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Snowpark Container Services
01Aug

Snowpark Container Services

Snowflake announced on Thursday the general availability of Snowpark Container Services, enabling customers to securely deploy and manage models and applications, including generative AI, within Snowflake’s environment. Initially launched in preview in June 2023, Snowpark Container Services is now a fully managed service available in all AWS commercial regions and in public preview in all Azure commercial regions. Containers are a software method used to isolate applications for secure deployment. Snowflake’s new feature allows customers to use containers to manage and deploy any type of model, optimally for generative AI applications, by securely integrating large language models (LLMs) and other generative AI tools with their data, explained Jeff Hollan, Snowflake’s head of applications and developer platform. Mike Leone, an analyst at TechTarget’s Enterprise Strategy Group, noted that Snowpark Container Services’ launch builds on Snowflake’s recent efforts to provide customers with an environment for developing generative AI models and applications. Sridhar Ramaswamy became Snowflake’s CEO in February, succeeding Frank Slootman, who led the company through a record-setting IPO. Under Ramaswamy, Snowflake has aggressively added generative AI capabilities, including launching its own LLM, integrating with Mistral AI, and providing tools for creating AI chatbots. “There has definitely been a concerted effort to enhance Snowflake’s capabilities and presence in the AI and GenAI markets,” Leone said. “Offerings like Snowpark help AI stakeholders like data scientists and developers use the languages they prefer.” As a result, Snowpark Container Services is a significant new feature for Snowflake customers. “It’s a big deal for the Snowflake ecosystem,” Leone said. “By enabling easy deployment and management of containers within the Snowflake platform, it helps customers handle complex workloads and maintain consistency across development and production stages.” Despite the secure environment provided by Snowflake Container Services, it was revealed in May that the login credentials of potentially 160 customers had been stolen and used to access their data. However, Snowflake has stated there is no evidence that the breach resulted from a vulnerability or misconfiguration of the Snowflake platform. Prominent customers affected include AT&T and Ticketmaster, and Snowflake’s investigation is ongoing. New Capabilities Generative AI can transform business by enabling employees to easily work with data to inform decisions and making trained experts more efficient. Generative AI, combined with an enterprise’s proprietary data, allows users to interact with data using natural language, reducing the need for coding and data literacy training. Non-technical workers can query and analyze data, freeing data engineers and scientists from routine tasks. Many data management and analytics vendors are focusing on developing generative AI-powered features. Enterprises are building models and applications trained on their proprietary data to inform business decisions. Among data platform vendors, AWS, Databricks, Google, IBM, Microsoft, and Oracle are providing environments for generative AI tool development. Snowflake, under Slootman, was less aggressive in this area but is now committed to generative AI development, though it still has ground to cover compared to its competitors. “Snowflake has gone as far as creating their own LLM,” Leone said. “But they still have a way to go to catch up to some of their top competitors.” Matt Aslett, an analyst at ISG’s Ventana Research, echoed that Snowflake is catching up to its rivals. The vendor initially focused on traditional data warehouse capabilities but made a significant step forward with the late 2023 launch of Cortex, a platform for developing AI models and applications. Cortex includes access to various LLMs and vector search capabilities, marking substantial progress. The general availability of Snowpark Container Services furthers Snowflake’s effort to foster generative AI development. The feature provides users with on-demand GPUs and CPUs to run any code next to their data. This enables the deployment and management of any type of model or application without moving data out of Snowflake’s platform. “It’s optimized for next-generation data and AI applications by pushing that logic to the data,” Hollan said. “This means customers can now easily and securely deploy everything from source code to homegrown models in Snowflake.” Beyond security, Snowpark Container Services simplifies model management and deployment while reducing associated costs. Snowflake provides a fully integrated managed service, eliminating the need for piecing together various services from different vendors. The service includes a budget control feature to reduce operational costs and provide cost certainty. Snowpark Container Services includes diverse storage options, observability tools like Snowflake Trail, and streamlined DevOps capabilities. It supports deploying LLMs with local volumes, memory, Snowflake stages, and configurable block storage. Integrations with observability specialists like Datadog, Grafana, and Monte Carlo are also included. Aslett noted that the 2020 launch of the Snowpark development environment enabled users to use their preferred coding languages with their data. Snowpark Container Services takes this further by allowing the use of third-party software, including generative AI models and data science libraries. “This potentially reduces complexity and infrastructure resource requirements,” Aslett said. Snowflake spent over a year moving Snowpark Container Services from private preview to general availability, focusing on governance, networking, usability, storage, observability, development operations, scalability, and performance. One customer, Landing AI, used Snowpark Container Services during its preview phases to develop LandingLens, an application for training and deploying computer vision models. “[With Snowflake], we are increasing access to AI for more companies and use cases, especially given the rapid growth of unstructured data in our increasingly digital world,” Landing AI COO Dan Maloney said in a statement Thursday. Future Plans With Snowpark Container Services now available on AWS, Snowflake plans to extend the feature to all cloud platforms. The vendor’s roadmap includes further improvements to Snowpark Container Services with more enterprise-grade tools. “Our team is investing in making it easy for companies ranging from startups to enterprises to build, deliver, distribute, and monetize next-generation AI products across their ecosystems,” Hollan said. Aslett said that making Snowpark Container Services available on Azure and Google Cloud is the logical next step. He noted that the managed service’s release is significant but needs broader availability beyond AWS regions. “The next step will be to bring Snowpark Container Services to general

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August 1, 2024in Snowflake
Cyber Group Targets SaaS Platforms
18Jun

