Glossary Archives - gettectonic.com
Alation Strengthens Data Cloud
20Nov

Alation Anywhere

Alation Anywhere for Google Chrome: A Streamlined Approach to Analysis Alation’s browser-based extension, Alation Anywhere for Google Chrome, integrates its tools directly into the user’s browser to reduce the inefficiencies caused by toggling between applications. This innovation enhances workflow efficiency and accelerates access to data-driven insights, bringing the full power of Alation’s Data Intelligence Platform into the daily flow of work. Tackling Context-Switching with Alation Anywhere A 2022 Harvard Business Review study revealed that Fortune 500 employees toggle between applications 1,200 times per day, resulting in four hours of weekly lost productivity and five weeks of annual time wasted. By embedding Alation’s capabilities into Chrome, users can seamlessly interact with curated and governed data without leaving their current workflows. According to Matt Aslett, analyst at Ventana Research, “The primary goal of capabilities like Alation Anywhere is to accelerate data-driven decision-making. By embedding data catalog functionality within productivity tools, it reduces the delays caused by switching contexts and facilitates quicker access to insights.” Enhanced Data Discovery in the Browser The popularity of web-based applications makes Chrome the ideal platform for extending Alation’s tools. Stewart Bond, analyst at IDC, emphasizes that “most modern applications are accessed via the browser. Alation Anywhere for Chrome eliminates the need to toggle between browser tabs, saving users time and boosting productivity.” Beyond efficiency, embedding analytics into frequently used tools increases the likelihood of data-driven decision-making. By integrating Alation’s insights directly into the browser, users can make informed decisions in real-time, with minimal disruptions. Key Features of Alation Anywhere for Google Chrome The Chrome extension introduces several tools to streamline data discovery and management: These features reflect Alation’s strategy of extending data catalog capabilities to the tools users rely on most, facilitating quicker and more accurate insights. Meeting Modern Data Demands As enterprises increasingly develop AI models and applications, the need for accessible, real-time data is growing. Alation’s vice president of product management, Diby Malakar, highlighted the role of user feedback in driving innovations like the Chrome extension. “Embedding analytics and data management directly into everyday tools is essential for streamlining workflows and reducing friction,” said Malakar. “Our goal is to ensure data intelligence is always available where it drives the most value.” Differentiation and Future Focus While Alation’s browser-based extension addresses a critical need, competitors such as Collibra, Informatica, and Qlik also offer similar capabilities. To stand out, Alation must build on unique initiatives like its new AI governance suite, which addresses emerging challenges in enterprise AI adoption. According to Malakar, Alation will continue developing features that enable both technical and non-technical users to discover and curate trusted data. This aligns with growing enterprise priorities, including real-time analytics and AI model development. “As AI and data initiatives become central to enterprises, the demand for accessible, reliable data will only increase,” Malakar noted. “Alation is committed to evolving our platform to meet these needs … backed by the data they trust.” Alation Anywhere for Google Chrome exemplifies the company’s commitment to improving access to governed data while staying attuned to user workflows and the evolving data landscape. 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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November 20, 2024in Data, Enterprise, Google, Salesforce, Snowflake
AI Prompts to Accelerate Academic Reading
19Oct

AI Prompts to Accelerate Academic Reading

10 AI Prompts to Accelerate Academic Reading with ChatGPT and Claude AI In the era of information overload, keeping pace with academic research can feel daunting. Tools like ChatGPT and Claude AI can streamline your reading and help you extract valuable insights from research papers quickly and efficiently. These AI assistants, when used ethically and responsibly, support your critical analysis by summarizing complex studies, highlighting key findings, and breaking down methodologies. While these prompts enhance efficiency, they should complement—never replace—your own critical thinking and thorough reading. AI Prompts for Academic Reading 1. Elevator Pitch Summary Prompt: “Summarize this paper in 3–5 sentences as if explaining it to a colleague during an elevator ride.”This prompt distills the essence of a paper, helping you quickly grasp the core idea and decide its relevance. 2. Key Findings Extraction Prompt: “List the top 5 key findings or conclusions from this paper, with a brief explanation of each.”Cut through jargon to access the research’s core contributions in seconds. 3. Methodology Breakdown Prompt: “Explain the study’s methodology in simple terms. What are its strengths and potential limitations?”Understand the foundation of the research and critically evaluate its validity. 4. Literature Review Assistant Prompt: “Identify the key papers cited in the literature review and summarize each in one sentence, explaining its connection to the study.”A game-changer for understanding the context and building your own literature review. 5. Jargon Buster Prompt: “List specialized terms or acronyms in this paper with definitions in plain language.”Create a personalized glossary to simplify dense academic language. 6. Visual Aid Interpreter Prompt: “Explain the key takeaways from Figure X (or Table Y) and its significance to the study.”Unlock insights from charts and tables, ensuring no critical information is missed. 7. Implications Explorer Prompt: “What are the potential real-world implications or applications of this research? Suggest 3–5 possible impacts.”Connect theory to practice by exploring broader outcomes and significance. 8. Cross-Disciplinary Connections Prompt: “How might this paper’s findings or methods apply to [insert your field]? Suggest potential connections or applications.”Encourage interdisciplinary thinking by finding links between research areas. 9. Future Research Generator Prompt: “Based on the limitations and unanswered questions, suggest 3–5 potential directions for future research.”Spark new ideas and identify gaps for exploration in your field. 10. The Devil’s Advocate Prompt: “Play devil’s advocate: What criticisms or counterarguments could be made against the paper’s main claims? How might the authors respond?”Refine your critical thinking and prepare for discussions or reviews. Additional Resources Generative AI Prompts with Retrieval Augmented GenerationAI Agents and Tabular DataAI Evolves With Agentforce and Atlas Conclusion Incorporating these prompts into your routine can help you process information faster, understand complex concepts, and uncover new insights. Remember, AI is here to assist—not replace—your research skills. Stay critical, adapt prompts to your needs, and maximize your academic productivity. 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 Alphabet Soup of Cloud Terminology As with any technology, the cloud brings its own alphabet soup of terms. This insight will hopefully help you navigate Read more

