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Einstein Copilot for Tableau in Public Beta

Einstein Copilot for Tableau in Public Beta

Salesforce Introduces Einstein Copilot for Tableau in Public Beta In early April, Salesforce unveiled the public beta availability of Einstein Copilot for Tableau, an innovative AI-powered assistant aimed at assisting users across various roles and functions in exploring and interacting with data within Tableau. This groundbreaking tool enables deep dives into data by leveraging Tableau’s analytical engine through natural language queries, accessing data from spreadsheets, cloud and on-premises data warehouses, and Salesforce Data Cloud. The public release of Copilot for Tableau is anticipated to be widely available to customers by summer 2024. Key Features of Einstein Copilot for Tableau Einstein Copilot for Tableau offers several features tailored to enhance user experience and streamline data exploration: Recommended Questions: The assistant automatically analyzes data and suggests relevant questions, allowing users to interact with data effortlessly without the need for specialized data analysis skills. Conversational Data Exploration: Users can iterate and refine their data exploration process seamlessly while maintaining context, enabling them to ask follow-up questions and delve deeper into insights as if they were engaging in a conversation with their data. Guided Calculation Creation: Copilot guides users through the process of creating calculations and parsing information, simplifying complex tasks such as extracting specific data elements from text fields. Enhancing Accuracy and Trust To ensure accuracy and contextual relevance, Einstein Copilot for Tableau leverages trusted company data from Data Cloud, fostering trust among users by delivering precise and relevant outputs based on internal data sources. Future Outlook Salesforce’s approach to introducing generative AI assistants for specific product types and use cases underscores the importance of function-specific training to meet users’ specific needs. As the technology matures, vendors may transition from premium license fees to consumption-based models, reflecting the evolving landscape of AI assistant technology adoption. The rollout of Einstein Copilot for Tableau represents a significant step forward in making data analysis accessible to a broader audience, reinforcing Salesforce’s commitment to innovation and customer-centric solutions in the realm of AI-powered analytics. 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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crm analytics

Build Better Tableau Dashboards

The effort made to build better Tableau dashboards pays tenfold in there readability and usability. “Dashboard design is not about making dashboards ‘pretty. It’s making them functional and helping the user to get the information they need as efficiently as possible.” ALEXANDER WALECZEK, ANALYTICS PRACTICE LEAD AND TABLEAU AMBASSADOR Effective communication with your audience involves considering their needs from start to finish. The key lies in posing the right questions. To convey information to your readers in an engaging manner, it is crucial to grasp fundamental aspects, such as: Possibly, when tailoring content for a time-pressed salesperson with only 15 seconds to spare for crucial performance indicators, it is imperative to present the most vital information in a glance. Additionally, ensuring that the dashboard is mobile-friendly and loads swiftly becomes essential. On the other hand, if your target audience consists of a team set to review quarterly dashboards over an extended period, offering more detailed views of the data might be advisable. Build Better Tableau Dashboards for Your Audience Take into account the expertise level of your audience. Gain a deeper understanding of their skill set by inquiring about their priorities and data consumption habits. This insight is crucial for determining the most effective way to present data, guiding key design decisions. For instance, a novice may require more action-oriented labels for filters or parameters compared to an advanced user. Here are four effective methods to assess the dashboard and data proficiency of your audience: Adjust Your Narrative Adjust your narrative accordingly. Tailoring your dashboards to suit the intended audience enhances their impact. Below are three visualizations depicting the distribution of tornadoes in the United States for the first nine months of the year. The distinction lies in the level of visual information employed to convey the narrative. There might e an extremely minimal presentation, progressing in complexity towards the right. None of these approaches is inherently superior to the others. The minimal visualization on the left might be ideal for audiences well-versed in the subject matter, appreciating simplicity and the elimination of redundancy. On the other hand, for newcomers or individuals viewing the visualization just once, the explicitness of the visualization on the right could be more effective. Determining what constitutes clutter versus essential information is where collaboration with colleagues becomes crucial. Crafting persuasive dashboards involves making a lasting impact on partnership. By closely collaborating with line-of-business stakeholders, you can secure the buy-in and engagement needed to tailor the dashboard to their specific requirements and expectations. This collaborative approach forms the essence of dashboard persuasion. A Work in Progress Demonstrate your process and embrace iterative refinement. Establishing a culture of analytics should be accompanied by a culture of supportive and frequent critique. Creating multiple versions of your work and actively seeking feedback throughout the process will contribute to a superior final product. Avoid isolation and stagnation; share your progress with others, use the feedback to refine your work, and repeat the process until you achieve a satisfactory result. Much like the formation of a diamond requiring extraordinary heat, pressure, and time, the outcome is worth the effort. Encouraging critiques is essential for cultivating a culture of constructive feedback. Trust among colleagues is important, arguably it enables mutual respect and trust in each other’s feedback. Developing a thick skin is also necessary, focusing on designing dashboards that cater to users and clients’ needs rather than personal preferences. Similar to writers who must “kill their darlings,” designers must prioritize the overall effectiveness of the dashboard, making honest assessments and adjustments when needed. “It also helps to have a public place—on a real or virtual wall—for sharing work. Making work public creates constant opportunities for feedback and improvements.” Tableau 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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Einstein Copilot Tableau

