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Google and Salesforce Expand Partnership

Google and Salesforce Expand Partnership

Google and Salesforce Expand Partnership to Enhance AI Agent Capabilities Google and Salesforce are deepening their collaboration to provide customers with greater flexibility in AI agent deployment. This expanded partnership will integrate Google Gemini within Salesforce’s Agentforce platform, enabling AI agents to process images, audio, and video with advanced multimodal capabilities. Enhanced AI Functionality with Gemini Through this integration, AI agents will gain access to Gemini’s powerful models, allowing them to handle complex tasks with extended context windows and leverage real-time insights from Google Search via Vertex AI. This collaboration aims to empower businesses with AI solutions that are not limited to a single model provider, offering crucial flexibility in AI customization. Srini Tallapragada, Salesforce’s President and Chief Engineering and Customer Success Officer, emphasized that the integration offers customers the ability to choose the applications and models that best suit their needs. “Salesforce offers a complete enterprise-grade agentic AI platform that makes it easy to deploy new capabilities quickly and realize business value fast. Google Cloud is a pioneer in enterprise agentic AI, offering some of the most powerful models, agents, and AI development tools on the planet. Together, we are creating the best place for businesses to scale with digital labor.” Key Benefits of the Integration The partnership is set to deliver significant advantages for businesses, as outlined in the official announcement: Thomas Kurian, CEO of Google Cloud, highlighted the benefits of this collaboration: “Our mutual customers have asked for seamless integration across Salesforce and Google Cloud. This expanded partnership enables them to accelerate AI transformations with state-of-the-art AI models, agentic AI, and advanced data analytics.” Strengthening Customer Service Integrations The partnership will also enhance the connection between Salesforce Service Cloud and Google Cloud’s Customer Engagement Suite, providing AI-driven improvements to customer support. Key upcoming features include: Expanding AI-Powered Decision-Making Beyond Gemini, Agentforce will integrate Google Search through Vertex AI, leveraging secure connections between Salesforce Data Cloud and Google BigQuery. This will enable AI agents to access real-time information for improved accuracy and decision-making. For example, in supply chain management, AI can track shipments, monitor inventory in Salesforce Commerce Cloud, and anticipate disruptions using real-time data on weather, port congestion, and geopolitical events. Additionally, joint customers will be able to utilize Salesforce’s unified platform—including Agentforce, Data Cloud, and Customer 360—on Google Cloud’s AI-optimized infrastructure. This integration ensures enhanced security through dynamic grounding, zero data retention, and toxicity detection via the Einstein Trust Layer. Businesses will also soon have the option to purchase Salesforce products via the Google Cloud Marketplace. More AI Innovations from Google and Salesforce Google recently announced the development of a personalized AI-powered chatbot that will be integrated into its devices, including smartphones, laptops, and tablets. This tool will automatically answer calls, process requests, and respond on behalf of users. Meanwhile, Salesforce’s Service Assistant—formerly known as Salesforce Service Planner—has launched on Service Cloud. Designed to support live agents, it generates step-by-step plans for resolving customer inquiries by analyzing intent, case history, and customer context. For optimal performance, Salesforce recommends integrating it with Data Cloud and the contact center knowledge base. With this expanded partnership, Google and Salesforce are setting the stage for businesses to leverage cutting-edge AI technology, driving innovation and operational efficiency across industries. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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salesforce end to end

