Snowflake

12Dec

Data Cloud Credits

Credits are the currency of usage in Salesforce Data Cloud, where every action performed consumes credits. The consumption rate varies based on the complexity and compute cost of the action, reflecting different platform features. Data Cloud Pricing Model The pricing model for Data Cloud consists of three primary components: Data Service Credits Each platform action incurs a specific compute cost. For instance, processes like connecting, ingesting, transforming, and harmonizing data all consume ‘data service credits’. These credits are further divided into categories such as connect, harmonize, and activate, each encompassing multiple services with differing consumption rates. Segment and Activation Credits Apart from data service credits, ‘segment and activation credits’ are consumed based on the number of rows processed when publishing and activating segments. Monitoring Consumption Currently, Data Cloud users must request a consumption report from their Salesforce Account Executive to review credit and storage usage. However, the new Digital Wallet feature in the Summer ’24 Release will provide users with real-time monitoring capabilities. This includes tracking credit and storage consumption trends by usage type directly within the platform. Considerations and Best Practices To optimize credit consumption and ensure efficient use of resources, consider the following best practices: Final Thoughts Credits are integral to Data Cloud’s pricing structure, reflecting usage across various platform activities. Proactive monitoring through the Digital Wallet feature enables users to manage credits effectively, ensuring optimal resource allocation and cost efficiency. Content updated June 2024. 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