Tableau has dedicated over two decades to empowering individuals to visualize and comprehend their data. This mission, driven by data analysts, continues to thrive. Data analysts serve as the cornerstone of organizations fostering a data-centric culture. They capture business needs, prepare data, and craft data content for end-users. Einstein Discovery insights seamlessly integrate into the Tableau workflow, ensuring uninterrupted analysis. The benefits of leveraging Einstein Discovery are manifold: Tableau Einstein represents a groundbreaking advancement in AI-driven data analytics. Einstein Copilot for Tableau, currently in beta for Tableau customers, democratizes AI in data analytics. It collaborates with analysts throughout the analytical process, from data preparation to visualization, reducing entry barriers and enhancing user experience. Einstein Copilot integrates seamlessly into the Tableau environment, serving as an intelligent assistant. It guides users through the creation process, ensuring accuracy and adherence to best practices. With Einstein Copilot, users confidently explore data, identify trends, and communicate findings effectively. The features of Einstein Copilot enhance the data analytics experience and empower users to unleash the full potential of their data. These features include faster insights through recommended questions, streamlined data exploration, improved visualization quality, and guided calculation creation. Einstein Copilot’s development involved overcoming several challenges. These challenges included accurately interpreting user questions, enhancing data intelligence, and automating visualization generation. The team addressed these challenges through continuous refinement of analytical data generation algorithms, leveraging Tableau Public’s vast dataset, and balancing accuracy, speed, and creativity in AI responses. Continuous improvement remains a key focus for the Einstein Copilot team. Through platforms like Zeus, the team systematically enhances engineering, intent detection, and knowledge generation. This iterative process ensures ongoing enhancements to Einstein Copilot’s capabilities, providing users with an increasingly seamless and insightful analytical experience. Einstein Discovery insights are integrated into your Tableau workflow, so you never need to disrupt your analysis. Some of the benefits of using Einstein Discovery include: Data analysis and data-driven decision-making have been part of the vocabulary in organizations over the years. And, while data analysis is one of the most in-demand tech skills sought by employers today, not everyone in an organization has “analyst” in their job title—myself included. Yet, so many of us use data daily to make informed decisions. The rise of generative AI presents a significant opportunity for us to bring transformative benefits to analytics. Businesses are eager to embrace generative AI because it can help save time, provide faster insights, and empower analysts to be even more productive with an AI assistant—freeing analysts to focus on delivering high-quality, data-driven insights. But before any of this can happen, a lot goes on behind the scenes. That’s where Einstein Copilot for Tableau comes in. Einstein Copilot for Tableau, now available for Tableau customers to try in beta, brings the power of AI to data analytics, reducing the barrier to entry and working alongside the analyst—from data preparation to visualization. Whether you’re an experienced data analyst or just starting your journey in data exploration, Einstein Copilot for Tableau becomes your trusted companion, empowering you to unlock insights and make informed decisions with confidence. Einstein Copilot for Tableau offers a range of features that enhance the data analytics experience and empower anyone to unlock the full potential of their data. Look for these features in the coming release, and even more as we continue to build. Faster insights with recommended questions When you are getting started in analytics—whether for work, learning, or just for fun—a blank canvas can be intimidating. Where do you even begin? Using Einstein to suggest questions you can ask of a specific datasource lightens that lift so you can quickly move from connecting to data to finding insights. Einstein Copilot for Tableau does a quick index across your connected datasource to create a summary context of the datasource. This summary is used to generate a few questions the dataset can answer. For example, using a dataset like Tableau’s Superstore practice dataset, Einstein Copilot for Tableau suggests “Are there any patterns over time for sales across product categories?” In one click a line chart is created. Since this is all happening in the authoring experience, users familiar with Tableau’s drag-and-drop interface can adjust anything displayed before saving and moving on to the next question. Combining analyzing data with learning by doing. With recommended questions, anyone can quickly uplevel their analytics skills. What is Einstein Copilot for Tableau? Using generative AI and statistical analysis, Einstein Copilot for Tableau is able to understand the context of your data to create and suggest relevant business questions to help kickstart your analysis. A smart, conversational assistant for Tableau users, Einstein Copilot for Tableau automates data curation—the organization and integration of data collected from various sources—by generating calculations and metadata descriptions. Einstein Copilot for Tableau can fill data gaps and enhance analysis by creating synthetic datasets where real data is limited. Einstein Copilot helps you anticipate outcomes with predictive analytics that simulate diverse scenarios and uncover hidden correlations. Additionally, generative models can bolster data privacy by producing non-traceable data for analysis. Accelerate insights from data with ease Tableau has thousands of features—and with Einstein Copilot’s in-product assistance, you ask questions using natural language, and from data prep and writing calculations to formatting worksheets and dashboards using your company brand guidelines, Einstein Copilot automates many time-consuming, repetitive tasks—increasing analyst productivity and speeding time-to-insights. Jumpstart data exploration Einstein Copilot for Tableau is a great tool for both data-savvy end users and data professionals. With the help of Einstein Copilot, you can ask more in-depth questions about the data insights without having to know all of the technical aspects of Tableau. In the worksheet, a set of recommended questions based on the data source’s metadata makes it easy for users to start analyzing their data. Einstein Copilot’s step-by-step guidance also helps new data professionals learn how to use Tableau effectively—with an opportunity for both novice and experienced users to increase their learn by doing. Improve viz and dashboard quality through prescriptive guidance With Einstein Copilot in Tableau, you

