Didier Mamma

Save the date! Next Friday, June 7th, 8:30 ET, 2:30 CEST! Join Stefan Baas, Senior Director Data Analytics at adidas, Databricks EMEA CTO Dael Williamson, and me for a discussion on Generative AI for data and analytics. - Does it have the potential to revolutionize the way business people get answers from data? - What are the implications for data leaders? - How to make your data ‘AI-ready’? - How important to success is technology versus organizational readiness and data culture? Register now:   https://lnkd.in/gttcmYTX #businessintelligence #analytics #artificalintelligence

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Get a primer on Generative BI before you go to #DataAISummit! Tune in to hear from Cindi Howson of ThoughtSpot, Dael Williamson of Databricks, and Stefan Baas of adidas chat about how to most effectively use #GenAI for #BI. Register here: https://lnkd.in/g7XMR66D

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{Siby'News} SIBYLONE ACHIEVES SELECT TIER PARTNER STATUS WITH SNOWFLAKE   Sibylone, Smart4 Engineering’s French Data specialist, today announced that it has achieved Select tier partner status from Snowflake, the AI Data Cloud company. As a Select partner, Sibylone is accelerating the digital transformation of its joint customers by leveraging the performance, flexibility and near-infinite scalability of Snowflake’s Data Cloud.   "Our partnership with Snowflake fits perfectly into our value proposition, which aims to support our clients in modernizing their data ecosystem to enable them to leverage their data assets and address today's and tomorrow's business challenges. The Snowflake platform acts as an accelerator for organizations looking to industrialize their data while benefiting from a managed, scalable service that facilitates the delivery of a wide range of Data and AI products" - Fabrice Haccoun   The partnership between Sibylone and Snowflake combines technology with business and data know-how to help joint customers set up their governed and industrialized corporate data environments and meet the business needs of different business departments.

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How LLMs add value in the enterprise : the 30,000 feet view We are seeing every company and software vendor enabling AI in their business. But what are they actually doing and what has changed ? Here is my take : -The rise of LLMs and associated tools like text splitters, embedded semantic search term association and vector databases -LLMs give the enterprise the horsepower around searching large data and document repositories with the above tools without investment in the infra. -Enterprises and software providers can take these tools and allow them to target their specific data sets such as knowledge bases, config docs, and any other data. -Users can interact via a chatbot and obtain relevant information needed to complete their tasks. Bonus: as the data queried is only the enterprise internal data, data rights and privileges, bad outcomes like hallucinations are avoided. The skill set needed is to choose from the various options within each tool set and tweak for better outcomes. This note is just a high level summary to satisfy curiosity around LLMs and distill some of the hype around AI applications.

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Whether you have been promoted, transitioned from another role or arrived from a different enterprise, CDAOs require a solid plan for their first 100 days. Set up objectives, representative actions and create a personalized plan with Gartner for IT. #GartnerDA #Data #Analytics #NewRole #Webinar

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It was an amazing experience to collaborate with Animesh Kumar to write up this article, from whom I have learnt a lot in the past 3 years! Please read it through and let us know what you think. Follow Modern Data 101 for more such articles. #datastrategy #dataproducts #dataplatform

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Really interesting read on the evolution of Data Warehouses, Data Lakes and Lake Houses and how Databricks and Snowflake are battling for the top spot. https://lnkd.in/egg4P5VG This is one of the more complete analysis I've seen on the evolution of the analytics space and it's big gorilla's. In the end, it gets into the AI discussion of big LLM's vs. small models and how SLM's will have a place in the analytics world, which I completely agree with.

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Join Databricks on September 18 for Data + AI World Tour New York! Discover how leading companies near you are taking control of their data and building custom AI on the Databricks Data Intelligence Platform. Register now!