December 12, 2023in Salesforce Data Cloud, Snowflake

14Sep

Snowflake and Customer 360 Data Model

What is data modelling in Snowflake? Snowflake and Customer 360 Data Model Data modeling is the process of organizing and mapping data using simplified diagrams, symbols, and text to represent data associations and flow. Engineers use these models to develop new software and to update legacy software. Data modeling also ensures the consistency and quality of data. What is Customer 360 Data Model? Snowflake and Customer 360 Data Model Customer 360 refers to a comprehensive view of a customer’s data, encompassing every interaction from website inquiries to product purchases to customer support tickets. It ensures that every department within a company accesses the same accurate information about the customer. Exploring Data Modeling in Snowflake Data modeling involves organizing and mapping data using simplified diagrams, symbols, and text to illustrate data associations and flow. Engineers utilize these models to develop new software and update existing ones, ensuring data consistency and quality. Unifying Business and Customer Data Break down silos and consolidate customer data into a unified platform using native-first and third-party connectors in Snowflake. These connectors securely ingest data from various sources, enriching customer profiles and resolving identities seamlessly. Enriching Profiles and Resolving Identities-Snowflake and Customer 360 Data Model Enhance customer profiles securely with a plethora of data sets available in Snowflake Marketplace. Resolve identities seamlessly using applications from leading providers native to the platform. Managing Consent and Responding to Data Subject Requests Adhere to customer data consent choices and comply with global privacy regulations by swiftly and effectively responding to data subject requests. Understanding the 360-Degree Customer View The 360-degree customer view is a coveted goal for B2C marketers, aiming to aggregate and unify customer interaction touchpoints. Achieving this comprehensive view enables businesses to better understand the customer journey, personalize experiences, and enhance engagement. Snowflake and Customer 360 Snowflake’s Data Cloud tackles the challenge of consolidating disparate data sources in Martech stacks. By collecting and unifying customer 360 data points into a SQL data warehouse, Snowflake empowers marketers to eliminate data silos and respond to customer behavioral trends promptly. Snowflake and Customer 360 Data Model: Evolution of Customer 360 The marketing technology landscape has evolved, with organizations shifting focus to centralized data and new marketing applications. This shift involves aggregating customer data centrally into Customer 360 profiles, enabling tailored marketing campaigns and improved customer experiences. CDPs: The Latest Incarnation of Customer 360 Customer Data Platforms (CDPs) have emerged as solutions to the Customer 360 challenge. By consolidating and organizing customer data, CDPs empower marketers to personalize customer journeys across channels effectively. Tectonic’s Role in Advancing Data Strategies-Snowflake and Customer 360 Data Model Tectonic assists businesses in embracing a composable architecture, future-proofing data structures, migrating data to the cloud securely, and creating a single source of truth for easy analysis of customer data. The Importance of Omnichannel Data in Marketing Understanding omnichannel data is crucial for marketers seeking to improve customer experiences and drive revenue. Omnichannel data encompasses every customer interaction, offering insights into behaviors, preferences, and values. Building a Customer 360 Crafting a holistic view of customers and their journey involves mapping touchpoints, identifying data sources, integrating data into a centralized location, and deriving insights to create customer profiles. Why a Robust Cloud Data Platform is Essential for Omnichannel A robust cloud data platform enables marketers to leverage a single source of truth, analyze streaming data, and facilitate collaboration across teams while ensuring compliance with privacy regulations. “Being customer-centric requires us to have a data-driven culture. We must ask ourselves how we can optimize the supply chain, product design, predictability and propensity of customers to buy our products. These are all data challenges.” Fabio Luzzi, VP of Data Science and Engineering, Tapestry The 360-degree customer view is the Holy Grail of B2C marketers: often sought but frequently unattainable. Companies that aspire to the Customer 360 view seek to aggregate and unify customer interaction touchpoints — from online transactions, social media, forums, and physical touches to third-party interactions, customer support, and service — to better understand the customer journey, meet demand, and personalize the customer experience. The challenge, of course, is that the customer data is spread across these numerous, various touchpoints. Without system synchronization, errors and duplicate records can become an ongoing problem. In the not-too distant past, interactions were largely limited to physical touch points or the phone. With the explosion of new interaction platforms, the job of aggreggating these disparate data sources has proven to be difficult. To really get a handle on all this data, modern B2C marketers need to engage with data management, data storage, data analytics, and often ML and BI tools to merge, unify, and then analyze these transactions to drive business insight. SNOWFLAKE AND CUSTOMER 360 The number of tools deployed in the average Martech stack has exploded from just a few to more than 90 SaaS applications. Marketers have struggled to consolidate these disparate data sources to both quickly react to customer behavior and also to report internally on performance. Snowflake’s Data Cloud solves this challenge, which collects and unifies all customer 360 data points — semi-structured or structured — into an easy-to-query SQL data warehouse that integrates with leading data analytics, BI, ML, and data management tools. This allows marketers to eliminate data silos and react to customer behavorial trends with timely and personalized campaigns. The world of marketing technology has evolved quickly. Although the quest for a single customer view remains, organizations are now focusing on how to create new marketing applications that centralize data. There’s a not-so-quiet (r)evolution going on in the world of marketing technology. Privacy-driven changes in the digital ecosystem are forcing companies to adopt a first-party data strategy with Customer 360 profiles at its center. But that’s not what this revolution is about; Customer 360 profiles have been part of marketing systems going back to Salesforce’s original Customer Relationship Management (CRM) platform. What is changing is not the “what” —a single customer view, but the “how”. What if Customer Data was aggregated centrally, organized into

September 14, 2023in Salesforce Implementation Services, Salesforce Optimization, Salesforce Personalization, Snowflake