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Tableau's Einstein Copilot

Tableau’s Einstein Copilot

Tableau’s Einstein Copilot: Streamlining Data Analysis with AI Tableau, on its mission to empower individuals in comprehending and interpreting their data for over two decades, has found success thanks to data analysts. These professionals, integral to organizations fostering a data-centric culture, capture business requirements, prepare data, and craft data content for end users. While data analysis and data-driven decision-making have become commonplace in organizational discourse, not everyone with a stake in data utilization holds the title of “analyst.” Many individuals, those of us at Tectonic included, leverage data daily to make informed decisions. The advent of generative AI presents a compelling opportunity to bring transformative benefits to analytics. Businesses are keen to embrace generative AI due to its time-saving capabilities, faster insights, and the potential to empower analysts further through an AI assistant, allowing them to focus on delivering high-quality, data-driven insights. Facilitating this transformation is Einstein Copilot in Tableau. Tableau’s Einstein Copilot Einstein Copilot in Tableau harnesses generative AI and statistical analysis to understand the context of your data. It creates and suggests relevant business questions, kickstarting your analysis. As a smart, conversational assistant for Tableau users, Einstein Copilot automates data curation—organizing and integrating data from diverse sources—by generating calculations and metadata descriptions. Einstein Copilot fills data gaps, enhances analysis with synthetic datasets in the absence of real data, anticipates outcomes through predictive analytics, and ensures data privacy by generating non-traceable data for analysis. It upholds the promise of generative AI, offering an efficient, insightful, and ethical approach to data analytics—an intelligent assistant seamlessly integrated into the Tableau suite for users at all levels of expertise. Accelerating Insights with Ease With thousands of features, Tableau simplifies the data analysis process. Einstein Copilot, through in-product assistance, allows users to ask questions in natural language. From data preparation to writing calculations and formatting worksheets and dashboards in line with company brand guidelines, Einstein Copilot automates many time-consuming, repetitive tasks, boosting analyst productivity and speeding up time-to-insights. Jumpstarting Data Exploration Einstein Copilot is an invaluable tool for both data-savvy end users and professionals. It enables users to ask in-depth questions about data insights without requiring intricate Tableau technical knowledge. In the worksheet, recommended questions based on the data source’s metadata facilitate data analysis. Einstein Copilot’s step-by-step guidance aids new data professionals in learning Tableau effectively while offering opportunities for both novice and experienced users to enhance their skills. Enhancing Visualization Quality Einstein Copilot provides built-in visual best practice guidance, enabling users to format visualizations using simple natural language prompts and simplifying complex, time-consuming tasks. Crucially, human involvement remains a vital part of the process, ensuring thorough checks before accepting any proposed responses. Whether exploring data or creating dashboards, users can confidently navigate each step with assistance always available. Privacy, Security, and Accuracy Built with privacy, security, and accuracy in mind, Einstein Copilot assures users of a reliable AI-powered assistant. Future updates will introduce Pulse Metrics generation, Slack integration for sharing insights, and additional context to insights before sharing them. Einstein Copilot in Tableau is set to be generally available in Summer ’24 with Tableau 2024.2. For those interested in participating in the pilot, a form is available for sign-up in Spring ’24. Witness the transformative potential of Einstein Copilot in Tableau through the demo showcasing its ability to revolutionize analytics. By Tectonic’s Salesforce Marketing Consultant, Shannan Hearne Like1 Related Posts Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more Salesforce AI Einstein Next Best Action Salesforce AI Einstein Next Best Action is a feature designed to identify the most effective actions available to agents and Read more Einstein Relationship Insights Setting Up Einstein Relationship Insights: Configure ERI Insights to empower your sales team in managing relationships among individuals, companies, and Read more Joined Datasets in B2B Marketing Analytics B2B Marketing Analytics (B2BMA) datasets comprise source data that has been formatted and optimized by the B2B Marketing Analytics app Read more

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Salesforce data success

The Long and Winding Data Success Road

Long and Winding Data Success Road Fostering a Data-Driven Culture for Informed Decision-Making Enhancing trust in data goes beyond technical solutions; it hinges on cultivating a culture that instills confidence and fosters widespread adoption. Data culture, defined as the collective behaviors and beliefs of individuals who value, practice, and promote data usage for improved decision-making, empowers all members of an organization with insights to address complex business challenges. Key Insights: Redefining Data Governance for Trustworthiness Data governance extends beyond a mere set of rules and restrictions; strategically employed, it becomes a vital tool for reinforcing data trustworthiness. An impressive 85% of analytics and IT leaders use data governance to ensure and certify baseline data quality. It entails establishing rules or policies governing the collection, management, storage, measurement, and communication of information, setting parameters for data access, accuracy, privacy, security, and retention. Governance in Action: A Multi-Pronged Approach Defying Data Gravity Data gravity, the notion that accumulating large data volumes in a specific location or system attracts additional applications and services, poses challenges for data relocation. Leaders in analytics and IT adopt a multi-pronged approach, employing an average of 3.2 different strategies to counteract data gravity. Strategies to Mitigate Data Gravity: Like1 Related Posts CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more Capture Initial Traffic Source With Google Analytics To ensure the proper sequencing of Tags, modify the Tag sequencing in the Google Analytics preview Tag settings. The custom Read more Snowflake and Salesforce with Embed Snowflake has deepened its partnership with investor Salesforce by introducing two tools that seamlessly connect their cloud-native systems. Snowflake and Read more