Cyber Group Targets SaaS Platforms

Cyber Group UNC3944 Targets SaaS Platforms like Azure, Salesforce, vSphere, AWS, and Google Cloud UNC3944, also known as “0ktapus” and “Scattered Spider,” has shifted its focus to attacking Software-as-a-Service (SaaS) applications, as reported by Google Cloud’s Mandiant threat intelligence team. This hacking group, previously linked to incidents involving companies such as Snowflake and MGM Entertainment, has evolved its strategies to concentrate on data theft and extortion. Cyber Group Targets SaaS Platforms Attack Techniques UNC3944 exploits legitimate third-party tools for remote access and leverages Okta permissions to expand their intrusion capabilities. One notable aspect of their attacks involves creating new virtual machines in VMware vSphere and Microsoft Azure, using administrative permissions linked through SSO applications for further activities. The group uses commonly available utilities to reconfigure virtual machines (VMs), disable security protocols, and download tools such as Mimikatz and ADRecon, which extract and combine various artifacts from Active Directory (AD) and Microsoft Entra ID environments. Evolving Methods Initially, UNC3944 employed a variety of techniques, but over time, their methods have expanded to include ransomware and data theft extortion. Active since at least May 2022, the group has developed resilience mechanisms against virtualization platforms and improved their ability to move laterally by abusing SaaS permissions. The group also uses SMS phishing to reset passwords and bypass multi-factor authentication (MFA). Once inside, they conduct thorough reconnaissance of Microsoft applications like SharePoint to understand remote connection needs. According to Google Cloud’s Mandiant team, UNC3944’s primary activity is now data theft without using ransomware. They employ expert social engineering tactics, using detailed personal information to bypass identity checks and target employees with high-level access. Social Engineering and Threats Attackers often pose as employees, contacting help desks to request MFA resets for setting up new phones. If help desk staff comply, attackers can easily bypass MFA and reset passwords. If social engineering fails, UNC3944 resorts to threats, including doxxing, physical threats, or releasing compromising material to coerce credentials from victims. Once access is gained, they gather information on tools like VPNs, virtual desktops, and remote work utilities to maintain consistent access. Targeting SaaS and Cloud Platforms UNC3944 targets Okta’s single sign-on (SSO) tools, allowing them to create accounts that facilitate access to multiple systems. Their attacks extend to VMware’s vSphere hybrid cloud management tool and Microsoft Azure, where they create virtual machines for malicious purposes. By operating within a trusted IP address range, they complicate detection. Additional targets include SaaS applications like VMware’s vCenter, CyberArk, Salesforce, CrowdStrike, Amazon Web Services (AWS), and Google Cloud. Office 365 is another focus, with attackers using Microsoft’s Delve tool to identify valuable information. To exfiltrate data, they use synchronization utilities such as Airbyte and Fivetran to transfer information to their own cloud storage. The group also targets Active Directory Federation Services (ADFS) to extract certificates and employ Golden SAML attacks for continued access to cloud applications. They leverage Microsoft 365 capabilities like Office Delve for quick reconnaissance and data mining. Recommendations – Cyber Group Targets SaaS Platforms Mandiant advises deploying host-based certificates with MFA for VPN access, implementing stricter conditional access policies, and enhancing monitoring for SaaS applications. Consolidating logs from crucial SaaS applications and monitoring virtual machine setups can help identify potential breaches. 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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June 18, 2024in Salesforce, Salesforce Managed Services, Snowflake
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
Snowflake With AWS Salesforce and Microsoft
04Jun

Snowflake With AWS Salesforce and Microsoft

In anticipation of its sixth annual user conference, Snowflake Summit 2024, Snowflake has unveiled the Polaris Catalog, a vendor-neutral, open catalog implementation for Apache Iceberg. This open standard is widely used for implementing data lakehouses, data lakes, and other data architectures. Snowflake With AWS Salesforce and Microsoft. The Polaris Catalog will be open-sourced for the next 90 days, offering enterprises like Goldman Sachs and the Iceberg community increased choice, flexibility, and control over their data. It also promises comprehensive enterprise security and compatibility with Apache Iceberg, enabling interoperability with AWS, Confluent, Dremio, Google Cloud, Microsoft Azure, Salesforce, and more. “We are collaborating with numerous industry partners to provide our mutual customers the ability to mix and match various query engines and coordinate read and write operations without vendor lock-in, and most importantly, to do so in an open manner.” Christian Kleinerman, Snowflake’s EVP of Product Kleinerman further highlighted that this initiative can “simplify how organizations access their data across diverse systems, enhancing flexibility and control.” Apache Iceberg, which became a top-level Apache Software Foundation project in May 2020 after emerging from incubation, has quickly become a leading open-source data table format. Building on this success, Polaris Catalog offers users a centralized location for any engine to discover and access an organization’s Iceberg tables with open interoperability. To ensure Polaris Catalog meets the evolving needs of the community, Snowflake is collaborating with the Iceberg ecosystem to advance the project. Chris Grusz, MD of technology partnerships at AWS, noted AWS’s commitment to working with partners on open-source solutions that enhance customer choice: “We’re pleased to work with Snowflake to continue to make Apache Iceberg interoperable across our engines.” Similarly, Raveendrnathan Loganathan, EVP of software engineering at Salesforce, mentioned that Apache Iceberg’s popularity has established an open storage standard simplifying zero-copy data access for organizations. “We’re thrilled to have Snowflake as a member of our Zero Copy Partner Network, and we’re excited about how this new open catalog standard will further zero-copy access in the enterprise,” he said. This development follows the recent expansion of the partnership between Snowflake and Microsoft, supporting leading open standards for storage formats, including Apache Iceberg and Apache Parquet. With Polaris Catalog, they aim to continue their mission of enabling users to leverage their enterprise data, regardless of its location, to develop AI-powered applications at scale. 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 4, 2024in Salesforce, Snowflake
Einstein Personalization and Copilots
30May