Salesforce and Google Announcement

Salesforce (NYSE:CRM) has entered into a deal with Google (NASDAQ:GOOGL) to offer its customer relations management software, Agentforce artificial intelligence assistants, and Data Cloud offerings through Google Cloud, the companies announced today. Google and Salesforce already have many of the same clients, and this new deal will allow for more product integration between Google Workspace and Salesforce’s customer relationship management and AI offerings. Salesforce already uses Amazon (AMZN) Web Services for much of its cloud computing. “Our mutual customers have asked us to be able to work more seamlessly across Salesforce and Google Cloud, and this expanded partnership will help them accelerate their AI transformations with agentic AI, state-of-the-art AI models, data analytics, and more,” said Thomas Kurian, CEO of Google Cloud. The deal is expected to total $2.5B over the next seven years, according to a report by Bloomberg. Salesforce and Google today announced a major expansion of their strategic partnership, delivering choice in the models and capabilities businesses use to build and deploy AI-powered agents. In today’s constantly evolving AI landscape, innovations like autonomous agents are emerging so quickly that businesses struggle to keep pace. This expanded partnership provides crucial flexibility, empowering customers to develop tailored AI solutions that meet their specific needs, rather than being locked into a single model provider. Google Cloud is at the forefront of enterprise AI innovation with millions of developers building with Google’s cutting-edge Gemini models and on Google Cloud’s AI-optimized infrastructure. This expanded partnership will empower Salesforce customers to build Agentforce agents using Gemini and to deploy Salesforce on Google Cloud. This is an expansion of the existing partnership that allows customers to use data from Data Cloud and Google BigQuery bi-directionally via zero-copy technology—further equipping customers with the data, AI, trust, and actions they need to bring autonomous agents into their businesses. Additionally, this integration empowers Agentforce agents with the ability to reference up-to-the-minute data, news, current events, and credible citations, substantially enhancing their contextual awareness and ability to deliver accurate, evidence-backed responses. For example, in supply chain management and logistics, an agent built with Agentforce could track shipments and monitor inventory levels in Salesforce Commerce Cloud and proactively identify potential disruptions using real-time data from Google Search, including weather conditions, port congestion, and geopolitical events. Availability is expected in the coming months. AI: Unlocking the Power of Choice and Flexibility with Gemini and Agentforce Businesses need the freedom to choose the best models for their needs rather than be locked into one vendor. In 2025, Google’s Gemini models will also be available for prompt building and reasoning directly within Agentforce. With Gemini and Agentforce, businesses will benefit from: For example, an insurance customer can submit a claim with photos of the damage and an audio voicemail from a witness. Agentforce, using Gemini, can then help the insurance provider deliver better customer experiences by processing all these inputs, assessing the claim’s validity, and even using text-to-speech to contact the customer with a resolution, streamlining the traditionally lengthy claims process. Availability is expected this year. Trust: Salesforce Platform deployed on Google Cloud Customers will be able to use Salesforce’s unified platform (Agentforce, Data Cloud, Customer 360) on Google Cloud’s highly secure, AI-optimized infrastructure, benefiting from features like dynamic grounding, zero data retention, and toxicity detection provided by the Einstein Trust Layer. Once Salesforce products are available on Google Cloud, customers will also have the ability to procure Salesforce offerings through the Google Cloud Marketplace, opening up new possibilities for global businesses to optimize their investments across Salesforce and Google Cloud and benefiting thousands of existing joint customers. Action: Enhanced Employee Productivity and Customer Service with AI-Powered Integrations Millions use Salesforce and Google Cloud daily. This partnership prioritizes choice and flexibility, enabling seamless cross-platform work. New and deeper connections between platforms like Salesforce Service Cloud and Google Cloud’s Customer Engagement Suite, as well as Slack and Google Workspace, will empower AI agents and service representatives with unified data access, streamlined workflows, and advanced AI capabilities, regardless of platform. Salesforce and Google Cloud are deeply integrating their customer service platforms—Salesforce Service Cloud and Google Cloud’s Customer Engagement Suite—to create a seamless and intelligent support experience. Expected later this year, this unified approach empowers AI agents in Service Cloud with: Salesforce and Google Cloud are also exploring deeper integrations between Slack and Google Workspace, boosting productivity and creating a more cohesive digital workspace for teams and organizations. The companies are currently exploring use cases such as: Expanding Partnership Capabilities and Integrations This partnership goes beyond core product integrations to deliver a more connected and intelligent data foundation for businesses. Expected availability throughout 2025: This landmark partnership between Salesforce and Google represents a strategic paradigm shift in enterprise AI deployment, emphasizing infrastructure innovation, AI capability enhancement, and enterprise value. The integration of Google Search grounding provides a unique competitive advantage, offering real-time, factual responses backed by the world’s most comprehensive search engine. The companies are committed to ongoing innovation and deeper collaboration to empower businesses with even more powerful solutions. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Cortex Framework Integration with Salesforce (SFDC)

