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Amazon Q Business
12Jan

Amazon Q Business

Amazon Q Business: Revolutionizing Enterprise Productivity with Generative AI and Plugins Amazon Q Business is a generative AI-powered assistant that empowers employees by solving problems, generating content, and offering actionable insights from across enterprise data sources. In addition to its robust search capabilities across indexed third-party services, Amazon Q Business enables real-time access to dynamic data like stock prices, vacation balances, and location tracking through its plugins. These plugins also allow employees to perform direct actions—such as prioritizing service tickets—within enterprise applications, all through a single interface. This eliminates the need to toggle between systems, saving valuable time and increasing productivity. This insight delves into how Amazon Q Business plugins seamlessly integrate with enterprise applications through built-in and custom configurations. We’ll explore: Simplifying Enterprise Tasks with Plugins Amazon Q Business enables users to access non-indexed data—such as calendar availability, stock prices, or PTO balances—and execute actions like booking a meeting or submitting PTO using services like Jira, ServiceNow, Salesforce, Fidelity, Vanguard, ADP, Workday, and Google Calendar. This unified approach streamlines workflows and minimizes reliance on multiple apps for task completion. Solution Overview Amazon Q Business connects to over 50 enterprise applications using connectors and plugins: Plugins are categorized into two types: Built-in Plugins Amazon Q Business supports more than 50 actions across applications: Category Application Sample Actions Ticketing ServiceNow Create, update, delete tickets Zendesk Suite Search, create, update tickets Project Management Jira Cloud Read, create, update, delete issues Smartsheet Search and manage sheets and reports CRM Salesforce Manage accounts, opportunities, and cases Communication Microsoft Teams Send private or channel messages Productivity Google Calendar Find events, list calendars Salesforce Plugin Example The Salesforce plugin allows users to: Configuration Steps: Custom Plugins For scenarios not covered by built-in plugins, custom plugins enable seamless integration with proprietary systems. For example: HR Time Off Plugin Example This plugin allows employees to: Setup Steps: End-to-End Use Cases 1. Salesforce Integration Sam, a Customer Success Manager, retrieves high-value opportunities using the Salesforce plugin. She creates a new case directly from the Amazon Q interface, enhancing efficiency by reducing application switching. 2. ServiceNow Ticket Management Sam uses Amazon Q Business to resolve a laptop email sync issue. After referencing indexed IT documentation, she creates a ServiceNow ticket and escalates it directly through the plugin interface. 3. HR System Integration Sam checks her PTO balance and submits a vacation request using the HR Time Off custom plugin, ensuring seamless task completion without switching to another app. Impact on Workflow Efficiency Amazon Q Business plugins simplify workflows by: Conclusion Amazon Q Business plugins represent a transformative step in automating enterprise workflows and enhancing employee productivity. From preconfigured integrations to custom-built solutions, these plugins provide unparalleled flexibility to adapt to diverse business needs. How can Amazon Q Business transform workflows in your organization? Whether through built-in integrations or custom solutions, explore the power of Amazon Q Business plugins to unlock new levels of efficiency. Share your feedback and use cases to inspire innovation across enterprises! 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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January 12, 2025in Data, Enterprise, Generative AI, Google, Salesforce0 Comments
Data Cloud Model
08Oct