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Tableau Pulse

Tableau Dashboard Design Tips

Better Tableau Dashboard Design Tips. Eight strategies for crafting engaging and delightful Tableau dashboards: Creating dashboards using Tableau Dashboard Design Tips makes for better user experience. “It’s easy to be distracted by formatting and finding the perfect color, size, and position for elements. It’s best to do this towards the end, after reviews by the end users, to not waste effort because entire charts suddenly change and all formatting is lost.” ALEXANDER WALECZEK, ANALYTICS PRACTICE LEAD AND TABLEAU AMBASSADOR 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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Salesforce Tableau Pulse

Tableau Pulse

Tableau Pulse, fueled by Tableau Artificial Intelligence and exclusive to Tableau Cloud, revolutionizes the data ingestion experience. The ability to empower business users with intelligent, personalized insights seamlessly integrated into their workflows. Whereas once upon a time AI for the lay user was about as friendly as asking Siri a question which she Googles for an answer and reads back to you. It saves a few clicks and a little typing, but it isn’t exactly thinking outside of the box – or phone. In the current data analytics demanding world, characterized by generative AI, the Internet of Things (IoT), and automation, the landscape is evolving. Data is at the core of these transformative technologies, and our interaction with said data is changing rapidly. As businesses worldwide confront an inflection point, embracing data-driven decision-making becomes crucial for staying competitive and building robust customer relationships. Tableau Pulse is a reimagined data experience, democratizing data accessibility for all users, irrespective of their familiarity with data visualization tools. Exclusively available to Tableau Cloud users, Tableau Pulse harnesses Tableau AI’s power to deliver more personalized, contextual, and intelligent data experiences in an easy-to-understand format. Key Features of Tableau Pulse: Upcoming Tableau Pulse Features in 2024: Tableau Pulse aims to breathe new life into analytics for everyone, capitalizing on the potential of generative AI, automation, and sensors to redefine how businesses interact with data. In a landscape where success hinges on data utilization, Tableau Pulse is poised to empower every employee with personalized, contextual, and intelligent insights directly within their workflow, fostering a truly data-driven organizational culture. Imaging the industry specific use cases for travel and tourism, manufacturing, health and life sciences, and the public sector? If you have data you aren’t able to utilize, reach out to Tectonic today to discover how Tableau Pulse could solve your challenges. 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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Tableau Pulse

Effectively Using Tableau Pulse

Here are several tips to guide you in effectively using Tableau Pulse: Begin with essential metrics, allowing users to adapt to Pulse gradually before introducing more features. 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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Salesforce Tableau Pulse