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October 19, 2024in AI Tools, Data, Generative AI
Salesforce for K-12 and Higher Education
04Oct

Technology to Showcase the Value of Education

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

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October 4, 2024in Data, Salesforce, Salesforce Education Cloud, Technology
Data Governance in Salesforce
01Oct

Data Governance in Salesforce

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

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October 1, 2024in Data, Enterprise, Salesforce
Salesforce Org Merge Risks
10Sep

Salesforce Org Merge Risks

Managing Multiple Salesforce Instances: Challenges and Solutions For growing enterprises, managing multiple Salesforce instances can be a significant challenge. Each instance may house critical business data and processes, which often need to be consolidated, particularly during mergers, acquisitions, or different stages of Salesforce adoption. This consolidation is essential to reduce operating costs and enhance efficiency. Salesforce Org Merge Risks. Salesforce Org Merge Risks Overview Salesforce consolidation involves merging several instances into a single Salesforce organization. This process aims to improve operational efficiency, data visibility, and process standardization while minimizing the total cost of ownership. It may require setting up a new Salesforce organization to facilitate the merger. Typical Salesforce Consolidation Plan A comprehensive consolidation plan typically includes the following steps: Complexity and Benefits of Salesforce Consolidation While Salesforce consolidation offers significant benefits, such as improved efficiency and reduced costs, it is a complex process requiring careful planning and execution. Many companies partner with Salesforce experts, like Tectonic, to navigate the intricacies of consolidation successfully. Salesforce Org Merge Risks Risk 1: Under-Scoping Data Mapping, Migration, and Merging Risk 2: Overlooking Metrics, Measurements, and Reports Risk 3: Limiting Stakeholder Engagement and Change Management Conclusion While meticulous planning cannot guarantee a flawless Salesforce migration, it fosters communication among Salesforce, data, and business leaders, making challenges more manageable. Although managing and consolidating systems might seem straightforward, guiding people, processes, and data through the consolidation process is inherently complex and demanding. 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 10, 2024in Salesforce Sales Cloud, Salesforce Service Cloud
2024 AI Glossary
02Sep