Data Cloud Model

While many Salesforce products like Sales Cloud, Service Cloud, Education Cloud, Health Cloud, and various industry clouds are built on a common ‘core’ platform that shares the same datastore (an Oracle relational database), Salesforce Data Cloud operates on (Data Cloud Model) a distinct architecture and technology stack. This insight explores the data models and related concepts that underpin the platform. Data Cloud Architecture and Storage Starting with the storage layer, Salesforce Data Cloud integrates multiple services: This combination enables Data Cloud to provide a petabyte-scale data store, overcoming the scalability and performance constraints of traditional relational databases. The physical architecture of Data Cloud is represented as a set of data objects, which form the foundation for how data is ingested, harmonized, and activated within the platform. Key Data Cloud Objects Data Source A Data Source is the initial data layer in Data Cloud, representing an external platform or system from which your data originates. Data Sources can include: Data Stream A Data Stream is an entity extracted from a Data Source, such as ‘Orders’ from Commerce Cloud, ‘Contacts’ from Sales Cloud, or ‘Subscribers’ from Marketing Cloud. Once a Data Source is connected to Data Cloud, Data Streams provide access to these entities and require assignment to a category: Profile, Engagement, or Other. A single Data Source can contain multiple Data Streams. Data Source Object (DSO) Data Streams are ingested into Data Source Objects (DSOs), which serve as temporary staging stores containing data in its raw, native format (e.g., CSV files). Minor transformations can be applied to fields during data ingestion. Data Lake Object (DLO) The next step in the data flow is the Data Lake Object (DLO). DLOs are typed, schema-based, materialized views that reside in the data lake (Amazon S3) and are generally stored as Apache Parquet files. This format, along with Apache Iceberg’s abstraction layer, supports efficient data storage and retrieval. DLOs are the first objects available for inspection and preparation of data, including field mapping and additional transformations. Data Model Object (DMO) Unlike DSOs and DLOs, which use a physical data store, Data Model Objects (DMOs) provide a virtual, non-materialized view into the data lake. Queries against a DMO return results based on the current data snapshot in DLOs, without storing them. DMOs can aggregate attributes from different Data Streams, Calculated Insights, and other sources. DMOs inherit their category from the first DLO mapped to them, and only DLOs with the same category can be mapped to the DMO. Like Salesforce objects, DMOs offer a canonical data model with pre-defined attributes (standard objects), and you can also create custom DMOs (custom objects). DMOs can have one-to-one or many-to-one relationships with other DMOs. Currently, there are 89 standard DMOs in Data Cloud, and this number is growing to support more use cases. DMOs are organized into various subject areas, including: Data Spaces Data Spaces offer logical partitions, allowing data to be segregated between different brands, regions, or departments, without the need for multiple Data Cloud instances. They also align with a Software Development Lifecycle (SDLC), enabling you to stage and test Data Objects in separate environments without affecting production data. Data Sources, Data Streams, and DLOs can be shared across Data Spaces, while DMOs and other platform features are isolated based on user permissions. Final Thoughts With the drop in storage costs and advancements in technology, companies now have vast datasets at their disposal. Every customer interaction, whether it’s a purchase, an email open, or a web page view, can be captured and stored. When properly organized, this data allows businesses to understand customers better, predict their needs, personalize interactions, and much more. However, one of Salesforce’s challenges is that its original platform, built over 20 years ago, was designed for a different era and struggles with handling voluminous, “big” data. Salesforce Data Cloud addresses these limitations with a modern architecture that overcomes the constraints of relational databases. Data Cloud is poised to become the backbone of the Salesforce platform, supporting the data needs of customers and products for the next two decades. If you’re interested in learning how to implement and integrate Salesforce Data Cloud in your organization, following best practices, reach out 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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October 8, 2024in Data, Google, Salesforce, Salesforce Data Cloud, Snowflake, Technology, Unified Knowledge
Data Integration with AWS Glue
04Sep