Examples of Tableau Pulse Value

Tableau Pulse simplifies data exploration and visualization. We currently live in a powerful analytics era, marked by transformative technologies such as generative AI, the Internet of Things (IoT), and automation. Tableau Pulse Value is reshaping the analytics landscape. At the core of these technologies lies data, and the way we interact with it is undergoing significant and constant changes. The swift evolution of these technologies presents a magical moment for businesses and organizations globally—a moment of decisive action.  To remain competitive and foster robust customer relationships, businesses must embrace data-driven decision-making. The performance gap between entities adept at leveraging data and those that lag behind is set to expand exponentially. Businesses unable to harness the power of their data risk falling behind, and the pace of this shift may be more rapid than anticipated. Exclusively available for Tableau Cloud users, Tableau Pulse harnesses the capabilities of Tableau AI to present data in ways that are more personalized, contextual, and intelligent. Tableau Pulse introduces the capabilities of a Metrics Layer, or headless BI, to Tableau’s platform, allowing the definition of metrics and KPIs once for universal use within the organization. This not only streamlines the work of analysts but also guarantees that teams adhere to consistent, trusted figures from a singular source of truth. Sitting Atop the Metrics Layer: Atop the Metrics Layer, an Insights platform operates as a statistical service that automatically generates insights based on the defined Metrics. These insights are ranked and presented in natural language using generative AI. The service also facilitates user interaction with insights, offering guided follow-up questions that surface proactively and align with the context of the data. Tableau Pulse goes further by delivering Next-Gen Experiences, presenting data through intuitive, user-friendly metrics directly integrated into users’ workflow in platforms like Slack, email, Tableau web app, and more. This approach allows for swift scalability across the business as users explore, follow, and share pertinent metrics akin to social media content. Generative AI-powered insight summaries assist users in focusing on key data highlights, ensuring the identification of important patterns, trends, outliers, and data changes. Generative AI plays a crucial role in enhancing each layer of Tableau Pulse, making it more accessible for users to discover relevant metrics, create new metrics, comprehend insights, pose questions, perform root cause analysis, and connect data to real-world contexts. Tableau dashboards can be infused with real-world AI and machine learning with tools like Aible. Considering, Tableau Pulse makes data more accessible to everyone regardless of their expertise with data visualization tools. Tableau Pulse Use Cases: Here are instances illustrating how Tableau Pulse, powered by Tableau GPT, enhances intelligent data experiences: Example 1: Service Leader A service leader receives a digest of metrics they monitor, providing relevant insights to stay informed about their business’s performance. Tableau Pulse alerts the leader to an unusual decrease in their team’s CSAT score, identifying potential causes like a high volume of active tickets and extended response times. When the leader has inquiries, Tableau Pulse facilitates a quick and easy analysis, enabling them to delve into the situation. Subsequently, they can share these details with colleagues on Slack, fostering collaboration and prompt action. Example 2: Commerce Leader A commerce leader tracks metrics such as conversion rate, average order value, and customer lifetime value. Tableau GPT detects any deviations in these metrics, investigates the reasons for the changes, and suggests actionable steps for the leader. By running an analysis on the data, Tableau GPT presents comprehensive information visually, allowing the leader to make informed decisions and take necessary actions. Tableau Pulse Value Throughout 2024, Tableau will release additional features that will provide even more value to those using Tableau Pulse, including: Tableau business science is a new class of AI-powered analytics that brings data science capabilities to business domain experts. Using AI, machine learning, and other statistical methods to solve business problems has largely been the purview of data scientists. 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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Salesforce Service Cloud Intelligence