13Sep

The Crucial Role of Data and Integration in AI at Dreamforce

Understanding The Crucial Role of Data and Integration in AI at Dreamforce At this year’s Dreamforce, AI is the star of the show, but two essential supporting actors are data and integration. Enterprises are increasingly recognizing the importance of unifying their diverse data sources for effective analysis and swift action, and the race to harness AI makes this integration even more critical. Integration is key not only for merging data but also for automating end-to-end processes, enabling organizations to move faster and deliver better outcomes to customers. Crucial Role of Data and Integration in AI at Dreamforce. It’s no surprise that MuleSoft, acquired by Salesforce five years ago, is now a major contributor to Salesforce’s growth. Brian Millham, President and COO at Salesforce, highlighted this during the company’s recent Q2 earnings call: “In Q2, nearly half of our greater than $1 million deals included MuleSoft. As customers integrate data from all sources to drive efficiency, growth, and insights, MuleSoft has become mission-critical and was included in half of our top 10 deals.” Breaking Down Silos Param Kahlon, EVP and General Manager for Automation and Integration at Salesforce, recently discussed the investments customers are making in data and integration. He emphasized the importance of breaking down operational silos: “We are in the business of breaking silos across systems to ensure that data can travel seamlessly through multiple systems and people for processes like order-to-cash or procure-to-pay. Our technology connects these dots.” The surge in AI interest has increased the urgency to act, as Kahlon explained: “Creating data repositories for AI algorithms requires real-time data across silos, driving significant demand for our integration solutions.” Consolidating Data Enterprises have long struggled with data consolidation due to monolithic application stacks with separate data stores. This has been a challenge even within Salesforce’s own products. Last year, Salesforce introduced a Customer Data Platform (CDP) called Data Cloud, which includes a real-time data layer named Genie. Kahlon elaborated on its significance: “Data Cloud’s strength lies in its understanding and storage of Salesforce metadata. This native integration allows for real-time actions within Salesforce, enhancing the ability to aggregate, reason over, and act on data.” For example, when a customer contacts a bank, Data Cloud can compile their ATM usage, website interactions, and recent support cases, providing the agent with a comprehensive view to better assist the customer. Leveraging Metadata for AI Salesforce’s metadata layer, which has been fine-tuned over two decades, gives it a distinct advantage. Kahlon noted: “This metadata-based architecture allows us to create meaningful AI algorithms that are natively consumed within Salesforce, enabling visualization and action based on real-time data.” This is crucial for training the underlying Large Language Model (LLM) accurately, ensuring generated content is contextually grounded and trustworthy. Kahlon emphasized: “The trust layer is essential. We need to ensure no hallucination or toxicity in the LLM’s responses, and that communications align with our company’s values.” Real-Time Data and API Management Data Cloud’s ability to connect to other data sources like Snowflake without duplicating data is a significant benefit. Kahlon commented: “Duplicating data is not desirable. Customers need real-time access to the actual source of truth.” On the integration front, APIs have simplified connecting applications and data sources. However, managing API sprawl is crucial. Kahlon explained: “Standardizing API use and publishing them in a centralized portal is essential for reusability and consistency. Low-code platforms and connectors are becoming increasingly relevant, enabling business users to access data without relying on IT.” Automation and AI The demand for automation is growing, and low-code tools are vital. Instead of integration experts being overwhelmed, organizations should establish Centers for Excellence to focus on creating reusable connectors and automations. Kahlon added: “Companies need low-code tools to involve more business users in the transformation journey without slowing down due to legacy applications.” In the future, AI may further ease the workload on integration specialists. MuleSoft recently introduced an API Experience Hub to make APIs discoverable, and AI might eventually help monitor execution logs and manage APIs more effectively. Kahlon concluded: “AI could help developers find and use APIs efficiently, enhancing security and governance while simplifying access to data across the organization.” 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