Data Integration with AWS Glue

The rapid rise of Software as a Service (SaaS) solutions has led to data silos across different platforms, making it challenging to consolidate insights. Effective data analytics depends on the ability to seamlessly integrate data from various systems by identifying, gathering, cleansing, and combining it into a unified format. AWS Glue, a serverless data integration service, simplifies this process with scalable, efficient, and cost-effective solutions for unifying data from multiple sources. By using AWS Glue, organizations can streamline data integration, minimize silos, and enhance agility in managing data pipelines, unlocking the full potential of their data for analytics, decision-making, and innovation. This insight explores the new Salesforce connector for AWS Glue and demonstrates how to build a modern Extract, Transform, and Load (ETL) pipeline using AWS Glue ETL scripts. Introducing the Salesforce Connector for AWS Glue To meet diverse data integration needs, AWS Glue now supports SaaS connectivity for Salesforce. This enables users to quickly preview, transfer, and query customer relationship management (CRM) data, while dynamically fetching the schema. With the Salesforce connector, users can ingest and transform CRM data and load it into any AWS Glue-supported destination, such as Amazon S3, in preferred formats like Apache Iceberg, Apache Hudi, and Delta Lake. It also supports reverse ETL use cases, enabling data to be written back to Salesforce. Key Benefits: Solution Overview For this use case, we retrieve the full load of a Salesforce account object into a data lake on Amazon S3 and capture incremental changes. The solution also enables updates to certain fields in the data lake and synchronizes them back to Salesforce. The process involves creating two ETL jobs using AWS Glue with the Salesforce connector. The first job ingests the Salesforce account object into an Apache Iceberg-format data lake on Amazon S3. The second job captures updates and pushes them back to Salesforce. Prerequisites: Creating the ETL Pipeline Step 1: Ingest Salesforce Account Object Using the AWS Glue console, create a new job to transfer the Salesforce account object into an Apache Iceberg-format transactional data lake in Amazon S3. The script checks if the account table exists, performs an upsert if it does, or creates a new table if not. Step 2: Push Changes Back to Salesforce Create a second ETL job to update Salesforce with changes made in the data lake. This job writes the updated account records from Amazon S3 back to Salesforce. Example Query sqlCopy codeSELECT id, name, type, active__c, upsellopportunity__c, lastmodifieddate FROM “glue_etl_salesforce_db”.”account”; Additional Considerations You can schedule the ETL jobs using AWS Glue job triggers or integrate them with other AWS services like AWS Lambda and Amazon EventBridge for advanced workflows. Additionally, AWS Glue supports importing deleted Salesforce records by configuring the IMPORT_DELETED_RECORDS option. Clean Up After completing the process, clean up the resources used in AWS Glue, including jobs, connections, Secrets Manager secrets, IAM roles, and the S3 bucket to avoid incurring unnecessary charges. Conclusion The AWS Glue connector for Salesforce simplifies the analytics pipeline, accelerates insights, and supports data-driven decision-making. Its serverless architecture eliminates the need for infrastructure management, offering a cost-effective and agile approach to data integration, empowering organizations to efficiently meet their analytics needs. 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 4, 2024in Salesforce
Salesforce Data Migration Tools
24Jul

Salesforce Data Migration

Salesforce Data Migration: A Key to CRM Success The migration of data into Salesforce is critical for the efficient functioning of Salesforce CRM. When executed correctly, it reduces data duplication, consolidates customer and operational data into a unified platform, and extends CRM capabilities beyond basic functionalities. Proper data migration serves as the foundation for advanced business intelligence and in-depth analytics. On the other hand, poorly managed migration can lead to transferring incorrect, duplicate, or corrupted data, compromising the system’s reliability. An efficient migration process safeguards data integrity, ensures a seamless transfer to Salesforce, and enhances overall organizational performance. What is Data Migration in Salesforce? Salesforce data migration is the process of transferring data from external systems, databases, or platforms into Salesforce. This process captures critical business information and integrates it into Salesforce’s CRM framework securely. The migration process also involves data cleansing, verification, and transforming data into formats compatible with Salesforce’s structure. Why You Need Salesforce Data Migration Importance Data migration is indispensable for companies looking to modernize their operations and enhance performance. With Salesforce, organizations can: Benefits Migrating Data from Legacy Systems to Salesforce Migrating data from legacy systems to Salesforce is essential for scalability and efficient data management. Key advantages include: Salesforce Data Migration Process Data migration involves transferring data into Salesforce to improve customer engagement and operational workflows. The process ensures data accuracy and compatibility with Salesforce’s architecture. Key Steps for Salesforce Data Migration Types of Salesforce Data Migration Top Salesforce Data Migration Tools Data Archiving in Salesforce Salesforce data archiving involves relocating unused or historical data to a separate storage area. This optimizes system performance and ensures easy access for compliance or analysis. Advantages Top Options for Data Archiving Best Practices for Salesforce Data Migration Conclusion Salesforce data migration is a pivotal step in transforming organizational processes and achieving CRM excellence. When done right, it improves efficiency, eliminates data duplication, and ensures accurate information storage. By following best practices, leveraging appropriate tools, and engaging migration specialists, organizations can unlock Salesforce’s full potential for scalability, automation, and advanced analytics. Successful migration paves the way for better decision-making and future growth. 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 24, 2024in Data
Zero ETL
13Jun