Einstein Personalization and Copilots

Salesforce launched a suite of new generative AI products at Connections in Chicago, including new Einstein Copilots for marketers and merchants, and Einstein Personalization. Einstein Personalization and Copilots To gain insights into these products and Salesforce’s evolving architecture, Bobby Jania, CMO of Marketing Cloud was interviewed. Salesforce’s Evolving Architecture Salesforce has a knack for introducing new names for its platforms and products, sometimes causing confusion about whether something is entirely new or simply rebranded. Reporters sought clarification on the Einstein 1 platform and its relationship to Salesforce Data Cloud. “Data Cloud is built on the Einstein 1 platform,” Jania explained. “Einstein 1 encompasses the entire Salesforce platform, including products like Sales Cloud and Service Cloud, continuing the original multi-tenant cloud concept.” Data Cloud, developed natively on Einstein 1, was the first product built on Hyperforce, Salesforce’s new cloud infrastructure. “From the start, Data Cloud has been able to connect to and read anything within Sales Cloud, Service Cloud, etc. Additionally, it can now handle both structured and unstructured data.” This marks significant progress from a few years ago when Salesforce’s platform comprised various acquisitions (like ExactTarget) that didn’t seamlessly integrate. Previously, data had to be moved between products, often resulting in duplicates. Now, Data Cloud serves as the central repository, with applications like Tableau, Commerce Cloud, Service Cloud, and Marketing Cloud all accessing the same operational customer profile without duplicating data. Salesforce customers can also import their own datasets into Data Cloud. “We wanted a federated data model,” Jania said. “If you’re using Snowflake, for example, we virtually sit on your data lake, providing value by forming comprehensive operational customer profiles.” Understanding Einstein Copilot “Copilot means having an assistant within the tool you’re using, contextually aware of your tasks and assisting you at every step,” Jania said. For marketers, this could start with a campaign brief created with Copilot’s help, identifying an audience, and developing content. “Einstein Studio is exciting because customers can create actions for Copilot that we hadn’t even envisioned.” Contrary to previous reports, there is only one Copilot, Einstein Copilot, with various use cases like marketing, merchants, and shoppers. “We use these names for clarity, but there’s just one Copilot. You can build your own use cases in addition to the ones we provide.” Marketers will need time to adapt to Copilot. “Adoption takes time,” Jania acknowledged. “This Connections event offers extensive hands-on training to help people use Data Cloud and these tools, beyond just demonstrations.” What’s New with Einstein Personalization Einstein Personalization is a real-time decision engine designed to choose the next best action or offer for customers. “What’s new is that it now runs natively on Data Cloud,” Jania explained. While many decision engines require a separate dataset, Einstein Personalization evaluates a customer holistically and recommends actions directly within Service Cloud, Sales Cloud, or Marketing Cloud. Ensuring Trust Connections presentations emphasized that while public LLMs like ChatGPT can be applied to customer data, none of this data is retained by the LLMs. This isn’t just a matter of agreements; it involves the Einstein Trust Layer. “All data passing through an LLM runs through our gateway. Personally identifiable information, such as credit card numbers or email addresses, is stripped out. The LLMs do not store the output; Salesforce retains it for auditing. Any output that returns through our gateway is logged, checked for toxicity, and only then is PII reinserted into the response. These measures ensure data safety beyond mere handshakes,” Jania said. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 30, 2024in Einstein 1 Platform, Generative AI, Hyperforce, Salesforce, Salesforce Data Cloud, Salesforce Einstein, Snowflake
Securing SaaS
26May

Securing SaaS

Obsidian Security recently discussed the complexity of enforcing Single Sign-On (SSO) within Salesforce and frequently encountering misconfigurations. Notably, 60% of Obsidian’s customers initially have local access without Multi-Factor Authentication (MFA) configured for Salesforce, highlighting a significant security gap that Obsidian diligently works to secure. Securing SaaS. The Hidden Vulnerability Application owners who manage Salesforce daily often remain unaware of this misconfiguration. Despite their deep knowledge of Salesforce management, local access without MFA presents an overlooked vulnerability. This situation raises concerns about the security of other SaaS applications, especially those without developed expertise or knowledge. If you have concerns about your configuration, Tectonic can help. Attacker Focus and Trends Attackers have historically targeted the Identity Provider (IdP) space, focusing on providers like Okta, Microsoft Entra, and Ping. This strategy offers maximal impact, as compromising an IdP grants broad access across multiple applications. Developing expertise to breach a few IdPs is more efficient than learning the diverse local access pathways of numerous SaaS vendors. Over the past 12 months, nearly 100% of the breaches that required Obsidian’s intervention through CrowdStrike or other incident response partners were IdP-focused. Notably, 70% of these breaches involved subverting MFA, often through methods like SIM swapping. In instances where local access bypasses the IdP, 95% of the time it lacks MFA. Recent discussions around Snowflake have brought attention to “shadow authentication,” defined as unsanctioned means to authenticate a user within an application. Obsidian Security has observed an increase in brute force attacks against SaaS applications via local access pathways over the last two weeks, indicating a growing awareness of this attack vector. Future Expectations Attackers continually seek easy and efficient pathways. Over the next 12 months, local access or shadow authentication is expected to become a major attack vector. Organizations must proactively secure these pathways as attackers shift their focus. What You Can Do How Obsidian Helps Salesforce Security partners offers robust solutions to address these challenges: By leveraging partner capabilities, organizations can enhance their security posture, protecting against evolving threats targeting local access and shadow authentication. The post “The Growing Importance of Securing Local Access in SaaS Applications” appeared first on Obsidian Security. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 26, 2024in Salesforce, Salesforce Einstein, Snowflake
Zero Copy from Salesforce
14May