2024 AI Glossary

Artificial intelligence (AI) has moved from an emerging technology to a mainstream business imperative, making it essential for leaders across industries to understand and communicate its concepts. To help you unlock the full potential of AI in your organization, this 2024 AI Glossary outlines key terms and phrases that are critical for discussing and implementing AI solutions. Tectonic 2024 AI Glossary Active LearningA blend of supervised and unsupervised learning, active learning allows AI models to identify patterns, determine the next step in learning, and only seek human intervention when necessary. This makes it an efficient approach to developing specialized AI models with greater speed and precision, which is ideal for businesses aiming for reliability and efficiency in AI adoption. AI AlignmentThis subfield focuses on aligning the objectives of AI systems with the goals of their designers or users. It ensures that AI achieves intended outcomes while also integrating ethical standards and values when making decisions. AI HallucinationsThese occur when an AI system generates incorrect or misleading outputs. Hallucinations often stem from biased or insufficient training data or incorrect model assumptions. AI-Powered AutomationAlso known as “intelligent automation,” this refers to the integration of AI with rules-based automation tools like robotic process automation (RPA). By incorporating AI technologies such as machine learning (ML), natural language processing (NLP), and computer vision (CV), AI-powered automation expands the scope of tasks that can be automated, enhancing productivity and customer experience. AI Usage AuditingAn AI usage audit is a comprehensive review that ensures your AI program meets its goals, complies with legal requirements, and adheres to organizational standards. This process helps confirm the ethical and accurate performance of AI systems. Artificial General Intelligence (AGI)AGI refers to a theoretical AI system that matches human cognitive abilities and adaptability. While it remains a future concept, experts predict it may take decades or even centuries to develop true AGI. Artificial Intelligence (AI)AI encompasses computer systems that can perform complex tasks traditionally requiring human intelligence, such as reasoning, decision-making, and problem-solving. BiasBias in AI refers to skewed outcomes that unfairly disadvantage certain ideas, objectives, or groups of people. This often results from insufficient or unrepresentative training data. Confidence ScoreA confidence score is a probability measure indicating how certain an AI model is that it has performed its assigned task correctly. Conversational AIA type of AI designed to simulate human conversation using techniques like NLP and generative AI. It can be further enhanced with capabilities like image recognition. Cost ControlThis is the process of monitoring project progress in real-time, tracking resource usage, analyzing performance metrics, and addressing potential budget issues before they escalate, ensuring projects stay on track. Data Annotation (Data Labeling)The process of labeling data with specific features to help AI models learn and recognize patterns during training. Deep LearningA subset of machine learning that uses multi-layered neural networks to simulate complex human decision-making processes. Enterprise AIAI technology designed specifically to meet organizational needs, including governance, compliance, and security requirements. Foundational ModelsThese models learn from large datasets and can be fine-tuned for specific tasks. Their adaptability makes them cost-effective, reducing the need for separate models for each task. Generative AIA type of AI capable of creating new content such as text, images, audio, and synthetic data. It learns from vast datasets and generates new outputs that resemble but do not replicate the original data. Generative AI Feature GovernanceA set of principles and policies ensuring the responsible use of generative AI technologies throughout an organization, aligning with company values and societal norms. Human in the Loop (HITL)A feedback process where human intervention ensures the accuracy and ethical standards of AI outputs, essential for improving AI training and decision-making. Intelligent Document Processing (IDP)IDP extracts data from a variety of document types using AI techniques like NLP and CV to automate and analyze document-based tasks. Large Language Model (LLM)An AI technology trained on massive datasets to understand and generate text. LLMs are key in language understanding and generation and utilize transformer models for processing sequential data. Machine Learning (ML)A branch of AI that allows systems to learn from data and improve accuracy over time through algorithms. Model AccuracyA measure of how often an AI model performs tasks correctly, typically evaluated using metrics such as the F1 score, which combines precision and recall. Natural Language Processing (NLP)An AI technique that enables machines to understand, interpret, and generate human language through a combination of linguistic and statistical models. Retrieval Augmented Generation (RAG)This technique enhances the reliability of generative AI by incorporating external data to improve the accuracy of generated content. Supervised LearningA machine learning approach that uses labeled datasets to train AI models to make accurate predictions. Unsupervised LearningA type of machine learning that analyzes and groups unlabeled data without human input, often used to discover hidden patterns. By understanding these terms, you can better navigate the AI implementation world and apply its transformative power to drive innovation and efficiency across your organization. Tectonic 2024 AI Glossary 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 Alphabet Soup of Cloud Terminology As with any technology, the cloud brings its own alphabet soup of terms. This insight will hopefully help you navigate Read more

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September 2, 2024in Generative AI
Requirements Engineering
21Jun

Requirements Engineering

Every project needs clear requirements. No exceptions. Without them, a project turns into a group of people standing around, unsure of what to do, essentially making things up as they go. This scenario may sound familiar to anyone who has been involved in disorganized projects. What are requirements? According to the Association for Project Management (APM), “Requirements are the wants and needs of stakeholders clearly defined with acceptance criteria.” Requirements engineering is the process for managing the entire lifecycle of these needs and involves five key stages: Let’s dive deeper into these stages: 1. Requirements Elicitation Sometimes, the term “requirements capture” is used, as if stakeholders’ needs are floating around, waiting to be caught. However, requirements are not passively waiting; they must be actively elicited. Elicitation Methods: Eliciting requirements involves interpreting genuine needs, not just compiling a wish list of requested features. 2. Requirements Analysis Once you’ve gathered a set of requirements, it’s time for analysis to ensure they are comprehensive, feasible, and aligned with the project’s objectives. This phase is crucial because 80% of project errors occur during the requirements phase, yet it often receives less than 20% of a project’s time. Key steps include: 3. Requirements Documentation After analyzing requirements, document them clearly to communicate with stakeholders and developers. A good requirements document typically includes: One popular method for documenting requirements is through user stories, which frame requirements from the user’s perspective: User stories focus on meeting user needs rather than prescribing technical specifications. 4. Requirements Validation The next step is validating your documented requirements. This ensures they accurately represent what users and stakeholders need. Validation methods include: Validation is essential to ensure requirements are complete, realistic, and verifiable. 5. Requirements Management The final phase involves tracking and managing changes to requirements throughout the project. Key Concepts: Agile frameworks often rely on iterative approaches, where product owners manage changes during sprint reviews and retrospectives. Summary Requirements engineering consists of five interdependent stages: elicitation, analysis, documentation, validation, and management. While these concepts may seem detailed, they offer a structured framework that’s essential for delivering high-quality solutions. By following this approach, even smaller, lower-risk digital projects can benefit from clear and actionable requirements. 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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June 21, 2024in Salesforce
abc
22Apr

