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Snowflake
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Volunteer Experience
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Founder
Lamorinda Kiva Club
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Over $25,000 loans to hundreds of entrepreneurs in 57 developing countries.
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Curtis Liu
Big announcement today- we’re unlocking Snowflake data for everyone! 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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34 Comments -
Jaap Westrik
Snowflake's Investor Day presentation this week was a great showcase of how CRO-CFO alignment is crucial in driving company strategy. The session had plenty of evidence of effective collaboration between the Sales and Finance teams. For example, Snowflake's FY2025 sales compensation redesign is directly tied to the company's strategic objectives to drive logo and consumption growth. This is impossible for a CRO or CFO to achieve alone; they have to do it together. My favorite piece of evidence of Snowflake's CRO-CFO alignment is the chart below (from last year's deck), which shows how sales productivity dictates new sales investment. Sales productivity is defined as (x) net new ACV in $ millions divided by (y) AE headcount at fiscal year-end. The 1.0x threshold metric means the company will only invest in new sales headcount when AEs on average close at least $1 million in net new ACV annually. In other words, as long as Finance sees the productivity, Sales will get more budget to hire more reps. This defines accountabilities and rules of engagement: The CFO proactively supports the CRO's evolving needs, and the CRO has clear expectations about driving efficient growth. This chart is easy to put on a slide, but achieving the level of alignment required for a common CRO-CFO definition of "sales productivity" is very difficult. Few companies succeed at this, but Snowflake shows it can be done. What makes Snowflake different? Here's a hint: The previous CEO used to call himself "Frank (Anti-Silo) Slootman" on his LinkedIn profile. That tells you everything you need to know. CRO-CFO alignment starts with the CEO (not with the tech stack). #CFO #CRO #CMO #CCO #RevOps #RevenueOperations #SalesOps #GTM #Finance #RevenuePlanning #RevenueForecasting #Marketing #Sales #Enterprise #SaaS #CustomerSuccess #SalesQuotas #SalesTerritories #SalesProcess #CapacityPlanning #SalesCompensation #Compensation #ResourceAllocation #VentureCapital #PrivateEquity #StrategicFinance #FPandA #Snowflake #InvestorDay #CapitalAllocation #SalesProductivity
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10 Comments -
Nick Polati
Synch Forecasting is our biggest launch to date! What makes Synch forecasting different? 🔹 One click Pipeline Waterfall (Video Below) 🔹 Out of the box configuration allowing fast implementation 🔹 Ability to add additional forecast weights based on historical deal data 🔹 Tracking historical forecasts and accuracy with snapshots at time of submission 🔹 Manager override ability with highlighted deltas for accuracy Check out what the future of forecasting looks like below: (https://lnkd.in/gGyneZFu)
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Deb Banerjee
The Anvilogic-Snowflake partnership has been playing out for over the past year, and we are beginning to see trends emerging in enterprise SOC adoption of Snowflake. (1) The most common trend has been the ingest of high volume (and high value) logs into the Snowflake data lake at an acceptable cost compared to their Splunk license. Crowdstrike FDR and AWS Logs (CloudTrail and VPC Flow) are the top data sources here. Cloud application logs are next. Retention is for 1 yr (at S3 costs!), and, yes, its all hot storage. (2) Customers demand the ability to correlate these Snowflake events with their legacy Splunk event which preserves years of prior investments in their people and process. Only Anvilogic can correlate across Snowflake and Splunk data lakes for threat detection use cases using a patented detection architecture that minimizes data movement across these lakes. We have large financials that have adopted this deployment architecture. (3) Multi-cloud customers are able to simultaneously use an AWS Snowflake (for logs arising in AWS) side-by-side with their Azure Snowflake(for their defender, O365 and AD logs) thereby storing logs on the “local” clouds.. Again, Anvilogic can correlate across these two Snowflake instances while minimizing data movement. A very large transportation company is deployed on this multi-snowflake architecture. (4) Finally, making normalized security events available in the Snowflake elastic data platform has allowed enterprise data science teams to bring their own ML(trained to their enterprise context) augmenting Anvilogic ML. We have a large financial whose data science team had developed security baselines in Snowflake that are integrated with Anvilogic detection rules. For now, there is great interest in trialing security copilots using GenAI, and we expect them to enter deployment in the next few quarters.
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5 Comments -
Josh Klahr
Sitting in on an insightful talk from Noah Arliss and Hossein Ahmadi on core platform performance improvements at Snowflake. If you want to learn about the impact of these improvements (as measured by the Snowflake Performance Index) and also catch up on all of our latest platform announcements, follow this link: https://lnkd.in/grNNtsQe
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Soumyadeb Mitra
We are very excited to hear about Snowflake Artic. Of many possible applications, one key data pipeline step it can revolutionize is data cleanup. Here are a few data cleanup steps I’ve built that could have been replaced by LLMs: ▪️ Standardizing a person’s name across different data sources. Ex: Mapping Robert, Rob, Bob, R. => Robert ▪️ Standardizing a job title across sources. Ex: Mapping Software Engineer, Sr. Software Developer, Software Hacker => “Software Engineer” ▪️ Extracting the City, Zip, Country from the address. Ex: “123 W 83rd Street, NYC, 10024, US” => City:New York, Zip: 10024, Country: USA ▪️ Standardizing dirty event data: Ex: product_clicked, product_clicked_ios, product_clicked_top_of_page, product_clk => product_clicked Often data teams waste time building and maintaining these data cleanup pipelines. RudderStack Profiles makes it easy to integrate LLMs into your c360 data pipeline to handle cleanup. What data cleanup tasks do you want to eliminate with LLMs?