Cortex Framework Integration with Salesforce (SFDC)

Cortex Framework: Integration with Salesforce (SFDC) This insight outlines the process of integrating Salesforce (SFDC) operational workloads into the Cortex Framework Data Foundation. By integrating Salesforce data through Dataflow pipelines into BigQuery, Cloud Composer can schedule and monitor these pipelines, allowing you to gain insights from your Salesforce data. Cortex Framework Integration with Salesforce explained. Prerequisite: Before configuring any workload integration, ensure that the Cortex Framework Data Foundation is deployed. Configuration File The config.json file in the Cortex Framework Data Foundation repository manages settings for transferring data from various sources, including Salesforce. Below is an example of how Salesforce workloads are configured: jsonCopy code”SFDC”: { “deployCDC”: true, “createMappingViews”: true, “createPlaceholders”: true, “datasets”: { “cdc”: “”, “raw”: “”, “reporting”: “REPORTING_SFDC” } } Explanation of Parameters: Parameter Meaning Default Value Description SFDC.deployCDC Deploy CDC true Generates Change Data Capture (CDC) processing scripts to run as DAGs in Cloud Composer. SFDC.createMappingViews Create mapping views true Creates views in the CDC processed dataset to show the “latest version of the truth” from the raw dataset. SFDC.createPlaceholders Create placeholders true Creates empty placeholder tables if they aren’t generated during ingestion, ensuring smooth downstream reporting deployment. SFDC.datasets.raw Raw landing dataset (user-defined) The dataset where replication tools land data from Salesforce. SFDC.datasets.cdc CDC processed dataset (user-defined) Source for reporting views and target for records processed by DAGs. SFDC.datasets.reporting Reporting dataset for SFDC “REPORTING_SFDC” Name of the dataset accessible for end-user reporting, where views and user-facing tables are deployed. Salesforce Data Requirements Table Structure: Loading SFDC Data into BigQuery The Cortex Framework offers several methods for loading Salesforce data into BigQuery: CDC Processing The CDC scripts rely on two key fields: You can adjust the CDC processing to handle different field names or add custom fields to suit your data schema. Configuration of API Integration and CDC To configure Salesforce data integration into BigQuery, Cortex provides the following methods: Example Configuration (settings.yaml): yamlCopy codesalesforce_to_raw_tables: – base_table: accounts raw_table: Accounts api_name: Account load_frequency: “@daily” Data Mapping and Polymorphic Fields Cortex Framework supports mapping data fields to the expected format. For example, a field named unicornId in your source system would be mapped to AccountId in Cortex with the string data type. Polymorphic Fields: Fields whose names vary but have the same structure can be mapped in Cortex using [Field Name]_Type, such as Who_Type for the Who.Type field in the Task object. Modifying DAG Templates You can customize DAG templates as needed for CDC or raw data processing. To disable CDC or raw data processing from API calls, set deployCDC=false in the configuration file. Setting Up the Extraction Module Follow these steps to set up the Salesforce to BigQuery extraction module: Cloud Composer Setup To run Python scripts for replication, install the necessary Python packages depending on your Airflow version. For Airflow 2.x: bashCopy codegcloud composer environments update my-composer-instance –location us-central1 –update-pypi-package apache-airflow-providers-salesforce>=5.2.0 Security and Permissions Ensure Cloud Composer has access to Google Secret Manager for retrieving stored secrets, enhancing the security of sensitive data like passwords and API keys. Conclusion By following these steps, you can successfully integrate Salesforce workloads into Cortex Framework, ensuring a seamless data flow from Salesforce into BigQuery for reporting and analytics. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Data Cloud and Zero Copy