September 13, 2023in Mulesoft, Salesforce, Salesforce Einstein, Snowflake

15Jun

Scale Data and Analytics in the Cloud

Winning in the Data Economy In the rapidly growing data economy, enterprises are eager to gain a competitive edge. This data economy, which revolves around the global supply and demand for data and data-driven applications, continues to expand as more organizations seek critical insights to drive their success. Scale Data and Analytics in the Cloud. The value of data isn’t a new concept. Companies acquired other companies for the sole purpose of obtaining their data – customers, prospects, etc. The value of actionable data is a bit newer. Whereas we once marketed to prospects based primarily on historical data, data-driven applications let us market at the right time on the right channel with the right message. To understand what it takes to excel in the new data economy, Tableau partner Snowflake surveyed business and technology leaders. Their research highlighted the characteristics of the leaders and laggards, emphasizing the importance of a strong data strategy for achieving successful outcomes. Industries like financial services, health and life sciences, and retail are still struggling to fully benefit from the data economy, often finding it challenging to unlock the full value of their data. Here are four key actions that can help organizations win in today’s data economy and achieve tangible results: 1. Create a Strong Data Culture A robust data culture is foundational for realizing the value of data. Organizations that prioritize becoming data-driven see significant benefits: Jennifer Belissent, Principal Data Strategist at Snowflake, emphasizes how a cloud-enabled data culture accelerates time-to-value by breaking down organizational silos. Tableau offers a playbook to help organizations build, expand, and mature their data capabilities. 2. Adopt an AI-Driven, Enterprise-Ready Analytics Platform Data leaders utilize AI-driven enterprise analytics platforms like Tableau, which provide trusted predictions and insights to scale decision-making. Traditional solutions often fall short in delivering speed to insight and self-service capabilities. Tableau, particularly with Tableau Cloud, offers an easy-to-scale solution that manages and analyzes data across various sources, supporting meaningful impact and agility. Tableau Cloud’s Advanced Management capabilities enhance security, usability, and scalability. Additionally, Tableau Accelerators—over 100 ready-to-use, in-product dashboard starters—support various industries, enabling comprehensive analysis and problem-solving. 3. Migrate to the Cloud Cloud adoption is accelerating as organizations pursue data-driven digital transformations. The cloud offers flexibility, agility, scalability, reduced IT overhead, and increased resilience and performance. Key considerations for cloud migration include: Whether opting for on-premise, hybrid, or full cloud migration, Tableau connects to data wherever it resides, fueling insights across the business. Tableau’s own journey to the cloud involved evaluating criteria, enhancing collaboration, and applying new data management processes, resulting in a unified source of truth. 4. Choose the Right Partners to Scale Cloud-Native Analytics Selecting partners that facilitate cloud-native analytics is crucial. Ideal partners should offer: Snowflake and Tableau exemplify these qualities, addressing data and organizational demands. Snowflake provides extensive data storage and processing, while Tableau offers intuitive, self-service analytics. This partnership has helped enterprises like Cart.com achieve significant revenue growth by embedding Tableau analytics in Snowflake’s platform. Embrace the Data Economy with Cloud-Native Analytics Regardless of where your organization stands in the data economy, taking steps to leverage cloud-native analytics can unlock numerous opportunities. Tableau continues to invest in its platform to help organizations thrive with data in the cloud, offering expert advice, solutions, and valuable partnerships. By adopting these strategies, your organization can become a leader in the data economy and achieve remarkable results. 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

June 15, 2023in Salesforce Data Cloud, Snowflake

26May

What Makes Snowflake So Popular?

Why opt for Snowflake over its competitors? What Makes Snowflake So Popular? One of Snowflake’s standout features is its multi-cloud capability, being accessible on major cloud platforms like Azure, AWS, and GCP. This is particularly advantageous for companies operating in multi-cloud environments, as they can seamlessly query Snowflake data from any of these platforms. Snowflake distinguishes itself as a true self-managed service, eliminating the need for users to handle hardware selection, installation, configuration, or management. Moreover, there is minimal software involvement, with ongoing maintenance, management, upgrades, and tuning efficiently managed by Snowflake. If your scaling requirements are primarily related to data warehousing, Snowflake’s data-centric scalability makes it a preferred choice. On the other hand, AWS might be more suitable for general infrastructure scalability across diverse cloud infrastructure components. Organizations opt for Snowflake’s cloud-built data warehouse to achieve significant benefits. These include reducing query times from hours to seconds, providing universal access to all business users, handling structured and semi-structured data swiftly, and doing so more cost-effectively compared to other data analytics platforms. Snowflake’s storage and compute separation enables seamless sharing of live data across business units, eliminating the need for data marts or maintaining multiple data copies. The flexibility to scale virtual warehouses based on specific needs, without concerns about underlying hardware, sets Snowflake apart. Additionally, its pricing model and central data repository contribute to enhanced flexibility, scalability, and cost-effectiveness. Furthermore, Snowflake allows users to share data with partners and customers, irrespective of region or cloud, fostering collaboration on a global scale. If you would like learn more about Snowflake cloud-build data warehouse, contact Tectonic today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