Zero Copy from Salesforce

When was the last time you relocated? Remember the hassle of packing up all your stuff, loading it onto a truck, and unpacking everything at your new digs, hoping it all survived the journey? Now, imagine if your furniture and possessions could simply teleport to your new location in perfect condition. While this may not be possible (yet) in the physical world, the concept of zero copy integration offers a similar seamless experience for handling customer data. Zero Copy from Salesforce. Zero copy integration, also known as zero ETL (extract-transform-load), allows data to be shared among multiple data stores without the need for actual movement or duplication. This is particularly advantageous for companies utilizing cloud data warehouses like Snowflake or Google BigQuery. Some companies hesitate to adopt a customer data platform (CDP) due to concerns about duplicating data. However, with zero copy integration, users can leverage the benefits of a CDP—such as data harmonization, identity management, built-in analytics, and activation—without the drawbacks of physical data movement. Some functions related to data have advanced with astonishing speed: generation, dissemination, storage, even security (and yes, that one still has many challenges). But there are others still mired in the stone age—call it the 80s—of the digital era. For example, think copies. How many business professionals still make multiple copies of sensitive data, just as it’s been done for the last four decades? What does this endless duplication do for regulatory risk, security threats and privacy liabilities? This is a symptom of a larger problem: Far from the data-centric universe we all envisioned, we’re beholden instead to the apps used to create, store, and distribute data. There’s an app for everything, but also a database for every app, leading to dozens of data silos undergoing hundreds of integrations, increasing fragmentation, complexity, and costs. The basic idea, according to Dan DeMers, Cinchy’s CEO, is that the framework aims to remove application data silos by using access-based data collaboration versus standard API-base data integration that involves copying data and branding it with complex app-specific coding. This would be done by access controls set in the data layer. It would also involve: What is Zero Copy Integration? Zero copy integration enables access to data stored in multiple databases simultaneously without the need to move, copy, or reformat the data. This approach not only facilitates faster and easier access to data but also reduces costs and minimizes the risk of errors associated with data movement or transformation. Comparing Traditional Methods with Zero Copy Integration: Traditional Methods: Zero Copy Integration: How It Works: From CDP to Data Warehouse In this scenario, data is accessed from the CDP and shared with the data warehouse, a process known as data sharing. The steps typically involve: How It Works: From Data Warehouse to CDP Conversely, in this scenario, data is accessed from the data warehouse and integrated into the CDP, a process referred to as data federation. The steps typically involve: Real-World Application: How Buyers Edge Utilizes Zero Copy Technology Buyers Edge, a leading procurement optimization company in the food service industry, leverages zero copy technology to access purchase data stored in a data warehouse while building a unified customer profile in a CDP. This allows them to provide better customer insights to their sales and marketing teams. By eliminating the need for data movement, duplication, or reformatting, zero copy technology streamlines data access, harmonizes data for insights and analytics, and provides a real-time holistic view of customers. As data volumes continue to grow exponentially, technologies like zero copy integration will play a crucial role in simplifying data management and facilitating seamless access to valuable insights. Whether it’s optimizing business processes or enhancing customer experiences, zero copy integration empowers organizations to navigate the data landscape with agility and efficiency. Be a zero copy hero and unlock the full potential of your data management strategy. “In today’s digital landscape, companies struggle with islands of data spread across various systems. With this global ecosystem of partners, companies can access all of their data, no matter where it resides, and unlock the power of all of that data within Salesforce — creating more personalized customer interactions and establishing a foundation for trusted AI, in less time and at lower cost.” Brian Millham, President and Chief Operating Officer at Salesforce The Zero Copy Partner Network features initial partners Amazon Web Services (AWS), Databricks, Google Cloud, and Snowflake, and adds Microsoft, all committed to zero copy integrations with Salesforce that give customers a secure and cost-effective way to connect and take action on all of their data New zero copy support for data warehouses and data lakehouses built on open table formats, like Apache Iceberg, with Salesforce Data Cloud, removes the need to copy or move data, so customers can unlock their data, powering Customer 360 experiences with AI, automation, and analytics The network includes Salesforce ISV partners, building new Zero Copy Data Kits to bring valuable new datasets to Salesforce Data Cloud, and Salesforce SI partners including Accenture, Cognizant, Deloitte Digital, and PwC, helping customers with zero copy Salesforce Data Cloud implementations. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 14, 2024in Salesforce, Salesforce Data Cloud, Snowflake
Zero-Copy Integrations
27Apr