Salesforce Data Cloud and Zero Copy

As organizations across industries gather increasing amounts of data from diverse sources, they face the challenge of making that data actionable and deriving real-time insights. With Salesforce Data Cloud and zero copy architecture, organizations can streamline access to data and build dynamic, real-time dashboards that drive value while embedding contextual insights into everyday workflows. A session during Dreamforce 2024 with Joanna McNurlen, Principal Solution Engineer for Data Cloud at Salesforce, discussed how zero copy architecture facilitates the creation of dashboards and workflows that provide near-instant insights, enabling quick decision-making to enhance operational efficiency and competitive advantage. What is zero copy architecture?Traditionally, organizations had to replicate data from one system to another, such as copying CRM data into a data warehouse for analysis. This approach introduces latency, increases storage costs, and often results in inconsistencies between systems. Zero copy architecture eliminates the need for replication and provides a single source of truth for your data. It allows different systems to access data in its original location without duplication across platforms. Instead of using traditional extract, transform, and load (ETL) processes, systems like Salesforce Data Cloud can connect directly with external databases, such as Google Cloud BigQuery, Snowflake, Databricks, or Amazon Redshift, for real-time data access. Zero copy can also facilitate data sharing from within Salesforce to other systems. As Salesforce expands its zero copy partner network, opportunities to easily connect data from various sources will continue to grow. How does zero copy work?Zero copy employs virtual tables that act as blueprints for the data structure, enabling queries to be executed as if the data were local. Changes made in the data warehouse are instantly visible across all connected systems, ensuring users always work with the latest information. While developing dashboards, users can connect directly to the zero copy objects within Data Cloud to create visualizations and reports on top of them. Why is zero copy beneficial?Zero copy allows organizations to analyze data as it is generated, enabling faster responses, smarter decision-making, and enhanced customer experiences. This architecture reduces reliance on data transformation workflows and synchronizations within both Tableau and CRM Analytics, where organizations have historically encountered bottlenecks due to runtimes and platform limits. Various teams can benefit from the following capabilities: Unlocking real-time insights in Salesforce using zero copy architectureZero copy architecture and real-time data are transforming how organizations operate. By eliminating data duplication and providing real-time insights, the use of zero copy in Salesforce Data Cloud empowers organizations to work more efficiently, make informed decisions, and enhance customer experiences. Now is the perfect time to explore how Salesforce Data Cloud and zero copy can elevate your operations. Tectonic, a trusted Salesforce partner, can help you unlock the potential of your data and create new opportunities with the Salesforce platform. Connect with us today to get started. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Collaborative Business Intelligence

Collaborative Business Intelligence

Collaborative Business Intelligence: Connecting Data and Teams In today’s data-driven world, the ability to interact with business intelligence (BI) tools is essential for making informed decisions. Collaborative business intelligence (BI), also known as social BI, allows users to engage with their organization’s data and communicate with data experts through the same platforms where they already collaborate. While self-service BI empowers users to generate insights, understanding the data’s context is critical to avoid misunderstandings that can derail decision-making. Collaborative BI integrates BI tools with collaboration platforms to bridge the gap between data analysis and communication, reducing the risks of misinterpretation. Traditional Business Intelligence Traditional BI involves the use of technology to analyze data and present insights clearly. Before BI platforms became widespread, data scientists and statisticians handled data analysis, making it challenging for non-technical professionals to digest the insights. BI evolved to automate visualizations, such as charts and dashboards, making data more accessible to business users. Previously, BI reports were typically available only to high-level executives. However, modern self-service BI tools democratize access, enabling more users—regardless of technical expertise—to create reports and visualize data, fostering better decision-making across the organization. The Emergence of Collaborative BI Collaborative BI is a growing trend, combining BI applications with collaboration tools. This approach allows users to work together synchronously or asynchronously within a shared platform, making it easier to discuss data reports in real time or leave comments for others to review. Whether it’s through Slack, Microsoft Teams, or social media apps, users can receive and discuss BI insights within their usual communication channels. This seamless integration of BI and collaboration tools offers a competitive edge, simplifying the process of sharing knowledge and clarifying data without switching between applications. Key Benefits of Collaborative Business Intelligence Leading Collaborative BI Platforms Here’s a look at some of the top collaborative BI platforms driving innovation in the market: Conclusion Collaborative BI empowers organizations by improving decision-making, democratizing data access, optimizing data quality, and ensuring data security. By integrating BI tools with collaboration platforms, businesses can streamline their operations, foster a culture of data-driven decision-making, and enhance overall efficiency. Choosing the right platform is key to maximizing the benefits of collaborative BI. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Winter 25 Salesforce Release