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 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 13, 2024in Snowflake
career
05Dec

Amazon Salesforce

The world’s leading cloud provider and the #1 CRM platform are making it easier for customers to seamlessly and securely manage their data across Salesforce and AWS. Now able to safely and responsibly use the latest generative artificial intelligence (AI) technologies in their applications and workflows. AWS and Salesforce support customers through new and enhanced integrations. Integrations between AWS technologies and Salesforce products, including unified data management, seamless deployment of AWS’s voice, video, and AI services, streamlined purchasing options through AWS Marketplace, and more. Amazon Salesforce is a marriage for the IT ages. In November 2023, Salesforce and Amazon announced a partnership. New joint innovations enhance data management, improve customer experiences, and enable AI-powered applications Salesforce significantly expands its use of AWS across its full portfolio and is taking an AWS-native approach for its most strategic and fastest growing innovation. The Salesforce Data Cloud. AWS increases its company-wide use of Salesforce CRM offerings, including adopting Data Cloud to manage its unified customer profiles. With Salesforce now available on AWS Marketplace, thousands of joint customers can accelerate their deployment of Salesforce products through seamless buying and billing experiences. San Francisco and Las Vegas — November 27, 2023 At AWS re: Invent, Amazon Web Services (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), and Salesforce, the #1 AI CRM (NYSE: CRM), today announced a significant expansion of their long standing, global strategic partnership. By deepening product integrations across data and artificial intelligence (AI), and for the first time offering select Salesforce products on the AWS Marketplace. The expanded agreement makes it easier for customers to seamlessly and securely manage their data across Salesforce and AWS,. Increasing the ability to safely and responsibly infuse the latest generative AI technologies into their applications and workflows. “Salesforce and AWS make it easy for developers to securely access and leverage data and generative AI technologies to drive rapid transformation for their organizations and industries. With this expanded partnership, our joint customers gain powerful new ways to innovate, collaborate, and build more customer-focused applications using the broadest and deepest set of cloud services.” Adam Selipsky, CEO, AWS How Customers Benefit To make it easier for customers to benefit from the combined value of Salesforce and AWS, the companies will deepen the integrations between AWS and Salesforce products. Salesforce will now support Amazon Bedrock. Bedrock is a fully managed service that makes foundation models (FMs) from leading AI companies available through a single application programming interface (API). This is part of Salesforce’s open model ecosystem strategy. Making Amazon Bedrock available through the Einstein Trust Layer to power AI-driven apps and workflows in Salesforce. In addition, Salesforce Data Cloud will expand to support data sharing across additional AWS technologies. These Data Cloud integrations will be governed by new centralized access controls. Thereby giving customers the ability to manage secure user access at the folder, object, and file level for Data Cloud content stored in Amazon Simple Storage Service (Amazon S3). Expanded Use of Amazon Web Services As part of this partnership, Salesforce will expand its use of Amazon Web Services, including compute, storage, data, and AI technologies through Hyperforce. Therefore further enhancing popular services like Salesforce Data Cloud. AWS will also expand its use of Salesforce products. Data Cloud will allow AWS to create a single unified customer profile allowing them to deliver more personalized experiences to customers.  Notable Quotable “We’re bringing together the #No. 1 AI CRM provider and the leading cloud provider to deliver a trusted, open, integrated data and AI platform, and ensuring we meet massive customer demand for our products on the AWS Marketplace. With these enhancements to our partnership, we’re enabling all of our customers to be more innovative, productive and successful in this new AI era.”  Marc Benioff, chair and CEO, Salesforce These new and enhanced integrations will include: Availability: What is Amazon Connect Salesforce? The Amazon Connect CTI Adapter provides a WebRTC browser-based contact control panel (CCP). This is within the Salesforce Lightning, Console, and Classic CRM experience. This CTI integration gives your agents the ability to leverage both inbound caller ID screen pop-ups and outbound click to call/transfer/conferencing. 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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December 5, 2023in Salesforce

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