Salesforce Service Cloud Service Intelligence Enhancements

Service Intelligence, a data-centric solution, showcases vital performance metrics within the contact center. Recent Service Intelligence Enhancements have given even greater insights. In a significant launch, Salesforce introduced Service Intelligence. Service Intelligence an advanced analytics app for Service Clou. It is aimed at boosting agent efficiency, reducing costs, and elevating customer satisfaction. Service Intelligence Enhancements and updates within this Salesforce product aim to bolster operational efficiency and take customer satisfaction to unprecedented heights. Representing a new milestone for Service Cloud, the Winter ’24 innovations redefine how businesses approach customer service and optimize operations. Fueled by Data Cloud, Salesforce’s real-time hyperscale data engine, Service Intelligence provides users with direct access to all their data within Service Cloud, eliminating the need to switch between screens for information. Pre-built and customizable dashboards in Service Intelligence offer a comprehensive view of essential metrics, including customer satisfaction and individual and team workloads. With Einstein Conversation Mining, service professionals can leverage AI to analyze customer chat and email conversations, uncover insights, assess the likelihood of complaint escalation, and proactively address issues with customers. The relevance of AI is emphasized, with an 88% increase in AI adoption among service professionals from 2020 to 2022. With 63% acknowledging that AI will help them serve customers faster. Service professionals are embracing AI enabling to make informed decisions swiftly, gaining a competitive edge. Service Intelligence Enhancements As of 2023, Service Intelligence is now generally available. Key features include pre-built service dashboards offering AI-powered insights through Einstein Conversation Mining, providing visibility into key metrics across cases. Einstein Conversation Mining employs AI to analyze customer conversations. Einstein Conversation mining enables quick identification of trends and top customer issues. Tableau integration allows users to seamlessly explore data in Tableau directly from a Service Intelligence dashboard, maintaining data context from their service console. Service Intelligence encompasses Data Cloud, CRM Analytics, and Einstein Conversation Mining. There by offering a wealth of information such as customer data and key performance indicators (KPIs) to help service teams enhance operations and reduce costs. Einstein for Service accelerates customer communication and satisfaction by generating email responses based on knowledge articles. The Winter ’24 release introduces the Lightning Article Editor and Article Customization in Salesforce Service Cloud, marking a significant advancement in knowledge management. The Lightning Article Editor simplifies content creation and editing. Thus enabling support and customer service teams to produce informative material efficiently. These enhancements in Service Cloud streamline operations, empower agent performance, and usher in a new era of customer satisfaction. Explore these exciting updates to transform your organization’s strategy. Embrace the future of service excellence with the Winter ’24 release for Service Cloud. Like Related Posts 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 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more