Definitive Salesforce Glossary of Acronyms

Once again our heroes at Salesforce Ben have put together a great and definitive salesforce glossary of acronyms and it is way too good not to share. Bookmark it. Keep it handy. And at least once you won’t have to ask that embarrassing question or Google an acronym to know what everyone is talking about. Starter Acronym Meaning Definition AKA Also Known As Due to name changes Salesforce has made to some products and also the slang/pet names the Salesforce community adorn certain functionality, these three letters have crept into our vocabulary. You will also often here a product referred to as XYZ formerly known as. BA Business Analyst Business Analysts are the people in your organization who are asking ‘why’ (why a process happens the way it does) to understand what the business needs from its technology. As an organization grows, it typically demands larger and more complex software solutions. That’s where BAs come in. BSS Business Support System “Solutions which streamline operations, reduce costs, and help businesses create more innovative products by centralizing customer data and automating processes.” (source) DF Dreamforce Dreamforce is Salesforce’s flagship conference – but a conference like no other! Tickets to this annual event are highly sought-after because of the learning and networking opportunities available to the 170,000+ attendees (not to mention the legendary parties, too!) FKA Formerly Known As Due to the name changes Salesforce has made to some products, these three letters have started to creep into our vocabulary to avoid confusion, bringing the person we’re speaking to along with us.READ MORE: Glossary of Salesforce Product Name Changes EE Enterprise Edition You will commonly hear these Salesforce editions: Professional, Enterprise, and Unlimited. Enterprise Edition (EE) is where most organizations opt to start from, where you gain access to the features that most organizations need. GA General Availability The release status where a feature has been formally released. This happens by its inclusion in a Salesforce release cycle (Spring, Summer, Winter). Support will be available as technical support teams have been briefed on the functionality. (It comes after the Pilot and Beta phases). IaaS Infrastructure as a Service “Self-service models for accessing, monitoring, and managing remote datacenter infrastructures, such as compute (virtualized or bare metal), storage, networking, and networking services (e.g. firewalls). Salesforce does not offer Infrastructure-as-a-Service (IaaS) services. It is a customer of them, primarily Amazon Web Services.” (source) KPI Key Performance Indicator “A Key Performance Indicator is a measurable value that demonstrates how effectively a company is achieving key business objectives.” (source)Admins play a key role in KPI tracking, tasked to build Salesforce dashboards that demonstrate business trends. LEX Lightning Experience Salesforce revamped the product interface around 2015 after having a relatively consistent look and feel for its 16 years in operation. Salesforce Lightning was designed to be a big improvement in user experience – to boost user productivity and make CRM a pleasure to use. Most organizations have now transitioned to Salesforce Lightning from Classic. LOB Line of Business Line of Business could often come up when planning Salesforce projects. For example, Sales, Marketing, etc. When it comes to packaging, you can either split by project (let’s say Quote to Cash broadly) or by LOB. PaaS Platform as a Service “A set of cloud-based services that enable business users and developers to build applications at speed…As it’s a cloud-based service there’s no need to worry about the set-up and maintenance of servers, patching, upgrades, authentication.” (source)Salesforce characteristics that make it PaaS include a Mobile Software Development Kit (SDK), managed cloud database, and point-and-click app building. PE Professional Edition You will commonly hear these Salesforce editions: Professional, Enterprise, and Unlimited. QA Quality Assurance QA is a stage of testing/test automation, which is essential to manage risk and deliver quality Salesforce releases on time. The quality of any Salesforce customizations is your responsibility – not Salesforce’s! QA teams will stress-test the system’s functionality and report any bugs that need to be resolved. ROI Return on Investment As the name suggests, this is the return (the revenue) that an organization has gained as a direct result of an investment (budget spent). This is heard in the Salesforce ecosystem in multiple contexts – it could be an investment into a new Salesforce product, enhancement project, or AppExchange app. It could be RevOps teams performing ROI reporting across their marketing and sales data. SaaS Software as a Service Salesforce set out to be SaaS through and through! A third-party provider, like Salesforce, hosts your CRM and related applications for your users to access over the internet. In the case of Salesforce, licenses to access the service are typically billed annually, with a contractual commitment of one to three years. That’s why SaaS was revolutionary in the beginning, as companies were no longer locked into one system, with the possibility to switch providers without investing in the IT infrastructure themselves! SDLC Software Development Lifecycle “A process that produces software with the highest quality and lowest cost in the shortest time possible.” (source)As Salesforce is a platform that businesses extend according to their evolving needs, you may hear this term! SFDC Salesforce dot com Salesforce pioneered cloud CRM, so it was always referred to as ‘Salesforce dot-com’ in the early days to emphasize its online accessibility and to distinguish itself from premise offerings. The acronym still sticks today, especially among serving community members. SLACK SearchableLog of All Communication and Knowledge This might seem like a strange entry on this list, but Salesforce’s workplace instant messaging/collaboration platform is, in fact, an acronym, standing for “Searchable Log of All Communication and Knowledge”. Yes, Slack is a real word you’ll find in the dictionary, often used in slang – to “slack off” or “cut me some slack”. Don’t you think these associations drum up collaborative, highly responsive, productive, happy teams? You’re right – it all sounds dull. SME Subject Matter Expert This is an individual with specialized knowledge in a specific area. In the Salesforce ecosystem, you will find

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April 22, 2024in Salesforce
How Good is Our Data
22Feb

How Good is Our Data?

