Craig Stewart

Here how Heineken and others are using Salesforce Data Cloud to underpin their digital strategies.

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As someone who spends a lot of time trying to fix product management/sales team dynamics, I really enjoyed this 20VC podcast episode with Chris Degnan (Snowflake CRO) and Harry Stebbings. Some of the most pertinent PM-relevant takeaways: 🤑 Chris has been with Snowflake from the beginning when they had no customers and no ICP, all the way through to Unicorn, so he's seen it all from an operational perspective (There was so much discovery and iteration going on upfront that I'd say Chris is almost an honorary product manager 😎). 🤑 The best salespeople do the work and are invaluable sources of customer feedback, but aren't gatekeepers and keep product managers involved with customers (and engineers) directly (this shouldn't be controversial but I've seen gatekeeping in more than one company). 🤑 The very best sales teams don't get sidetracked by glitzy-looking enterprise deals and writing 150 feature requests into a contract, but focus on where they can get the fastest payback (I've seen this too many times - blow up the entire roadmap again and again for deals that take too long to close, bully you throughout the relationship and churn after 1 year anyway). 🤑 Product management and sales teams need to work together much more closely (strong, strong, strong agree, of course... product managers need to give sales teams a product they can sell, and sales teams need to respect the wider context that PMs (should) bring to the table) There were also some spicy opinions about Customer Success, which I'm still digesting, but CS leaders might want to put their crash helmets on. Chris sounds like he's a good guy to work for and with, albeit demanding and driven, although maybe I should get a Snowflake PM on my podcast to see how it's going from their end! And, as a well-spoken British podcaster myself, I'm always glad to hear more British cheekiness and dry wit on a podcast 🙂

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After three weeks of #DataPlatform conferences and our research into the Next Intelligent Data Platform continuing to be proven accurate (Power Law of Gen AI), we now break down the Major Announcements from Informatica over the past few weeks. Go take a read to get Our Perspective on everything going on. https://lnkd.in/ehrSwjpY 🤖 AI Innovations: CLAIRE GPT: Generative AI for enterprise data management, ensuring trusted and actionable insights. CLAIRE Co-pilot: GenAI-driven automation for data integration, quality, and governance. 🤝 Databricks Partnership: 📌 GenAI Solution Blueprint for Databricks DBRX: Enables the development of enterprise-grade GenAI applications. 📊 Native Databricks SQL ELT Support: Leverages Databricks' intelligent data warehouse for scalable data transformations. 💡 Free Cloud Data Integration Service via Databricks Partner Connect: Offers no-cost, no-code data loading and integration. 🛡️ Full IDMC Support via Databricks Unity Catalog: Enhances data lineage and governance. 🤝 Snowflake Partnership: Comprehensive Metadata Management: Informatica's solutions break down silos, providing master data management, catalog, and metadata capabilities across Snowflake environments. CLAIRE GPT Integration: Leverages Informatica’s AI engine for enhanced data quality, governance, and management within Snowflake. No-Code / Low-Code Data Pipelines: Simplifies the creation of ETL and ELT data pipelines natively within Snowflake. Security and Compliance: Ensures high-quality, trusted data with robust governance and security measures. 🏆 Accolades: 2024 Databricks Data Integration Partner of the Year: Recognized for industry-leading, AI-powered data integration and management solutions. 📈 Customer Success & Strategic Alliances: Snowflake Integration: Enhanced metadata management and governance. Customer Stories: Transformative use cases from industry leaders like Takeda Pharmaceuticals and Royal Caribbean. Informatica continues to shape the future of data platforms, providing robust solutions to navigate the complexities of digital transformation. #InformaticaWorld #DataManagement #theCUBEresearch #AI #GenAI #Databricks #Snowflake #DigitalTransformation #CLAIREGPT #DataGovernance #CloudIntegration SiliconANGLE & theCUBE

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If you are a customer of Snowflake and Salesforce this integration is game changing. Deeper integration = more ROI as illustrated via 3 industry use case examples below. Data is only valuable to the Business if it’s Accessible, Actionable & can be used in the front office: 💪 Retailers can use Commerce and Service Cloud data w/ POS and supply chain in Snowflake 💪 CPGs can organize Marketing and Sales Cloud in Data Cloud w/ financial and transaction data in Snowflake; and share data via clean room 💪 Media orgs can use 1P data in Data Cloud to power media campaigns via Snowflake clean rooms or Data Cloud ad activations