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Tableau CRM Refresh Button With LWC

Tableau CRM Refresh Button With LWC

Revitalize your Tableau CRM (formerly known as Einstein Analytics) dashboards with a custom Refresh button, enhancing user experience and analytical efficiency. This button serves as a simple yet powerful tool to reset applied filters and revert the dashboard to its default state, facilitating seamless exploration of data insights. Tableau CRM Refresh Button With LWC. What exactly is a Tableau CRM Refresh Button With LWC? It’s a user interface component that, upon activation, clears all applied filters, restoring the dashboard to its initial configuration. This feature proves particularly beneficial in scenarios where users seek to initiate fresh analyses or when dealing with intricate filter structures. To embark on this enhancement journey, you’ll require three essential components: Once equipped, follow these steps to integrate the Refresh button seamlessly: Step 1: Crafting a Lightning Web Component (LWC) Initiate the creation process by developing a Lightning Web Component (LWC) within Salesforce. This component will seamlessly embed into your Tableau CRM dashboard. Step 2: Designing the HTML Framework Within the HTML file of your LWC (let’s name it refreshButton.html), define the structural blueprint for your button. Below is a sample markup: phpCopy code<template> <div class=”reset-btn_container”> <lightning-button variant=”base” label=”&#xe912;” aria-label=”Clear Filters” onclick={clearFilters} class=”slds-m-right_x-small hpe-icon-button hpe-icon-bare” ></lightning-button> </div> </template> This markup establishes a container for the button, utilizing a lightning-button element to create the button itself. Key attributes such as label, variant, and onclick event handler are set accordingly. Step 3: Implementing JavaScript Logic In the JavaScript file of your LWC (refreshButton.js), define the logic to execute filter clearance upon button activation. Here’s an illustrative example: typescriptCopy codeimport { LightningElement, api, track } from ‘lwc’; export default class DceResetDashboardButton extends LightningElement { @api getState; @api setState; @api refresh; @track initialState = null; clearFilters() { const {state, pageId} = this.getState(); const newState = { state: { …state, datasets: this.initialState.state.datasets, steps: Object.fromEntries(Object.entries(state.steps).map(([k, v]) => { return [k, { …v, values: [] }] })), }, pageId, } this.setState({ …newState, replaceState: true }); } connectedCallback() { this.initialState = this.getState(); } } This JavaScript snippet encompasses crucial elements such as property definition, filter clearance methodology, and initialization of the dashboard’s initial state. Step 4: Deploying the Lightning Web Component With your LWC crafted, proceed to deploy it within your Salesforce organization. Step 5: Integrating the LWC into Your Dashboard Edit your Tableau CRM dashboard, adding a new “Custom Component” widget and configuring it to utilize your deployed LWC as the custom component. Step 6: Testing Your Refresh Button Upon completion, navigate to your Tableau CRM dashboard to confirm the presence of the Refresh Button. A simple click on this button will swiftly clear all filters, providing a seamless experience for resetting your analysis. By incorporating this Refresh button into your Tableau CRM dashboard, you enhance user satisfaction and analytical agility. Take advantage of this tutorial to elevate your dashboards and witness the appreciation from your users firsthand! If you need assistance building a refresh button in your Tableau CRM dashboard, contact Tectonic today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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Modern Cloud Analytics