Generative AI promises to significantly reshape how you manage your customer relationships, but it requires data that is accurate, updated, accessible, and complete. Why is this important? You may do something differently this quarter than you did last quarter, based on the latest data. But if your data is outdated or incorrect, that’s what the AI will use.  Generative AI focuses on creating new and original content, chat responses, designs, synthetic content or even deepfakes. It’s particularly valuable in creative fields and for novel problem-solving, as it can autonomously generate many types of new outputs. Generative Artificial Intelligence models often present inaccurate information as though it were correct. This is often caused by limited information in the system, biases in training data, and issues with the algorithm. These are commonly called ‘hallucinations‘ and they present a huge problem. When training your models for generative AI, you should first ensure high information excellence from top to bottom. To get your information house in order, remove duplicates, outliers, errors, and other things that can negatively affect how you make decisions. Then connect your data sources — marketing, sales, service, commerce – into a single record, updated in real time, so the AI can make the best recommendations.   McKinsey recently wrote, “Companies that have not yet found ways to harmonize and provide ready access to their information will be unable to unlock much of generative AI’s potentially transformative power.” Why is data important in generative AI? Aside from the cost factor, poor information quality can introduce unnecessary and harmful noise into the generative AI systems and models, leading to misleading answers, nonsensical output, or overall lower efficacy. What is high-quality data for AI? High-quality information is essential for AI systems to deliver meaningful results. Data quality possesses several key attributes: Accuracy: High-quality information is free from errors and inaccuracies. Inaccurate information can mislead AI models and produce unreliable outputs. Is AI 100 percent accurate? Because AI will still rely on your data for decision making and accuracy depends on the quality of your information. AI machines must be well-programmed to make sure the machine is making decisions based on the correct, available information. Also, privacy and security of the data are paramount. AI machines need to access information that is encrypted and secure. Understand that Generative AI is most effective at creating new data based on existing patterns and examples, with a focus on text and image data. Generative AI is most suitable for generating new data based on existing patterns and examples. It doesn’t actually think for itself. Yet. Known Limitations Of Generative AI Large language models (LLMs) are prone to “hallucinations” – generating fictitious information, presented as factual or accurate. This can include citations, publications, biographical information, and other information commonly used in research and academic papers. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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February 22, 2024in Generative AI, Salesforce Einstein
Generative AI Glossary
27Sep

The Salesforce Generative AI Glossary

Salesforce has built and maintains a fairly definitive glossary of generative Artificial Intelligence terminology, Tectonic thought was good enough to share in our insights. Salesforce Generative AI Glossary. Help everyone in your company understand key generative AI terms, and what they mean for your customer relationships. Fun fact: This article was (partially) written using generative AI. Bookmark this! This generative AI glossary will be updated regularly. Does it seem like everyone around you is casually tossing around terms like “generative AI,” “large language models,” or “deep learning”? Salesforce has created a primer on everything you need to know to understand the newest, most impactful technology that’s come along in decades. Let’s dive into the world of generative AI. Salesforce has built a list of the most essential terms that will help everyone in your company — no matter their technical background – understand the power of generative AI. Each term is defined based on how it impacts both your customers and your team. And to highlight the real-world applications of generative AI, we put it to work for this article. Salesforce experts weighed in on the key terms, and then let a generative AI tool lay the groundwork for this glossary. Each definition needed a human touch to get it ready for publication, but it saved loads of time. Anthropomorphism The tendency for people to attribute human motivation, emotions, characteristics or behavior to AI systems. For example, you may think the model or output is ‘mean’ based on its answers, even though it is not capable of having emotions, or you potentially believe that AI is sentient because it is very good at mimicking human language. While it might resemble something familiar, it’s essential to remember that AI, however advanced, doesn’t possess feelings or consciousness. It’s a brilliant tool, not a human being. Artificial intelligence (AI) AI is the broad concept of having machines think and act like humans. Generative AI is a specific type of AI (more on that below). Artificial neural network (ANN) An Artificial Neural Network (ANN) is a computer program that mimics the way human brains process information. Our brains have billions of neurons connected together, and an ANN (also referred to as a “neural network”) has lots of tiny processing units working together. Think of it like a team all working to solve the same problem. Every team member does their part, then passes their results on. In the end, you get the answer you need. Augmented intelligence Think of augmented intelligence as a melding of people and computers to get the best of both worlds. Computers are great at handling lots of data and doing complex calculations quickly. Humans are great at understanding context, finding connections between things even with incomplete data, and making decisions on instinct. Augmented intelligence combines these two skill sets. It’s not about computers replacing people or doing all the work for us. It’s more like hiring a really smart, well-organized assistant.  Customer Relationship Management (CRM) with Generative AI CRM is a technology that keeps customer records in one place to serve as the single source of truth for every department, which helps companies manage current and potential customer relationships. Generative AI can make CRM even more powerful — think personalized emails pre-written for sales teams, e-commerce product descriptions written based on the product name, contextual customer service ticket replies, and more. Deep learning Deep learning is an advanced form of AI that helps computers become really good at recognizing complex patterns in data. It mimics the way our brain works by using what’s called layered neural networks, where each layer is a pattern (like features of an animal) that then lets you make predictions based on the patterns you’ve learned before (ex: identifying new animals based on recognized features). It’s really useful for things like image recognition, speech processing, and natural-language understanding. Discriminator (in a GAN) In a Generative Adversarial Network (GAN), the discriminator is like a detective. When it’s shown pictures (or other data), it has to guess which are real and which are fake. The “real” pictures are from a dataset, while the “fake” ones are created by the other part of the GAN, called the generator (see generator below). The discriminator’s job is to get better at telling real from fake, while the generator tries to get better at creating fakes. This is the software version of continuously building a better mousetrap. Ethical AI maturity model An Ethical AI maturity model is a framework that helps organizations assess and enhance their ethical practices in using AI technologies. It maps out the ways organizations can evaluate their current ethical AI practices, then progress toward more responsible and trustworthy AI usage. It covers issues related to transparency, fairness, data privacy, accountability, and bias in predictions.  Explainable AI (XAI) Remember being asked to show your work in math class? That’s what we’re asking AI to do. Explainable AI (XAI) should provide insight into what influenced the AI’s results, which will help users to interpret (and trust!) its outputs. This kind of transparency is always important, but particularly so when dealing with sensitive systems like healthcare or finance, where explanations are required to ensure fairness, accountability, and in some cases, regulatory compliance. Generative AI Generative AI is the field of artificial intelligence that focuses on creating new content based on existing data. For a CRM system, generative AI can be used to create a range of helpful outputs, from writing personalized marketing content, to generating synthetic data to test new features or strategies. Generative adversarial network (GAN) One of two deep learning models, GANs are made up of two neural networks: a generator and a discriminator. The two networks compete with each other, with the generator creating an output based on some input, and the discriminator trying to determine if the output is real or fake. The generator then fine-tunes its output based on the discriminator’s feedback, and the cycle continues until it stumps the discriminator. Generative pre-trained transformer

