting Limitations Hold You Back With Own Discover, customers can effortlessly generate time-series datasets from any objects and fields over any time period in just a few clicks. These datasets can be accessed using standard query and reporting tools without requiring a data warehouse or the need to enrich existing data warehouses, overcoming Salesforce’s native limitations. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 7, 2023in Enterprise
einstein discovery dictionary
06Sep

Einstein Discovery Dictionary

Familiarize yourself with terminology that is commonly associated with Einstein Discovery. Actionable VariableAn actionable variable is an explanatory variable that people can control, such as deciding which marketing campaign to use for a particular customer. Contrast these variables with explanatory variables that can’t be controlled, such as a customer’s street address or a person’s age. If a variable is designated as actionable, the model uses prescriptive analytics to suggest actions (improvements) the user can take to improve the predicted outcome. Actual OutcomeAn actual outcome is the real-world value of an observation’s outcome variable after the outcome has occurred. Einstein Discovery calculates model performance by comparing how closely predicted outcomes come to actual outcomes. An actual outcome is sometimes called an observed outcome. AlgorithmSee modeling algorithm. Analytics DatasetAn Analytics dataset is a collection of related data that is stored in a denormalized, yet highly compressed, form. The data is optimized for analysis and interactive exploration. AttributeSee variable. AverageIn Einstein Discovery, the average represents the statistical mean for a variable. BiasIf Einstein Discovery detects bias in your data, it means that variables are being treated unequally in your model. Removing bias from your model can produce more ethical and accountable models and, therefore, predictions. See disparate impact. Binary Classification Use CaseThe binary classification use case applies to business outcomes that are binary: categorical (text) fields with only two possible values, such as win-lose, pass-fail, public-private, retain-churn, and so on. These outcomes separate your data into two distinct groups. For analysis purposes, Einstein Discovery converts the two values into Boolean true and false. Einstein Discovery uses logistic regression to analyze binary outcomes. Binary classification is one of the main use cases that Einstein Discovery supports. Compare with multiclass classification. CardinalityCardinality is the number of distinct values in a category. Variables with high cardinality (too many distinct values) can result in complex visualizations that are difficult to read and interpret. Einstein Discovery supports up to 100 categories per variable. You can optionally consolidate the remaining categories (categories with fewer than 25 observations) into a category called Other. Null values are put into a category called Unspecified. Categorical VariableA categorical variable is a type of variable that represents qualitative values (categories). A model that represents a binary or multiclass classification use case has a categorical variable as its outcome. See category. CategoryA category is a qualitative value that usually contains categorical (text) data, such as Product Category, Lead Status, and Case Subject. Categories are handy for grouping and filtering your data. Unlike measures, you can’t perform math on categories. In Salesforce Help for Analytics datasets, categories are referred to as dimensions. CausationCausation describes a cause-and-effect relationship between things. In Einstein Discovery, causality refers to the degree to which variables influence each other (or not), such as between explanatory variables and an outcome variable. Some variables can have an obvious, direct effect on each other (for example, how price and discount affect the sales margin). Other variables can have a weaker, less obvious effect (for example, how weather can affect on-time delivery). Many variables have no effect on each other: they are independent and mutually exclusive (for example, win-loss records of soccer teams and currency exchange rates). It’s important to remember that you can’t presume a causal relationship between variables based simply on a statistical correlation between them. In fact, correlation provides you with a hint that indicates further investigation into the association between those variables. Only with more exploration can you determine whether a causal link between them really exists and, if so, how significant that effect is .CoefficientA coefficient is a numeric value that represents the impact that an explanatory variable (or a pair of explanatory variables) has on the outcome variable. The coefficient quantifies the change in the mean of the outcome variable when there’s a one-unit shift in the explanatory variable, assuming all other variables in the model remain constant. Comparative InsightComparative insights are insights derived from a model. Comparative insights reveal information about the relationships between explanatory variables and the outcome variable in your story. With comparative insights, you isolate factors (categories or buckets) and compare their impact with other factors or with global averages. Einstein Discovery shows waterfall charts to help you visualize these comparisons. CorrelationA correlation is simply the association—or “co-relationship”—between two or more things. In Einstein Discovery, correlation describes the statistical association between variables, typically between explanatory variables and an outcome variable. The strength of the correlation is quantified as a percentage. The higher the percentage, the stronger the correlation. However, keep in mind that correlation is not causation. Correlation merely describes the strength of association between variables, not whether they causally affect each other. CountA count is the number of observations (rows) associated with an analysis. The count can represent all observations in the dataset, or the subset of observations that meet associated filter criteria.DatasetSee Analytics dataset. Date VariableA date variable is a type of variable that contains date/time (temporal) data.Dependent VariableSee outcome variable. Deployment WizardThe Deployment Wizard is the Einstein Discovery tool used to deploy models into your Salesforce org. Descriptive InsightsDescriptive insights are insights derived from historical data using descriptive analytics. Descriptive insights show what happened in your data. For example, Einstein Discovery in Reports produces descriptive insights for reports. Diagnostic InsightsDiagnostic insights are insights derived from a model. Whereas descriptive insights show what happened in your data, diagnostic insights show why it happened. Diagnostic insights drill deeper into correlations to help you understand which variables most significantly impacted the business outcome you’re analyzing. The term why refers to a high statistical correlation, not necessarily a causal relationship. Disparate ImpactIf Einstein Discovery detects disparate impact in your data, it means that the data reflects discriminatory practices toward a particular demographic. For example, your data can reveal gender disparities in starting salaries. Removing disparate impact from your model can produce more accountable and ethical insights and, therefore, predictions that are fair and equitable. Dominant ValuesIf Einstein Discovery detects dominant values in a variable, it means that the data is unbalanced. Most values are in the same category, which can limit the value of the analysis. DriftOver time, a deployed model’s performance can drift, becoming less accurate in predicting outcomes. Drift can occur due to changing factors in the data or in your business environment. Drift also results from now-obsolete assumptions built into the story

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September 6, 2023in Artificial Intelligence, Data, Salesforce

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