May 26, 2023in Salesforce Development Services, Snowflake

23Jan

Snowflake Database

What is Snowflake Database? Snowflake Database serves as the repository for an organization’s structured and semi-structured data sets, facilitating processing and analysis. It offers automated management of various aspects of data storage, including organization, structure, metadata, file size, compression, and statistics. Snowflake: The Global Data Cloud Platform Snowflake stands as a unified global platform powering the Data Cloud, connecting businesses worldwide across diverse data types, scales, and workloads, fostering seamless data collaboration. Understanding Snowflake Database Snowflake, a relational database hosted in the cloud, serves as a data warehousing solution. Leveraging infrastructure from Google Cloud Platform, Azure, and AWS, it combines traditional database features with innovative functionalities. Snowflake: More Than Just a Data Warehouse Snowflake’s Data Cloud encompasses a pure cloud-based SQL data warehouse, uniquely engineered to handle all data and analytics aspects. It offers high performance, concurrency, simplicity, and affordability unmatched by other data warehousing solutions. Snowflake Database’s Role in ETL Processes Snowflake streamlines data loading, transformation, and storage, eliminating the need for additional ETL tools. Its unique features, scalability, and security have led many organizations worldwide to adopt it as their primary Data Warehousing solution. Snowflake’s Integration with SQL and Python Built on a new SQL database engine, Snowflake’s data warehouse architecture is tailored for the cloud. Moreover, Snowflake provides first-class Python APIs for managing core resources, enabling seamless integration without SQL queries. Challenges and Advantages of Snowflake Despite its advantages such as scalability, performance tuning, and data security, Snowflake faces challenges like higher costs and limited support for unstructured data. Snowflake’s Position in Comparison to Other Databases Snowflake offers faster, easier-to-use, and more flexible data storage and analytic solutions compared to traditional offerings. It is not built on existing database technology or big data software platforms like Hadoop. Ownership and Integration Snowflake operates on major public clouds like AWS, Azure, and GCP, offering pre-warmed virtual machines to support rapid compute. Salesforce had a stake in Snowflake but sold its holdings, making Snowflake an independent entity. Snowflake vs. Salesforce: Choosing the Right Solution Snowflake is preferable for businesses requiring a versatile data platform, whereas Salesforce Data Cloud suits organizations already using Salesforce products due to its seamless integration. Some companies utilize both platforms for diverse 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

January 23, 2023in Salesforce, Salesforce Data Cloud, Salesforce Development Services, Salesforce Implementation Services, Snowflake

19Oct

Salesforce Genie Announced

Salesforce Genie announced this year is an innovative data platform recently unveiled at Dreamforce 2022, heralding the world’s first real-time CRM. Genie is the driving force behind Salesforce’s entire Customer 360 platform, delivering hyper-scale, real-time data capabilities. With Genie, any business can harness the power of data to create magical customer experiences, offering seamless, personalized interactions across sales, service, marketing, and commerce. It adapts effortlessly to evolving customer needs. Consider scenarios we encounter daily: the frustration of lengthy customer support calls navigating purchase history, or the challenge of locating specific items on cluttered e-commerce websites. These situations underscore the demand for real-time updates in every customer interaction, a demand that Genie aims to fulfill. In the last 12 hours alone, the volume of stored customer data worldwide has doubled, explaining the delays in customer support. However, with Salesforce Genie, businesses can make sense of their data regardless of source, system, or channel. This unified data drives unprecedented levels of personalization, akin to magic. Salesforce Genie’s Key Features: Genie is pivotal for various industries leveraging Salesforce, like banks managing vast customer records and administrative tasks. Salesforce aims to enhance data utilization without altering existing approaches. Comparison with Salesforce CDP: Genie transcends traditional Customer Data Platforms (CDPs) by: How Genie Works: Genie ingests and stores real-time data streams at scale, integrating them seamlessly with Salesforce data. It consolidates data from diverse channels, legacy systems via MuleSoft, and proprietary data lakes through connectors. Core Pillars of Salesforce Genie: Salesforce Genie’s Extensibility: Genie partners with leading data providers such as Snowflake and Amazon SageMaker, enabling seamless integration and real-time data sharing without data movement. Unified Customer 360 Use Cases: Genie unifies data across Salesforce’s Customer 360 products for various departments: In essence, Salesforce Genie revolutionizes data integration and utilization, enabling businesses to deliver unparalleled customer experiences across all touchpoints. 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