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September 27, 2023in Generative AI, Salesforce Einstein
Salesforce BI
15Jul

Salesforce Analytics Acronyms

Here is a helpful list of analytics acronyms you may encounter when discussing Salesforce. Salesforce Analytics Acronyms Acronym Meaning Definition AWS Amazon Web Services AWS offers “reliable, scalable, and inexpensive cloud computing services…the world’s most comprehensive and broadly adopted cloud, offering over 200 fully featured services from data centers globally.” (source)Multiple Salesforce products use AWS; however, it’s prominent in the analytics arena, where organizations rely on AWS to:”Extract, prepare, and analyze Salesforce.com data using Amazon AppFlow, AWS Glue DataBrew, and Amazon Athena.” (source) BYOAI Bring Your Own AI ‘Bring your own AI (model)’ is Salesforce’s way to meet their customers where they’re at. With Data Cloud, Salesforce not only supports Einstein (their own LLM), but also other ones like Sagemaker, Vertex AI, etc. BYOM Bring Your Own Model ‘Bring your own AI (model)’ is Salesforce’s way to meet their customers where they’re at. With Data Cloud, Salesforce not only supports Einstein (their own LLM), but also other ones like Sagemaker, Vertex AI, etc. CRMA CRM Analytics This is the analytics/business intelligence (BI) solution on the Salesforce platform, integrating Salesforce data with external data and provides the ability to analyze large datasets while performing predictive analytics. (Previously known as Wave/Einstein Analytics/Tableau CRM). EA Einstein Analytics The former name for CRM Analytics (also formerly Tableau CRM). You may still come across EA in outdated documentation. GPT Generative Pre-trained Transformer GPT is a technology concept, although it’s often mistaken for a product name (with the rise of the wildly popular ChatGPT). LLM Large Language Model An AI model that has been trained using lots of data. Salesforce has their own LLM that outperformed expectations during testing. Salesforce’s LLM leverages Data Cloud, or can be plugged into a different data lake. Organizations can also opt to their own LLM alongside their Salesforce data. NBA Einstein Next Best Action An AI-driven Salesforce product that makes recommendations to users when they are working with records in Salesforce. It appears within a Lightning component that’s typically placed on the record page sidebar. The user can choose to Accept or Reject the recommendation. NLP Natural Language Processing “Artificial intelligence that focuses on how computers can understand, interpret, and generate human language. NLP allows customers to interact with systems using normal human language rather than complex commands.” (source) SAQL Structured Query Language “Use SAQL to access data in Tableau CRM dataset. Tableau CRM uses SAQL behind the scenes in lenses, dashboards, and explorer to gather data for visualizations.” (source) TCRM Tableau CRM Tableau CRM is a self-service data visualization and business intelligence (BI) platform that integrates Salesforce data with external data. Formerly known as Einstein Analytics, and now CRM Analytics, this product boasts some of the most powerful data analysis capabilities in the market. XMD Extended Metadata “Enables you to customize the formatting of dataset fields and their values in Analytics dashboards and lenses.” (source) 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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July 15, 2023in Salesforce
Salesforce JSON
28Jun