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Unlock the power of data with Snowflake and Collibra! Dive into the conversation with Alexandre t'Kint to learn more about the importance of finding, trusting, and understanding the right data to enhance the customer AI journey 🚀

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After the announcement of #QlikTalendCloud yesterday (https://lnkd.in/eXvi52z4) we can see the updates starting to flow into #QlikCloud. First a refresh of the navigation and home page for the newly-named "Qlik Talend Data Integration". Along with this there are improvements to the catalog, metadata management, gateways and more in this area... I will share any key bits I find as I get into using it all in more detail. The enhancements just keep on coming! #QlikPartnerAmbassador

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AI has come a long way since I programmed my first MDP agent in 2010 with David Parkes in CS181 at Harvard University. A decade later in late 2020, at GrowthLoop, we started experimenting with #gpt3 for audience building and activation, knowing that as the models improved, we wanted to be ready to bring value to our customers. On March 14, 2023 - the same day #gpt4 and #PaLM launched, we launched one of the first enterprise applications of generative AI with Marve, our natural language audience builder (link in comments). Marve enables marketers to define an audience or goal in natural language, then our system creates relevant audiences from their connected data in their data warehouse in seconds, dramatically reducing the time to value and presenting marketers with new ideas to drive revenue. Since then, we've launched new features based on feedback from our customers like Audience Discovery which proactively builds data-driven audiences based on inferred goals and previously successful audiences. This week at Snowflake Data Cloud Summit, I'll be covering some things I've learned throughout my AI journey and show some ways that applying #AI to a strong #data foundation can bring #omnichannel marketing to the next level. If you're interested in AI, Data, and/or Marketing, come stop by and say hi on Wednesday for a discussion on Generative AI for Marketing. https://lnkd.in/ecqFMEnZ David Wells Sridhar Sundaresan James W. Warner Erin Foxworthy Onil Gunawardana Kamakshi Sivaramakrishnan Luke Ambrosetti Lourenço Mello Ashley Carson (Frizzell) Bill Stratton Sridhar Ramaswamy Harry Lewis

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Some things are just better together.  With Snowflake Native Amplitude, you get all the benefits of Amplitude without your data ever leaving Snowflake. That means one single source of truth for all your enterprise, financial, and behavioral data to inform better product decisions. Learn more:

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🚀 𝐄𝐱𝐜𝐢𝐭𝐢𝐧𝐠 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐋𝐚𝐮𝐧𝐜𝐡 𝐀𝐧𝐧𝐨𝐮𝐧𝐜𝐞𝐦𝐞𝐧𝐭! 🚀 As a former top-tier Snowflake customer and an early adopter of Amplitude, I've always envisioned unifying these robust data ecosystems. Today, I'm thrilled to announce a significant milestone in this journey. 🌟 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐢𝐧𝐠: 𝐒𝐧𝐨𝐰𝐟𝐥𝐚𝐤𝐞 𝐍𝐚𝐭𝐢𝐯𝐞 𝐀𝐦𝐩𝐥𝐢𝐭𝐮𝐝𝐞 🌟 You can now drive your Amplitude analytics experience directly from your source of truth. With this launch, the power of Amplitude Insights is fully integrated with your Snowflake data—all in one place! 🔹 𝐆𝐚𝐦𝐞-𝐂𝐡𝐚𝐧𝐠𝐢𝐧𝐠 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬: * 𝐔𝐧𝐢𝐟𝐢𝐞𝐝 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞:: Run the same incredible Amplitude experience using your Snowflake data. * 𝐑𝐞𝐠𝐮𝐥𝐚𝐭𝐨𝐫𝐲 𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞: Maintain key regulatory constraints on data processing locations. * 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬: Leverage the combined power of Amplitude and Snowflake for unparalleled analytics. This is a game-changer for anyone looking to harness the full potential of their data while adhering to strict regulatory requirements. Ready to revolutionize your analytics experience? https://bit.ly/3yQBQ5m #DataIntegration #Analytics #Amplitude #Snowflake #ProductLaunch #DataRevolution #TechInnovation

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Coming back from #GoogleCloudSummit in #TLV it seems like we just started a new race. Not that long time ago it was a different race ,#BigData and #LakeHouse race. What can we learn from the previous race ? 1. Big Data initiatives frequently underestimate the technical and organizational challenge , this might lead to a project failures. 2. Neglecting Data Quality and Governance - Many BigData projects fail due to poor data quality. 3. Lack of Talent and Diversity 4. Failure to integrate Data Silos and Modernize infrastructure 5. Understanding the Organizational and Culture Challenges - becoming a data-driven organization requires more then just a technology ; it necessitates a fundamental shift in mindset , skills and organisational practices. Are we still on the same race , please let me know what you think ? Exciting time ahead of us...

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NEW BLOG! Want to know more about data warehouse benefits and use cases? Read the new blog by Federico Razzoli, Vettabase Founder: https://lnkd.in/eMPDuS2j #datawarehouse #database #databases

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