Zero-Copy Integrations

At the recent Salesforce World Tour NYC event, Salesforce introduced a new global ecosystem of technology and solution providers designed to assist its customers in leveraging third-party data through secure, bidirectional zero-copy integrations with Salesforce Data Cloud. Tyler Carlson, VP of business development and strategic partnerships at Salesforce, highlighted the key challenge faced by many customers: integrating data from various platforms without creating multiple iterations and losing data lineage. Currently, some startups offer “reverse” ETL services, copying data from customers’ data warehouses or platforms back into systems of engagement. However, this approach requires duplicating data, creating storage spaces, and maintaining data synchronization pipelines. To address these challenges, Salesforce introduced the Zero Copy Partner Network, which brings together ISVs and SIs to eliminate custom integrations and complex data pipelines. This network aims to provide businesses with a more efficient, secure, and user-friendly way to connect data to their applications compared to traditional ETL processes. Zero-copy integration allows teams to access data directly from its source, either through queries or virtual access, without the need for data duplication. Salesforce has pioneered zero-copy bidirectional integrations with Data Cloud partners like Amazon Redshift, Databricks, Google Cloud’s BigQuery, and Snowflake. While integrations with BigQuery and Snowflake are generally available, those with Redshift and Databricks are still in pilot but expected to launch later this year. Salesforce is expanding this network to include its ISV ecosystem, enabling them to build on top of zero-copy connectors to offer enrichment datasets and business applications with zero-copy integration. Additionally, the company is extending this capability to its SI ecosystem, ensuring that global SIs are certified and ready to assist customers with distributed zero-copy integration patterns. 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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April 27, 2024in Salesforce, Snowflake
Harnessing Zero Copy Integration
21Apr

Harnessing Zero Copy Integration

Streamlining Data Management: Harnessing Zero Copy Integration for Efficient Customer Insights Zero copy integration offers a revolutionary approach to accessing and utilizing customer data without the need for burdensome data transfers. By seamlessly linking disparate databases, this innovative technique eliminates the complexities associated with moving, copying, or reformatting data. Let’s explore how zero copy integration can optimize data management processes and enhance the efficiency of customer data platforms (CDPs) alongside traditional data warehouses. Understanding Zero Copy Integration: Zero copy integration, also known as zero ETL (extract-transform-load), facilitates the sharing of data across multiple databases without physically relocating it. This method enables real-time access to data, significantly reducing costs and mitigating the risks of errors inherent in data movement processes. Unlike traditional data replication methods, zero copy integration ensures that data remains in its original location, eliminating the need for redundant storage and synchronization efforts. Good technology standards can actually bring order to the chaos and allow products from different companies to work together, fostering healthy competition and enhancing productivity. That is precisely what Zero-Copy Integration does. Zero-Copy Integration is a framework that eliminates the need for data copies and integration, making it easier to work with applications, analytics, artificial intelligence, and machine learning. Canada’s Digital Governance Council recently announced that Zero-Copy Integration has been published for open access by the public, setting a new standard for data collaboration. Moreover, Zero-Copy Integration prioritizes data-centricity and active metadata over complex code and solution modularity over monolithic design. It also facilitates data governance through data products and federated stewardship, eliminating the need for centralized teams. In addition to boosting the development and deployment of new technologies, Zero-Copy Integration also addresses the growing number of data privacy regulations. By putting data at the center of the process, Zero-Copy Integration ensures greater collaboration and control, positively affecting industries like healthcare, research, banking, and public services. Benefits of Zero-Data Integration Proponents of zero-copy integration and dataware say the framework will lower data storage costs, improve performance of IT teams, improve privacy and security of data, and drive innovation in systems for public health, social research, open banking and sustainability through innovations in: Comparing Traditional vs. Zero Copy Integration: Aspect Traditional Zero Copy Replication Requires copying data to target Data remains in original location Updates Data accuracy dependent on synchronization Real-time access to data Cost Involves data movement expenses No additional data movement costs Regulatory Compliance Complex governance due to data duplication Simplified compliance with source data only Errors Data movement introduces potential errors Minimized risk of errors with no data movement Maintenance Increases complexity with copying and synchronization Streamlined management with no data relocation Implementing Zero Copy Integration: The implementation of zero copy integration varies depending on the platform and direction of data access. Let’s explore how it works in scenarios involving Salesforce Data Cloud and Snowflake data warehouse: Case Study: Buyers Edge’s Zero Copy Success Story: Buyers Edge, a procurement optimization company, leveraged zero copy integration to unify customer profiles in a CDP while accessing purchase data from their data warehouse. By seamlessly integrating Salesforce Data Cloud with their warehouse, Buyers Edge enhanced predictive modeling capabilities, resulting in tailored sales and marketing strategies. Zero copy integration revolutionizes data management practices by enabling seamless data access and eliminating the need for data duplication or relocation. As businesses navigate the evolving data landscape, leveraging zero copy integration can streamline operations, enhance insights, and empower organizations to unlock the full potential of their data assets. MILESTONES / TIMELINE Second half 2023 – Internationalization February 21, 2023 – Information Session (watch above ☝ or via YouTube) February 15, 2023 – ‘Zero-copy’ applications published by DCA February 08, 2023 – Published by Digital Governance Council (Press release) December 15, 2022 – Approved by Standards Council of Canada June-Nov 2022 – Public consultation period 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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April 21, 2024in Salesforce, Salesforce Data Cloud, Salesforce Einstein, Snowflake
Salesforce in a Mega-Data Deal with Informatica
15Apr