October 19, 2022in Hyperforce, Mulesoft, Salesforce, Salesforce Data Cloud, Salesforce Marketing Cloud, Salesforce Optimization, Salesforce Sales Cloud, Salesforce Slack, Snowflake

20Oct

Snowflake and Salesforce Marketing Cloud

Harnessing the Power of Salesforce Marketing Cloud and Snowflake Two of the most influential trends in marketing technology (MarTech) and analytics today are Salesforce’s Marketing Cloud (SFMC) and Snowflake’s data warehousing platform. SFMC offers marketers a robust Journey Builder experience, while Snowflake eliminates data silos, making more data accessible to analysts than ever before. Both platforms are next-generation, cloud-first solutions that open new possibilities for marketers and are already helping to create more compelling and relevant experiences for consumers. A shared commitment to simplifying the end-user experience while unlocking a vast array of new data capabilities makes these solutions powerful examples of “soft technology.” Soft Technology: Snowflake and SFMC “When I speak about the power and virtues of technology, I am referring to soft technology: technology that is flexible, that is under our control.” — Don Norman What makes a technology great is its ease and flexibility for end users. Both SFMC and Snowflake simplify the user experience for their target users with remarkable results. SFMC’s Journey Builder allows marketers to build sophisticated journey orchestration flows on a canvas similar to how they might draft a journey on a whiteboard. Once configured, there’s no need to call IT for support; it’s time for delivery. Snowflake targets analysts, data engineers, and data scientists, breaking down data silos and removing traditional storage and processing constraints. This allows them to focus on solving business problems rather than dealing with perpetual data consolidation and cleansing. Snowflake also simplifies working with different types of data, such as unstructured data like logs or customer activity signals, through its “variant” datatype. The Perils of “Hard Technology” for SFMC Users “Hard technology remains unheedful of the real needs and desires of users. It is a technology that, rather than conforming to our needs, forces us to conform to its needs. Hard technology makes us subservient;” — Don Norman SFMC’s Journey Builder users are most productive when their source data is well-prepared for marketing purposes. However, as marketing needs evolve, new customer profile data and segments are required, often necessitating IT intervention and the use of complex SQL queries or programming languages. An inefficient process often emerges: This lengthy process can slow down time-to-market for campaigns and hinder marketing agility. Bridging Snowflake and SFMC to Avoid Hard Technology Low-code and visual SQL tools allow campaign analysts to remain business-focused and meet most of their daily data needs without relying heavily on IT. These tools are now more powerful thanks to modern data warehousing platforms like Snowflake, which supports SQL-like querying of unstructured data directly. Low-code solutions help marketers maintain productivity within SFMC’s Journey Builder by enabling them to autonomously explore and retrieve new customer data and segments. Checklist for Low-Code & Visual SQL Tools For maximum impact, look for low-code and visual SQL tools that: Simplifying Data Integration with Skyvia, Integrate.io, and GetCensus Skyvia Skyvia allows you to replicate Salesforce Marketing Cloud data to Snowflake with minimal configuration. It creates tables for cloud data automatically and keeps the data updated with incremental updates. Integrate.io Integrate.io provides a lightning-fast CDC platform for Salesforce data integration, offering robust ETL and ELT capabilities to connect your Salesforce data with hundreds of other apps. Integrate.io’s low-code interface allows for easy configuration and seamless data migration. GetCensus GetCensus enables data synchronization between Snowflake and Salesforce Marketing Cloud in four simple steps: By leveraging these tools and platforms, marketers can enhance their campaigns and improve customer experiences through efficient and effective data integration and management. 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

October 20, 2021in Salesforce Marketing Cloud, Snowflake

Snowflake and Customer 360 Data Model

What Makes Snowflake So Popular?

Snowflake Database

Salesforce Genie Announced

Recent Posts

Understanding the Causes of Disillusionment with Generative AI

Meta Joins the Race to Reinvent Search with AI

Google Prepares AI-Powered Jarvis Agent

Is the Future Agentic for ERP?

AI is Transforming Threat Detection

Contact Us

Be in touch today — and start your business on a path to success.

Category

Archives