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The Microsoft Purview Data Governance team are thrilled to announce the expansion of our data quality management capability to all data sources supported by Microsoft Fabric OneLake shortcuts and mirroring. With OneLake shortcuts, you can now activate Purview data quality management for your data lakes in AWS S3, Google Cloud Storage (GCS), and Azure Data Lake Storage Gen 2, without needing to copy or move your data. With OneLake database mirroring, you can now activate Purview data quality management for your data in Azure SQL database, Azure Cosmos DB, and Snowflake with a seamlessly managed one-copy replica. This is one more incremental milestone in the new Microsoft Purview Data Governance solution's journey. Huge kudos to the team who made this milestone happen: Souvik D., Karthik Prabhu, Rohan Singh Jain, Keshav Singh, Arun Prasath, Yuehan Xu, and Shafiq Mannan. Resources to learn more: Data quality management in Microsoft Purview Data Governance: https://lnkd.in/gE92bJGc OneLake shortcuts: https://lnkd.in/gczj9Qmb Purview data quality management for OneLake shortcuts: https://lnkd.in/gRprfxyd OneLake database mirroring: https://lnkd.in/gxpgcG2a Purview data quality management for OneLake mirrored databases: https://lnkd.in/geZVEfct Microsoft Purview Data Governance: Interactive walkthrough https://lnkd.in/g2yN8-fq Getting started https://lnkd.in/g8xQe3d5 Note: The new Microsoft Purview Data Governance solution is currently in public preview. We are marching towards our general availability later this year and to be announced soon. The doc shared above has information on getting started with the public preview.

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Extract and structure data faster in any format with AI-powered accuracy #mulesoft #salesforce #mulesoftIDP

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Check out this Customer Insights Analyzer in Snowflake built by Phani Raj.

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There we are, the deal seems to be off as apparently the two sides could not agree on terms - aka Salesforce apparently was not willing to put the amount of money on the table that Informatica owners asked for. (NB: the rumor mill says that Salesforce was willing to pay "mid 30 dollar per share" - today the shares are down to 31.50). I can also imagine that Salesforce investors were not too happy with this plan, as on the short term profitability (and dividends) likely would have suffered. I still think that this would have been an interesting acquisition for Salesforce as its current data management capabilities are lacking, data management becomes ever more important in an #AI age - and this is exactly what Informatica can offer, on top of adding to integration capabilities. All in all I think that this is a lost opportunity for Informatica. Let's look what'll happen next.

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Great to hear the perspective of Salesforce SVP & former Gartner analyst Ed Thompson on the strategic outlook for AI! Subscribe to ServicesTalk and get notified whenever new episodes publish! #ProfessionalServices #AI #Salesforce

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Antony Elliott points out the perfect use case for answers! If you are using traditional search to find this in unstructured data your reps are wasting their time!

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Why will Snowpark Container Service change the data world in a disruptive way? #snowflake #snowpark #snowparkcontainerservices #snowflakesummit One could argue, that applications running in containers are not new. And that is a fact. One could argue that running containers on a manged Kubernetes cluster is not new. As well that holds true. So why should Snowpark Container Services be a disruptive change for the industry? The reason is how organization work. In bigger organisations we have departments for infrastructure, opertaions and we have other teams responsible for data analytics. And on most days they don’t interacted with each other. Except we, as data analyst need more RAM in our database. As well hopefully not much interaction with the operations guys. Except we need some restore of a database or they need to ask us why a job isn’t running. That changed with the introduction with agile development. To do a proper agile development supporting CI/CD and distributed development (in my opinion the most missed bit) we need to have feature sandboxes. Feature sandboxes are the equivalent of a work folder in java development. But a sandbox consists of a database, a data modeling tool, a model driven code generator, a data profiling tool, a tool being able to check-out and check-in data models into GIT, a deployment tool to transport code from development to test and production systems and a scheduler to run our jobs. Snowflake has covered some of the requirements for the data teams by allowing zero-copy-cloning of database: we are able to develop new “features” (aka stories) on sandbox databases with the full data set. That was already revolutionary but it wasn’t enough. As all the other tools mentioned above were missing and needed to be deployed by the infrastructure or operations team it created unnecessary complexity. Now, by offering Snowpark container service, not only can the database be cloned with a few simple SQL commands, but also the other functions can be covered by starting a service on Snowpark Container Services with simple SQL commands. This means you don’t need to learn how Kubernetes works. Type START SERVICE, and you’re good. That is the revolution. This gives the data teams the power to do everything they need without interacting with other teams. Projects are not blocked anymore because other departments have (usually for a good reason) other priorities than to setup environments for the data team. And the cool thing is: Datavault Builder is now available for Snowfpark Container Services and is covering all the functions of the full DevOps process as a single service: Modeling, code generation, documentation, data lineage, data profiling, historization, bi-temporality, data consumption interface generation, operations, code versioning in GIT, deployment and operations. Watch how it works here: https://lnkd.in/eS6RNgcK