Salesforce in a Mega-Data Deal with Informatica

Since Salesforce announced its acquisition of Slack for $27.7B in late 2020, the cloud software mega-giant has paused its acquisition strategy due to factors like rising interest rates, declining revenues, and a laser focus on profitability. However, recent leaks from The Wall Street Journal and other news publications suggest that Salesforce in a Mega-Data Deal with Informatica, is in advanced talks to acquire Informatica in a deal worth over $11B. Informatica is a significant player in enterprise data management, boasting revenues of over $1.51B and a workforce of over 5,000 employees. They specialize in AI-powered cloud data management, assisting companies in processing and managing large volumes of data from various sources to derive actionable and real-time insights. Salesforce in a Mega-Data Deal with Informatica The synergies between Informatica and Salesforce are many, with both companies focusing on consolidating data from multiple sources to provide comprehensive business insights. This aligns well with Salesforce’s strategic shift towards AI-driven data processing and analysis, aiming to enhance generative and predictive capabilities. While Salesforce’s previous acquisition of MuleSoft in 2018 for $6.5B has proven successful in facilitating API connectivity for real-time integrations, Informatica brings expertise in ETL (Extract-Transform-Load), data quality, and data movement to and from platforms like Snowflake and Databricks. This potential mega-data deal underscores the growing importance of data in the tech industry, especially with the emergence of generative AI and large language models (LLMs) that enable deeper analysis of vast datasets. Salesforce’s recent rebranding of its platform to “Einstein 1” underscores the convergence of AI and data within its product suite. The company’s emphasis on “AI + Data + CRM” reflects its commitment to leveraging data analytics for CRM enhancement, exemplified by the growth of its Data Cloud product. Partnering with industry leaders like Snowflake, Databricks, AWS, and Google, Salesforce aims to offer comprehensive data solutions that integrate seamlessly with existing systems. Informatica’s capabilities in ETL and Master Data Management (MDM) align with this vision, particularly in streamlining data integration and ensuring data quality across disparate systems. In final thoughts, while the Informatica acquisition is still pending finalization, it represents a strategic move by Salesforce to strengthen its position in the AI and data-driven CRM market. As Salesforce continues to evolve its product ecosystem, this acquisition signals its commitment to innovation and leadership in the era of AI-powered data 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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April 15, 2024in Generative AI, Mulesoft, Salesforce, Snowflake
Salesforce Einstein Features
13Apr

Salesforce Einstein Features

Salesforce Einstein Discover the power of the #1 AI for CRM with Einstein. Built into the Salesforce Platform, Einstein uses powerful machine learning and large language models to personalize customer interactions and make employees more productive. With Einstein powering the Customer 360, teams can accelerate time to value, predict outcomes, and automatically generate content within the flow of work. Einstein is for everyone, empowering business users, Salesforce Admins and Developers to embed AI into every experience with low code. Salesforce Einstein Features. Einstein Copilot Sales Actions: Sell faster with an AI assistant in the flow of work.Call Exploration: Ask Einstein to synthesize important call information in seconds. Ask Einstein to identify important takeaways and customer sentiment, so you have the context you need to move deals forward.

 Sales Summaries: Summarize records to identify likelihood the deal will close, the competitors involved, key activities, and more. Forecast Guidance: Ask Einstein to inform your forecast and help you identify which deals need your attention. Close Plan: Generate a customized action plan personalized to your customer and sales process. Increase conversion rates with step-by-step guidance and milestones grounded in CRM data. Salesforce Einstein Features Sales Generative AI features: ° Knowledge Creation: ° Search Answers for Agents and Customers: Einstein Copilot Service Actions: Streamline service operations by drafting Knowledge articles and surfacing answers, grounded in knowledge, to the most commonly asked questions. Summarize support interactions to save agent time and formalize institutional knowledge. Surface generated answers to agents’ & customers’ questions that are grounded in your trusted Knowledge base directly into your search page. Search Answers for Agents is included in the Einstein for Service Add-on SKU and Search Answers for Customers is included in the Einstein 1 Service Edition.
Empower agents to deliver more personalized service and reach resolutions faster with an AI assistant built into the flow of work. You can leverage out-of-the-box actions like summarize conversations or answer questions with Knowledge or you can build custom actions to fit your unique business needs. Service Salesforce Einstein Features This Release Einstein CopilotSell faster with an AI assistant. No data requirements
Included in Einstein 1 Sales Edition.hEinstein Copilot: Sales ActionsSell faster with an AI assistant.No data requirements. 
 Call explorer and meeting follow-up requires Einstein Conversation Insights.
Included in Einstein 1 Sales Edition. Generative AIBoost productivity by automating time-consuming tasks.No data requirements. 
 Call summaries and call explorer requires Einstein Conversation Insights.
Included in Einstein 1 Sales Edition. Einstein will use a global model until enough data is available for a local model. For a local model: ≥1,000 lead records created and ≥120 of those converted in the last 6 monthsEinstein Automated Contacts Automatically add new
contacts & events to your CRM≥ 30 business accounts. If you use Person Accounts, >= 50 percent of accounts must be business accounts Einstein Recommended ConnectionsGet insights about your teams network to see who knows your customers and can help out ona deal ≥ 2 users to be connected to Einstein Activity Capture
and Inbox (5 preferred) Einstein Forecasting Easily predict sales forecasts inside
of Salesforce Collaborative Forecasting enabled; use a standard fiscal year; measure forecasts by opportunity revenue; forecast hierarchy must include at least one forecasting enabled user who reports to a forecast manager; opportunities must be in Salesforce ≥ 24 months;Einstein Email Insights Prioritize your inbox with actionable intelligence Einstein Activity Capture enabledEinstein Activity Metiics (Activity 360) Get insight into the activities you enter
manually and automatically from Einstein
Activity Capture Einstein Activity Capture enabled Sales Analytics Get insights into the most common sales KPIs No data requirements. User specific requirements like browser and device apply Einstein Conveisation Insights Gain actionable insights from your sales calls with conversational intelligenceCall or video recordings from Lightning Dialer, Service Cloud Voice, Zoom and other supported CTI audio and video partners.Buyer Assistant Replace web-to-lead forms with real-time conversations. No data requirements – Sales Cloud UE or Sales Engagement. Einstein Opportunity ScoringEinstein Activity CaptuiePrioritize the opportunities most likely to convertAutomatically capture data & add to your CRMEinstein will use a global model until enough data is available for a local model. For a local model: ≥ 200 closed won and ≥ 200 closed lost opportunities in the last 2 years, each with a lifespan of at least 2 days≥ 30 accounts, contacts, or leads; Requires Gmail, Microsoft Exchange 2019, 2016, or 2013 Einstein Relationship Insights Speed prospecting with AI that researches for you. No data requirements. Einstein Next Best Action Deliver optimal recommendations at the point of maximumimpactNo data requirements. User specific requirements like browser and device apply Sales AIGenerate emails, prioritize leads & opportunities most likely to convert, uncover pipeline trends, predict sales forecasts, automate data capture, and more with Einstein for Sales. Generative AIPrompt BuilderEinstein Lead ScoringEinstein Opportunity ScoringEinstein Activity CaptureEinstein Automated ContactsEinstein Recommended ConnectionsEinstein ForecastingEinstein Email InsightsEinstein Activity Metrics (Activity 360)Sales AnalyticsEinstein Conversation InsightsBuyer Assistant Sales AIGenerative AI: 
Feature Why is it so Great? What do I need? Automate common questions and business processes to solve customer requests fasterBoost productivity by auto-generating service replies, summarizing conversations during escalations andtransfers or closed interactions, drafting knowledge articles, and surfacing relevant answers grounded inknowledge for agents’ and customers’ commonly asked questions. Deliver optimal recommendations at the point of maximum impactEliminate the guesswork with AI-powered recommendations for everyoneDecrease time spent on manual data entry for incoming cases and improve case field accuracy and completionAutomate case triage and solve customer requests fasterDecrease time spent selecting field values needed to close a case with chat conversations and improved field accuracySurface the best articles in real time to solve any customer’s questionEliminate time spent typing responses to the most common customer questionsGet insights into contact center operations, understand customers, and deliver enhanced customerexperiencesChat or Messaging channels, minimum of 20 examples for most languagesNo data requirements. User specific requirements like browser and device apply Make sure that your dataset has the minimum records to build a successful recommendation. Recipient Records need a minimum of 100 records,Recommended Item Records need a minimum of 10 records, andPositive Interaction Examples need a minimum of 400 records