Get Ready for Winter 25 Salesforce Release

Salesforce Winter 25 Release notes are here. Salesforce Overall Learn about new features and enhancements that affect your Salesforce experience overall. August 8: Get early access by signing up for a Pre-Release org Admins can sign up for a pre-release Developer Edition environment, which is full of all the Winter ’25 features to explore to your heart’s content. Developer environments are stand-alone environments where you can learn, build, and get comfortable with features and functionality. If you already had a pre-release org for Summer ’24, you can log back into that one. August 14: Review the Release Notes Search the products you use for release updates in the Release Notes section of Salesforce Help. The notes will go live August 14 and we will share the link here. Get help from the community! With each release, there are a number of blogs by community members who break it down. Check out the Release Readiness Trailblazer Community Group where you can continue to get updates, share your favorite features, and ask questions about the upcoming release. August 19: Be Release Ready with Winter ’25 features for Admins Starting on August 19th, we’ll begin publishing blog posts on the Admin Blog to help you Be Release Ready with Winter ’25 features. Get ready to dive into blog posts featuring Winter ’25 user access highlights and more! As blog posts and more release resources become available, we’ll be updating the Be Release Ready page with all the resources and information you need to get started with Winter ’25. August 29 before 5 p.m. PT: Be sure to refresh your Sandbox Once you’ve explored the pre-release org and reviewed the Release Notes for features that are important to you, it’s time to try out features related to your customizations in your sandbox. This is a great time to evaluate how specific features may be useful or impact the way your organization uses Salesforce. During each release, there is a group of sandboxes slated to remain on the non-preview instance (i.e. the current release) while there is another group of sandboxes that will upgrade to the preview instance. Use the Salesforce Sandbox Preview Guide to determine the plan for your sandbox instance(s). Use the tool where you can search by sandbox instance and then specify what you want to do with your sandbox — stay on the non-preview or move to preview. It will then instruct you to refresh your sandbox to get to the desired instance or inform you that there is no action needed because your sandbox is slated for the desired instance. Contact Tectonic today if you need assistance getting Salesforce release ready. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Zero ETL

Zero ETL

What is Zero-ETL? Zero-ETL represents a transformative approach to data integration and analytics by bypassing the traditional ETL (Extract, Transform, Load) pipeline. Unlike conventional ETL processes, which involve extracting data from various sources, transforming it to fit specific formats, and then loading it into a data repository, Zero-ETL eliminates these steps. Instead, it enables direct querying and analysis of data from its original source, facilitating real-time insights without the need for intermediate data storage or extensive preprocessing. This innovative method simplifies data management, reducing latency and operational costs while enhancing the efficiency of data pipelines. As the demand for real-time analytics and the volume of data continue to grow, ZETL offers a more agile and effective solution for modern data needs. Challenges Addressed by Zero-ETL Benefits of ZETL Use Cases for ZETL In Summary ZETL transforms data management by directly querying and leveraging data in its original format, addressing many limitations of traditional ETL processes. It enhances data quality, streamlines analytics, and boosts productivity, making it a compelling choice for modern organizations facing increasing data complexity and volume. Embracing Zero-ETL can lead to more efficient data processes and faster, more actionable insights, positioning businesses for success in a data-driven world. Components of Zero-ETL ZETL involves various components and services tailored to specific analytics needs and resources: Advantages and Disadvantages of ZETL Comparison: Z-ETL vs. Traditional ETL Feature Zero-ETL Traditional ETL Data Virtualization Seamless data duplication through virtualization May face challenges with data virtualization due to discrete stages Data Quality Monitoring Automated approach may lead to quality issues Better monitoring due to discrete ETL stages Data Type Diversity Supports diverse data types with cloud-based data lakes Requires additional engineering for diverse data types Real-Time Deployment Near real-time analysis with minimal latency Batch processing limits real-time capabilities Cost and Maintenance More cost-effective with fewer components More expensive due to higher computational and engineering needs Scale Scales faster and more economically Scaling can be slow and costly Data Movement Minimal or no data movement required Requires data movement to the loading stage Comparison: Zero-ETL vs. Other Data Integration Techniques Top Zero-ETL Tools Conclusion Transitioning to Zero-ETL represents a significant advancement in data engineering. While it offers increased speed, enhanced security, and scalability, it also introduces new challenges, such as the need for updated skills and cloud dependency. Zero-ETL addresses the limitations of traditional ETL and provides a more agile, cost-effective, and efficient solution for modern data needs, reshaping the landscape of data management and analytics. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Bring Your Own Lake With Google BigQuery