Salesforce JSON

Today we are diving into JSON (JavaScript Object Notation) and exploring why it’s a crucial concept for you to understand. JSON is a data representation format widely used across the internet for APIs, configuration files, and various applications JSON Class Contains methods for serializing Apex objects into JSON format and deserializing JSON content that was serialized using the serialize method in this class. Usage Use the methods in the System.JSON class to perform round-trip JSON serialization and deserialization of Apex objects. Roundtrip Serialization and Deserialization Use the JSON class methods to perform roundtrip serialization and deserialization of your JSON content. These methods enable you to serialize objects into JSON-formatted strings and to deserialize JSON strings back into objects. What does JSON serialize do in Salesforce? JSON. serialize() accepts both Apex collections and objects, in any combination that’s convertible to legal JSON. String jsonString = JSON. What is the difference between JSON parse and JSON deserialize? The parser converts the JSON data into a data structure that can be easily processed by the programming language. On the other hand, JSON Deserialization is the process of converting JSON data into an object in a programming language. What is the difference between JSON and XML in Salesforce? JSON supports numbers, objects, strings, and Boolean arrays. XML supports all JSON data types and additional types like Boolean, dates, images, and namespaces. JSON has smaller file sizes and faster data transmission. XML tag structure is more complex to write and read and results in bulky files. Which is more secure XML or JSON? Generally speaking, JSON is more suitable for simple and small data, more readable and maintainable for web developers, faster and more efficient for web applications or APIs, supports native data types but lacks a standard schema language, and is more compatible with web technologies but less secure than XML. What is Salesforce JSON heap size limit? Salesforce enforces an Apex Heap Size Limit of 6MB for synchronous transactions and 12MB for asynchronous transactions. How to store JSON data in Salesforce object? If you need to store the actual JSON payload in Salesforce for audit purposes, Tectonic would recommend just using a Long Text Area field to store JSON content. You wouldn’t have any performance impacts when interacting with records, and if required you could add this to the layout of the child object storing this data. 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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June 28, 2023in Salesforce
Salesforce Nonprofit
25Oct

Salesforce Nonprofit History

In the beginning, there was CRM software; CRM stands for customer relationship management. Sure, that sounds for-profit, but when you stop to think about it, you realize that the technology can help you track your stakeholder relationships too. CRM technology helps teams at any organization collaborate, gather insights, track important metrics, and communicate internally and externally. Salesforce Nonprofit History. Salesforce has taken CRM technology and brought it to the cloud, making it web-based without any software to install. That helps businesses and organizations of all types start using the technology faster and with more ease. For decades, Salesforce has built powerful technology for diverse industries, including nonprofits, schools, and philanthropic organizations. With their help and guidance, Tectonic builds solutions to tackle the world’s biggest problems. Salesforce products and features to help you operate effectively, raise funds, distribute grants, manage program impact, and connect with supporters. Plus, the Power of Us Program helps eligible nonprofits get started with Salesforce. Salesforce Nonprofit History Salesforce for Nonprofits is a complete set of nonprofit technology solutions built to connect your nonprofit with the people who care about your cause. Use it to unlock the knowledge to better track your supporters and programs, and find new, more efficient ways of working to accomplish your mission. The core product in Salesforce for Nonprofits is Nonprofit Cloud, a built-in Salesforce solution with tools for fundraising, program management, case management, and outcome management. For organizations that distribute funds or in-kind grants there’s also Nonprofit Cloud for Grantmaking, which includes everything in Nonprofit Cloud plus tools to manage the grantmaking lifecycle. Alternatively, choose from a number of managed packages that can be installed into Salesforce, such as Nonprofit Success Pack (NPSP). NPSP organizes constituent, fundraising, and program data for nonprofits. Like Related Posts Alphabet Soup of Cloud Terminology As with any technology, the cloud brings its own alphabet soup of terms. This insight will hopefully help you navigate Read more PII Explained Personal Identifiable Information (PII) is defined as: Any representation of information that permits the identity of an individual to whom Read more Can-Spam Explained Despite its name, the CAN-SPAM Act is not limited to bulk email; it encompasses all commercial messages. These messages, defined Read more Business Analysis and Project Management Acronyms Here is a helpful glossary of business analysis and project management acronyms you may encounter when discussing business analysis and Read more

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October 25, 2022in Salesforce for Nonprofits
Salesforce Industries
04Oct