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April 13, 2024in Generative AI, Salesforce Einstein, Snowflake
Data Cloud and Snowflake Bidrectional Data Sharing
01Apr

Data Cloud and Snowflake Bidrectional Data Sharing

Salesforce Data Cloud and Snowflake are excited to announce that bidirectional data sharing between Snowflake, the Data Cloud company, and Salesforce Data Cloud is now generally available. In September, we introduced the ability for organizations to leverage Salesforce data directly in Snowflake via zero-ETL data sharing, enabling unified customer and business data, accelerating decision-making, and streamlining business processes. Today, we’re thrilled to share that customers can now also share Snowflake data into the Salesforce Data Cloud, using the same zero-ETL innovation to reduce friction and quickly surface powerful insights across sales, service, marketing, and commerce applications. Data Cloud and Snowflake Bidrectional Data Sharing. Data Cloud and Snowflake Bidrectional Data Sharing Enterprises generate valuable customer data within Salesforce applications, while increasingly relying on Snowflake as their preferred data platform for storing, modeling, and analyzing their full data estate. This integration between Salesforce and Snowflake minimizes friction, data latency, scale limitations, and data engineering costs associated with using these two leading platforms. The Snowflake Marketplace also offers customers the opportunity to acquire new data sets to enhance or fill gaps in their existing business data, driving innovation. By combining enterprise data and third-party data from Snowflake Marketplace with valuable customer data from Salesforce applications, organizations can unify their data and build powerful AI solutions to surface rich insights, driving superior and differentiated customer experiences. “Zero-ETL data sharing between Salesforce Data Cloud and Snowflake is game-changing. It has opened up new frontiers of data collaboration. We’re excited to see how customers are powering their customer data analytics and developing innovative AI solutions with near real-time data from Salesforce and Snowflake, generating incredible business value. Now that this integration is generally available, this kind of innovation will be broadly accessible,” says Christian Kleinerman, SVP of Product, Snowflake. Power Personalized Experiences with Salesforce and Snowflake Data sharing between Salesforce Data Cloud and Snowflake brings together holistic insights, empowering multiple customer-facing departments within any organization to create a truly robust customer 360. As Snowflake’s Chief Marketing Officer, Denise Persson, often states, a true, enterprise-wide customer 360 is the beating heart of a modern, customer-facing organization. The applicability of this integration spans various industries and unlocks new growth opportunities. For example: The bidirectional integration enables data sharing across business systems, Salesforce clouds, and operational systems, facilitating data set analysis and future action planning. This brings actionable insights and drives actions, unleashing a new level of customer experience and business productivity. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more 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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April 1, 2024in Salesforce Data Cloud, Salesforce Marketing Cloud, Snowflake
Salesforce and Snowflake
13Mar

Is Snowflake a Data Cloud?