Bring Your Own Lake With Google BigQuery

Can BigQuery Function as a Data Lake? Why you should Bring Your Own Lake With Google BigQuery. Google BigQuery serves as a fully-managed, petabyte-scale data warehouse, utilizing Google’s infrastructure’s processing power. The combination of Google Cloud Storage and BigQuery transforms Google Cloud Platform into a scalable data lake capable of storing both structured and unstructured data. Why Embrace BigQuery’s Serverless Model? In a serverless model, processing is automatically distributed across numerous machines operating in parallel. BigQuery’s serverless model allows data engineers and database administrators to concentrate less on infrastructure and more on server provisioning and deriving insights from data. Advantages of Using BigQuery as a Data Warehouse: BigQuery is a completely serverless and cost-effective cloud data warehouse designed to work across clouds, scaling seamlessly with your data. With integrated business intelligence, machine learning, and AI features, BigQuery provides a unified data platform for storing, analyzing, and sharing insights effortlessly. The Relevance of Data Lakes: Data Lakes and Data Warehouses are complementary components of data processing and reporting infrastructure, each serving distinct purposes rather than being alternatives. Data Lakes in the Evolving Landscape: Data lakes, once immensely popular, are gradually being supplanted by more advanced storage solutions like data warehouses. Data Lake Content Formats: A data lake encompasses structured data from relational databases (rows and columns), semi-structured data (CSV, logs, XML, JSON), unstructured data (emails, documents, PDFs), and binary data (images, audio, video). Building a Data Lake on GCP: Constructing a Data Lake: Introduction to Google Big Lake: BigLake serves as a storage engine, offering a unified interface for analytics and AI engines to query multiformat, multicloud, and multimodal data securely, efficiently, and in a governed manner. It aspires to create a single-copy AI lakehouse, minimizing the need for custom data infrastructure management. Data Extraction from a Data Lake: Distinguishing BigQuery as a Data Warehouse: BigQuery stands out as a serverless and cost-effective enterprise data warehouse, functioning across clouds and seamlessly scaling with data. It incorporates built-in ML/AI and BI for scalable insights. Data Lake Implementation Time: Building a fully productive data lake involves several steps, including workflow creation, security mapping, and tool and service configuration. As a result, a comprehensive data lake implementation can take several months. Acquiring a Data Lake: One option is to buy a Data Lake through a decentralized exchange (DEX) supporting the blockchain where the Data Lake resides. Connecting a crypto wallet to a DEX and utilizing a Binance account to purchase the base currency is outlined in a guide for this purpose. Like Related Posts Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to 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 Web Pages That Helped With My Google Data Engineer Exam Google Data Engineer Exam It seems like every day more resources appear to help you study for the Google Data Read more What is Advanced Reporting in Salesforce? Cross Filters, Summary Formulas, and More: Advanced Reporting in Salesforce Salesforce comes with report types out-of-the-box for all standard objects Read more

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Google Analytics and Salesforce Integration