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Salesforce's Einstein Trust Layer is crucial in safeguarding customers' data integrity. Without trust, adopting AI technologies remains a significant challenge for companies. Salesforce is deeply committed to working with our customers and experts so they can reap the rewards of transformative GenAI while ensuring it is a force for good. Learn more about Salesforce's initiatives in AI via the link below. [Link to the article](https://lnkd.in/gA-RcN84)

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Databricks + Slalom + Amperity will share the virtual stage on Wednesday (4/24) at 10a PST. Learn how to turn raw, disconnected customer data into business value.

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❌ Metadata is not simply ”data about data” ❌ On a general level, metadata can include all kinds of permissions and accesses, automations and processes that an org might have. In Salesforce terminology, custom metadata is another story altogether. Metadata is powerful stuff indeed. I can understand Benioff's obsession very well from a business standpoint. Data is transitory, whereas metadata is proprietary. Data can be shared and moved from system to system. Data becomes outdated and obsolete over time. Metadata on the other hand, is something "owned" by Salesforce. It is built unto its core architecture and cannot be as easily decoupled. Metadata forms the basis of interaction with data – by users and applications alike. Salesforce is smart to finally tap into this power, since it knows that metadata is a powerful glue. #Metadata #Data #Salesforce

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What would a combined portfolio of #Salesforce and #Informatica look like for customers or consultants architecting solutions? Sometimes, one's mind doesn't stop processing a particular topic. So I wrote... to share and to get your perspectives.

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This is one of the reasons Salesforce is gaining so much traction in the AI space; they are taking a very wise approach of minding security concerns first and foremost. #salesforce #security #ai #zerocopy https://lnkd.in/e-N8hsuJ

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Top 5 Reasons to attend the ThoughtSpot Data Renaissance event on 12th June! I'm thrilled to be hosting the event and will be joined by some of the most successful data teams in the industry, some of our most innovative technology partners and some of the most informed thought leaders as we discuss what the Data Renaissance is and why it matters for your business. Here's why attending is a must; 📊 Learn From Customers - Ovo Energy, Brambles and Vita Mojo are all sharing their unique journeys of how they have become more data driven and delivered value from their data. Learn from their challenges and understand what shortcuts can be made 📊 Bernard Marr - world renowned futurist, influencer and thought leader will be discussing how GenAI in practice will revolutionise your business 📊 See the Data Renaissance - ThoughtSpot has a differentiated vision as to how Search and AI can come together to deliver an easy and unique experience for the business user. Learn how our innovations can drive adoption, time to insight and value for your business 📊 Cindi Howson - there are few people in the world that understand the Data & Analytics market as well as Cindi. Her unique perspectives and views on how to be successful with data will inspire, inform and educate. 📊 Engage with Innovators - Google, AWS and Snowflake will all be at the event showing their latest and greatest data platforms and AI. A real chance to engage 1 on 1 to understand their product vision and alignment to your strategy The event is the launch of the Data Renaissance so don't miss out, we'd love to see you there. See the link in the comments for more info and to register.

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Gemini in BigQuery changes the game for data engineers and analysts! More productivity ✔️ Improved query performance ✔️ Optimized costs throughout the analytics lifecycle—from ingestion and pipeline creation to deriving insights with AI ✔️ #GoogleCloudNext

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Databricks Sees Compound Systems as Cure to AI Ailments Another well writeen article by Alex Woodie in Datarama "The solution, according to Databricks, is to build compound #GenAI applications that utilize the best of each #LLM. With today’s updates to its #Mosaic AI platform, Databricks says customers can string together compound AI systems that connect LLMs to customers’ data using vector databases, vector search, and retrieval augmented generation (#RAG) capabilities." https://lnkd.in/giuNi_5Q

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