Modern Cloud Analytics

Unlocking the Power of Modern Cloud Analytics: A Tableau and AWS Initiative According to IDC research, analytics spending on the cloud is growing eight times faster than other deployment types. A comprehensive cloud technology stack supports data integration, self-service analytics, and essential use cases for digital transformation and analytics at scale. To help customers harness the power of cloud-based self-service analytics, Tableau continues to invest in its Modern Cloud Analytics initiative, launched at the Tableau Conference in 2019. What is Modern Cloud Analytics? Modern Cloud Analytics (MCA) combines the expertise and resources of Tableau, Amazon Web Services (AWS), and their partner networks. This collaboration maximizes the value of end-to-end data and analytics investments, from data strategy and migration to operational optimization. MCA helps organizations at any digital transformation stage securely deploy and scale cloud analytics, delivering faster time to value and reduced costs with validated migration processes that mitigate risk. Core Product Integration and Connectivity Tableau integrates seamlessly with AWS services, providing a complete solution for analyzing data stored in Amazon’s infrastructure. Key integrations include: Amazon S3 Connector: Leveraging Tableau’s Hyper in-memory data engine, this connector reads Parquet or CSV files directly from Amazon S3, eliminating the need for Hyper extracts. Available in Tableau Cloud and Tableau Exchange.Amazon Athena Connector: Now supports third-party identity providers (IdP) like Azure AD and Okta, offering secure and flexible authentication with multi-factor options.Amazon OpenSearch Connector: Developed by the Amazon OpenSearch Service team, available on Tableau Exchange.Amazon DocumentDB Connector: Created by the Amazon DocumentDB Service team, featured on Tableau Exchange.Amazon Neptune Connector: Developed by the Amazon Neptune Service team, available on Tableau Exchange. Skip Server Administration with Tableau CloudTableau Cloud, hosted on AWS, offers significant cost savings and performance improvements. “With Tableau Cloud, we’re saving over $300,000 annually in server and platform administration costs, with dashboard performance improving by 2x,” said Raj Seenu, Senior Director of Data Technologies at Splunk. This platform allows IT and data engineers to focus on other critical tasks, demonstrating a cloud-first approach. Splunk anticipates doubling its enterprise analytics adoption by the end of 2021. Getting Started with Modern Cloud AnalyticsThe MCA program assists customers in migrating data and analytics workloads to AWS, unlocking the benefits of a cloud-based analytics strategy. *Source: IDC InfoBrief, sponsored by Tableau and AWS, Cloud Business Intelligence and Analytics, doc #US46135420TM, April 2020. 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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Salesforce Success Story

Case Study: Google Cloud and Tableau Ecommerce Success

An industry leader in lifesciences research and ecommerce, is tasked with integrating recent acquisitions, standardizing processes, and improving marketing return-on-investment. Ecommerce company moves to the cloud and adopts Google Cloud and Tableau to improve sales and operational efficiency. Google Cloud and Tableau Ecommerce Success to the rescue. Industry: Lifesciences and Biotechnology Research Problem: Leadership requested help driving an improved culture of proactive decision-making, rather than reactive. Implemented : Our solution? Results: Salesforce offers customized solutions for the ecommerce industry, assisting companies in this field to provide outstanding customer experiences, optimize workflows, and spur growth and brand loyalty. Salesforce offers digital transformation technology for life sciences, ecommerce, and biotechnology research industries. If you are considering a Salesforce health and life sciences implementation, contact Tectonic today. Like2 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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