Google Analytics and Salesforce Integration

Syncing Google Analytics Data to CRM Analytics To integrate Google Analytics and Salesforce Integration using the Google Analytics connector, follow these steps: Important Note: As of July 1, 2023, the main product Google Analytics has been decommissioned and replaced with the new product Google Analytics 4 (GA4). The Salesforce announcement GA4 Set to Replace Universal Analytics gives an overview on this. Creating a Connection Required Settings: Google Analytics 4 Integration To sync Google Analytics 4 data to Salesforce Data Pipelines: Connector Considerations: Google Analytics Salesforce Sales Cloud Integration User Identification Analytics provides two methods to identify users: Required Salesforce Sales Cloud Objects and Fields: Integration Steps: Testing and Viewing Imported Data: Notes: Google Data Studio and Salesforce Integration Connecting Salesforce with Google Data Studio allows for powerful visualizations that combine sales and marketing data. This integration helps in understanding which channels generate the most leads and income. Google Analytics 4 Connection Setup: Connection Details: Advanced Properties: Considerations: By following these steps, you can seamlessly integrate Google Analytics data into your CRM Analytics and Salesforce Data Pipelines, ensuring robust data analysis and informed decision-making. Decide How to Identify Your Users: Analytics offers two ways to programmatically identify your users: Client ID and User-ID. To support Data Import for Salesforce Sales Cloud, you must implement Client ID. You may optionally choose to also implement User-ID. Client ID pseudonymously identifies a browser instance and is best suited for businesses focused on lead generation and new customer acquisition. User-ID enables the analysis of groups of sessions, across devices, using a unique, persistent, and non-personally identifiable ID string representing a user. This option is best for businesses with high rates of logged-in users. How to Import CRM/ERP Data with Google Analytics 4 Using a CSV File: Transitioning to Google Analytics 4: As of March 2023, Google has automatically created GA4 properties for users unless they opt-out. Until July 1, 2023, you can continue to use and collect new data in your Universal Analytics properties. After this date, you must export your historical reports as Universal Analytics will be phased out. How Does Google Help Salesforce Marketing Cloud Users? Google Analytics provides invaluable insights into user behavior, helping Salesforce Marketing Cloud users optimize campaigns and understand customer journeys. Integration with the Google platform allows businesses to combine offline sales data with digital analytics, optimizing digital marketing strategies and improving campaign effectiveness. Additional Integration: Using datasets from Google Analytics and Google BigQuery, businesses can create interactive Tableau CRM dashboards to visualize campaign activities and performance metrics. By following these guidelines, organizations can leverage Google Analytics data effectively within their Salesforce ecosystem, enhancing decision-making and strategic planning. Content updated July 2024. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Integrations for Sales and Marketing Teams

What do Salesforce integrations entail? Salesforce Integrations for Sales and Marketing Teams. Salesforce integrations involve establishing connections between Salesforce and various third-party applications, ranging from marketing automation tools and customer service software to accounting programs. This seamless exchange of data between platforms serves to enhance Salesforce’s overall functionality. How extensive is Salesforce’s integration ecosystem? Salesforce boasts a robust integration ecosystem, with over 3,000 integrations available on its AppExchange marketplace. Beyond these, users can leverage: Salesforce Integrations for Sales and Marketing Teams While there isn’t a one-size-fits-all list of essential Salesforce integrations for sales and marketing, we’ve curated a selection of widely-used integrations across various categories: These integrations cater to diverse needs within sales and marketing, facilitating efficient data handling, analytics, communication, project management, and more. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Integration

Salesforce Integrations for Sales and Marketing Teams

First Understand Salesforce Integrations Salesforce integrations involve establishing seamless connections between Salesforce and diverse third-party applications. These applications range from marketing automation tools and customer service software to accounting programs. The purpose is to facilitate a smooth exchange of data, ultimately enhancing Salesforce’s overall functionality. Salesforce integrations for sales and marketing teams brings all the applications needed for the relationship with prospects into one place. Salesforce’s Integration Ecosystem While Salesforce boasts a robust integration ecosystem, featuring over 3,000 integrations available on its AppExchange marketplace. Users can leverage various integration approaches: Salesforce Integrations for Sales and Marketing While there’s no complete universal list of essential Salesforce integrations for sales and marketing, several widely-used integrations cater to diverse needs: No-code Data Automation Integrations: Analytics and Reporting Integrations: Email Marketing Automation Integration: Data Storage Integration: Communications Apps Integrations: Project Management Tools Integration: Account Management Integration: CRM Tools Integration: Helpdesk Integrations: Feedback Tools Integration: These integrations facilitate efficient data handling, analytics, communication, project management, and more within sales and marketing teams. Integrations for Sales and Marketing Tools Salesforce seamlessly integrates with various tools relevant to Sales and Marketing teams, including but not limited to: Salesforce Integration with Teams and Workday The Salesforce AppExchange Salesforce’s Role in Sales and Marketing Salesforce Marketing Cloud Salesforce and ERP Integration Digital Marketing and Salesforce Salesforce’s Role in Marketing Automation Content updated November 2023. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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