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3 Comments -
James Hall
This week marked a watershed moment for Snowflake: We launched #SnowflakeArctic, a state-of-the-art large language model uniquely designed to be the most open, enterprise-grade LLM on the market. Arctic not only outperforms many leading open models, but we brought it to market at one-eighth of the cost and in less than three months compared to other models. Arctic will significantly enhance our ability to deliver reliable, efficient AI to our customers. By delivering industry-leading intelligence and efficiency in a truly open way to the AI community, we are furthering the frontiers of what open-source AI can do. https://lnkd.in/eueT5Wcs
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Ania Moniuszko
“Sometimes we need to go slow to go faster.” This quote from Thomas Hughes, a woodworker from Berkeley, is so relevant to everything we build. When we are mindful, use precautionary principles and build not just features, but a system that will serve everyone who uses we go faster. Cleaning up a mess, loosing customers and credibility are high prices to pay. In the documentary film about Thomas Hughes which just premiered at the SF Documentary festival, the quote was about how much wood is wasted if you go too fast. In the case of snowflake, there is so much data loss which can lead to bad outcomes for so many. The company’s reputation is damaged. As you are building products think about the periphery. Build your requirements not just around the vision for the product, but also around stability, human and environmental benefit, and long term goals. I’m referring to goals 100 years out, not just towards exit strategy. What is the legacy and continuation of value you want to leave all of us with.
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Yvonne Chou
Snowflake Summit has brought a lot of clarity to me. Conversations with accomplished and seasoned professionals in the data space like Ben Castleton have really solidified our confidence in our mission and the problems we're trying to solve at Kater.ai (YC W24). Having Ben on our side feels like a superpower.
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Travis Hardegree
Introducing Databricks Assistant Autocomplete. Assistant Autocomplete real-time code suggestions as you type in SQL and Python. It uses context from code cells, Unity Catalog metadata, DataFrame data, and more to relevant suggestions as you type. This is a super cool time saver for databricks practitioners leveraging our AI Assistant!!!
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Noah Arling
Today, the Snowflake AI Research Team is thrilled to introduce Snowflake Arctic, a top-tier enterprise-focused LLM that pushes the frontiers of cost-effective training and openness. Arctic is efficiently intelligent and truly open. "Snowflake and AWS are aligned in the belief that generative AI will transform virtually every customer experience we know," said David Brown, Vice President Compute and Networking, AWS. "With AWS, Snowflake was able to customize its infrastructure to accelerate time-to-market for training Snowflake Arctic. Using Amazon EC2 P5 instances with Snowflake’s efficient training system and model architecture co-design, Snowflake was able to quickly develop and deliver a new, enterprise-grade model to customers. And with plans to make Snowflake Arctic available on AWS, customers will have greater choice to leverage powerful AI technology to accelerate their transformation." https://lnkd.in/eUnAAAKg
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Jason Davis
It's been a few days now since Snowflake's 2024 Summit last week - and I sat down this week (along with Lauren Saalmuller) to put together a few thoughts on year over year trends & market changes we're seeing. #1 - Marketing activation from Snowflake & the CDW has good awareness - and it's not just about copying data. #2 - Adtech & Martech are in fact converging - but slower that I would have expected. #3 - AI is hotter than ever. Opportunities are huge, but unfortunately there's still a lot more discussing than actual doing right now. See link below for my full thoughts. Simon Data https://lnkd.in/erJjgFPN
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Eleanor Treharne-Jones
Weren't able to attend the recent Snowflake and Databricks conferences? Tired of just reading about them on LI and want some more detail? This session is for you... Catch the replay of our 2024 Conference Season Recap ⬇️ Kyle, Zach and Eric from Bigeye cover: - The biggest conference season announcements - Top trends data leaders should be watching - How to evaluate what new tech you should invest in and more!
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Jonathan Shuster
What do dbt and the Dawgs have in common? Going back to back, of course! ❄ 🔸 'dbt for Snowflake' has a nice ring to it 🔸 ❄ , so does back-to-back Snowflake Data Integration Partner of the Year for dbt Labs🏆. Starting today, you will officially be able to purchase dbt on the Snowflake Marketplace 🚨. With purchase, you get access to enterprise dbt Cloud and the dbt for Snowflake native app, which extends what you have built on dbt Cloud to the Snowflake UI. With one Snowflake login, you can access three experiences: -dbt Explorer -Ask dbt (a dbt-assisted chatbot that integrates with Snowflake Cortex and the dbt Semantic Layer) -orchestration observability https://lnkd.in/ebnHJ8pZ
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