Is Snowflake recognized as a data cloud? Certainly, Snowflake stands as an encompassing platform integral to the Data Cloud. Uniquely designed for global connectivity, it empowers businesses to navigate diverse data types and scales, accommodating various workloads and fostering seamless data collaboration. Globally, over 400 million SaaS data sets often remain isolated in cloud storage and on-premise data centers, creating data silos. The Data Cloud, driven by Snowflake, eradicates these silos, facilitating the effortless consolidation, analysis, sharing, and monetization of data. Is Snowflake categorized as a database or cloud? Snowflake exclusively operates on cloud infrastructure. With all components residing in public cloud infrastructures (excluding optional command line clients, drivers, and connectors), Snowflake utilizes virtual compute instances for computing needs and a storage service for persistent data storage. What characterizes a data cloud? A data cloud serves as a unified platform for structured, unstructured, or semi-structured data, simplifying data discovery and reducing complexity. It should be capable of collecting, ingesting, and processing data from various on-premises or cloud-based source systems, consolidating it into a single accessible location. Snowflake’s Data Cloud facilitates organizations in effortlessly unifying and connecting to a single copy of all their data. This results in an ecosystem where businesses connect not only to their individual data but also to each other, seamlessly sharing and consuming data and data services. How does Snowflake’s Data Cloud handle different workloads? Snowflake’s Data Cloud efficiently powers diverse data workloads, including Data Warehousing, Data Lake, Data Engineering, AI and ML, Applications, and Cybersecurity. It operates seamlessly across multiple cloud providers and regions, catering to organizational needs from any location within the organization. What storage type does Snowflake employ? Snowflake utilizes scalable Cloud blob storage for its storage layer, accommodating data, tables, and query results. This storage is designed to scale independently from compute resources, allowing customers to adjust storage and analytics requirements independently. Is Snowflake considered a data warehouse or ETL? Snowflake’s capabilities in data loading, transformation, and storage eliminate the need for additional ETL tools, providing an end-to-end solution. Renowned worldwide, many organizations have adopted Snowflake as their primary Data Warehousing solution due to its distinctive features, scalability, and security. Where is Snowflake’s data stored? Snowflake’s database storage layer resides in a scalable cloud storage service, such as Amazon S3, ensuring data replication, scaling, and availability without requiring customer management. The data is optimized and stored in a columnar format within the storage layer, following user-specified database organization. How does Snowflake’s architecture benefit organizations? Snowflake’s architecture offers near-unlimited storage and real-time computing to an extensive number of concurrent users within the Data Cloud. It enables organizations to execute critical workloads on a fully managed platform, leveraging the cloud’s near-infinite resources. What are the advantages of Snowflake’s single platform? Snowflake’s single platform delivers optimal workload performance, full automation, secure global collaboration, Snowflake capabilities for non-SQL code processing, and optimized storage. It encompasses features such as Elastic Multi-Cluster Compute, Cloud Services, and Snowgrid, providing businesses with a comprehensive and fully managed solution. Why opt for Snowflake over competitors? Snowflake’s main advantage lies in its multi-cloud capability, available on major platforms like Azure, AWS, and GCP. This flexibility benefits companies operating in multi-cloud environments, enabling them to query Snowflake data directly from any of these platforms. About Snowflake Inc. Snowflake Inc., an American cloud computing-based data cloud company located in Bozeman, Montana, was founded in July 2012 and publicly launched in October 2014. Operating as a data-as-a-service provider, Snowflake offers cloud-based data storage and analytics services. Like 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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March 13, 2024in Salesforce Data Cloud, Snowflake
Salesforce Data Cloud
05Feb

Salesforce Data Cloud vs Snowflake

A Comprehensive Comparison In the today’s data-driven world, businesses increasingly turn to cloud-based data platforms for managing, analyzing, and deriving insights from their customer data. Among the prominent options available, Salesforce Data Cloud and Snowflake stand out from the crowd. While both platforms offer robust capabilities, they exhibit distinct strengths and weaknesses. This insight looks into the comparison of Salesforce Data Cloud vs Snowflake. Salesforce Data Cloud: Salesforce Data Cloud is a hyperscale customer data platform (CDP) designed to help businesses consolidate all their customer data, including engagement data sourced externally. It establishes a unified view of the customer, empowering businesses to personalize experiences, enhance decision-making, and foster growth. Snowflake: Snowflake is a cloud-based data warehousing platform that facilitates the storage, analysis, and sharing of data for businesses. It encompasses a wide array of features, including an awesome SQL engine, elastic scalability, and compatibility with various data sources. Salesforce Data Cloud vs Snowflake Feature Salesforce Data Cloud Snowflake Focus Customer data General data Strengths Data enrichment, personalization, real-time updates Scalability, analytics, SQL support Weaknesses Less flexible than Snowflake, limited analytics capabilities Not as user-friendly as Salesforce Data Cloud Pricing Based on data volume Based on usage The ideal platform for you will be contingent on your specific needs and requirements. If your primary focus is on managing customer data and enhancing customer engagement, Salesforce Data Cloud proves to be a suitable option. On the other hand, if you require a more versatile data platform capable of handling a broad range of data types and workloads, Snowflake emerges as a better choice. Additional considerations include: Ultimately, the most effective way to determine the right platform for you is to experiment with both and assess which one aligns better with your preferences. Contact Tectonic today to explore Data Cloud and Snowflake for your data needs. Like2 Related Posts Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more 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 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

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February 5, 2024in Salesforce Data Cloud, Salesforce Optimization, Snowflake

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