Salesforce Industries Acronyms

Here is a helpful glossary of terms you are likely to encounter when discussing Salesforce Industries (formerly Vlocity). Salesforce Industries Acronyms. Salesforce Industries Acronyms Acronym Meaning Industry Cloud Definition AAR Account-Account Relationships Financial Services Cloud A feature to relate households with businesses and organizations. For example, it can be a relationship between a household and their trust. ABM Account Based Marketing Marketing Cloud and Account Engagement Account based marketing is a marketing strategy targeting accounts that are look-alikes to existing customers of a high value, marketing to a group of individuals in the account. ACR Account-Contact Relationships Financial Services Cloud A feature to build Account-Contact Relationships between their clients and households. For example, it can be a relationship between a household and a member of the household. AUM Assets Under Management Financial Services Cloud “The total market value of the investments that a person or entity manages on behalf of clients.” (source)AUM is featured in the pre-defined reports and dashboards within Salesforce Financial Services Cloud. CCR Contact-Contact Relationships Financial Services Cloud A feature to relate members of the household with other contacts. For example, it can be a member of the household related to their attorney or accountant. CSRD Corporate Sustainability Reporting Directive Net Zero Cloud A prominent regulation mandated by the EU to encourage Net Zero practices. Net Zero Cloud’s CSRD report builder supports companies to comply. DPE Data Processing Engine Financial Services Cloud “The Data Processing Engine is an “Enhanced Rollup-by-Lookup (RBL) framework that uses [the] superior processing power of Tableau CRM for faster calculation of RBL rules.” – an optimized way to transform and update records in Salesforce that is also being utilized as a framework for the RBLs. E&U Energy & Utilities Cloud Energy & Utilities Cloud A solution designed for power and utilities, oil and gas, and even further to green energy options. EDA Education Cloud Architecture Education Cloud Education Cloud is built on the EDA (Education Data Architecture) a pre-built data model, designed for the education sector. This supports institutes to connect each student account to an administrative account, and shows a clear record of any student addresses, relationships, and affiliations. This superseded the Higher Education Pack (HEDA). EPC Enterprise Product Catalog Energy & Utilities Cloud “Introduce and effectively manage a portfolio of products that are relevant to customers, released at the most opportune time, and at a low cost.”READ MORE: Salesforce Help ERM Emergency Response Management Work.com One of the four pillars of Work.com, this app is designed to allocate health, public and private sector resources (program management and incident resolution) aimed towards the public sector and health industries. Perhaps less relevant now than in Covid times, this app still can empower certain sectors (i.e. Public Sector and Nonprofits) for crisis management. ESG Environmental Social Governance Net Zero Cloud Salesforce has developed Net Zero Cloud to be an ESG platform. ESG reporting is typically complex and time-consuming to collate and disclose reports. With this solution, Einstein suggests report content, which alleviates the burden from ESG professionals and is suitable for companies of all sizes and industries. FSC Financial Services Cloud Financial Services Cloud Salesforce developed a set of industry products to enhance and extend the functionality of its core products – the Financial Services Cloud is one example. This Salesforce managed package enhances and extends the functionality of Sales Cloud and Service Cloud combined to meet the needs of wealth management firms, insurance companies, and banks. HEDA Higher Education Data Architecture Education Cloud Education Cloud is built on the EDA (Education Data Architecture). This superseded the Higher Education Pack (HEDA). HEDA is a community-driven data architecture and set of best practices designed to configure Salesforce out of the box for Higher Education. ITSC IT Service Center Work.com Part of Work.com, this tool helps IT teams better support employees from anywhere – a cross-team, cross-company initiative leveraging Tanium’s real-time asset management capabilities, Service Cloud’s case management technology, and the power of the Salesforce Platform for automation, integration, and personalization. NPSP Nonprofit Success Pack Nonprofit Cloud The Nonprofit Success Pack was specifically designed to meet the “unique” needs of Nonprofits, aka NGOs or charities, to aid them in being successful with their mission. There is a lot to unpack just in the name itself! It’s a “Pack” because it consists of several puzzle pieces to meet those needs, sitting on top of Sales Cloud. NZC Net Zero Cloud Net Zero Cloud A solution for carbon accounting, emissions tracking, calculating building energy intensity, and more. PSS Public Sector Solutions Government Cloud The group of applications built on an Experience Cloud infrastructure to enable citizens and institutions log in to a portal and manage their data. RBL Rollup by lookup Financial Services Cloud “Rollup-by-Lookup (RBL) is a feature of Salesforce Financial Services Cloud (FSC) that allows you to aggregate client financial data and rollup to the individual or group level using configuration rules.” Salesforce are moving away from RBL to the Data Processing Engine (DPE). SFI Salesforce Industries – The umbrella term for all industry-specific solutions that Salesforce has released. There are approximately 12 Industry Clouds, which are pre-built data models that enable Salesforce customers operating in these industries to get up and running faster. SID Shared Information Data Communications Cloud “Provides an information/data reference model along with a common vocabulary for implementing business processes. This business model is independent of platform, language or protocol and can help identify business entities that are important to the Communications Service Provider.”(source) VPL Vlocity Process Library – A library of pre‐built business processes that can be used with Vlocity (Salesforce Industry) OmniStudio. (source) Salesforce Industries Acronyms 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

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October 4, 2022in Salesforce

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