Vincent Chung

❄DATA CLOUD USER GROUP❄ As luck would have it, our next Snowflake Dallas User Group topic (which was selected several weeks back) is quite timely in light of recent events. 📣 Join us next Tuesday (May 28) to hear Sanjay Kattimani talk about business continuity and disaster recovery. Sanjay will give us a detailed exploration of Snowflake's disaster recovery capabilities, where he will delve into the advanced mechanisms designed to protect your data from unexpected disruptions. Our session will kick off with an in-depth look at Snowflake's features that enhance data resilience and support seamless business continuity. We'll cover key aspects of disaster recovery and demonstrate how Snowflake addresses potential data failure scenarios. 🌟 The demonstration will include: ➡ Replication Processes: Understand how data is replicated across accounts to ensure availability. ➡ Sample Account Failover: See how Snowflake handles a failover process in real-time. ➡ Sample connected application and its behaviors during DR events. Sanjay will also discuss strategies for automating the detection of disaster recovery events, as well as the steps involved in the failover and failback processes. ❓ The session will conclude with an interactive Q&A segment, allowing you to engage directly with Snowflake experts and gain insights into best practices and operational efficiencies for disaster recovery. 🚀 Come be a part of an amazing community -- Dallas is one of the local Texas user groups that is growing fast (there are also groups in Austin and Houston!). Everyone is welcome at our in-person Snowflake events, whether you're new to Snowflake or a seasoned expert. 😎 See you soon in Carrollton at the Dallas Makerspace! #datacloud #datasuperhero #snowflakesquad #disasterrecovery

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Ad Age's Jack Neff digs into a challenge that's been plaguing our industry for decades. Despite the best efforts across all leaders in the Data Industry some level of error is inevitable. Even a Brand's 1st party data or "Golden Records" are often loaded with error. We (Truthset) have a solution to solve this problem while supporting the entire ecosystem through independent, transparent validation of accuracy. I believe all boats rise with greater accuracy in data. For the first time, Truthset's system will afford you the opportunity measure the accuracy of all the data you rely so heavily on for important business decisions and activation.

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** Any Databricks based Data Engineering Guru's looking for a new opportunity? ** At Databricks Conference? :-) I am looking for a Data Engineer with deep experience (NOT KNOWLEDGE only) but real world practical experience. Can be based in LA/NYC (2-3 days per week) or possibly 100% remote. I'd love to hear (DM me) exactly, what, where, when and how you worked with Databricks. This is a good start... I am looking for people with practical experience and not people willing to learn. We need the person to hit the ground running. Therefore priorty will be given to suitable applicants. Feel free to tag anyone. *** PLEASE NOTE *** 1. Do not expect a reply to your message - why ? I anticipate there will be an abundance of messages/emails etc and, realistically, 90%+ will not be a fit (based on experience) however I will review EVERY messsage but only reply to those I can help at this moment. 2. Its not personal, however this is conditional on your databricks experience, this is nothing to do with you as a person. #databricks #aws #dataengineering #dataengineerjobs

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Have you tried Snowflake's Artic? Artic is the latest open sourced LLM launched by Snowflake. It's amazing to observe the innovation driving training and operating efficiency for LLMs. Some Specs about Artic: - Dense-MoE Hybrid transformer architecture - 480B parameters spread across 128 fine-grained experts - 17B Active Parameters - Apache 2.0 licensed The main use cases of Arctic are SQL, coding, and instruction following for enterprise applications. Generating SQL code presents an important challenge, demanding a deep understanding of both natural language and programming syntax. It involves crafting precise outputs that faithfully reflect the user's intentions. Artic is available on Hugging Face, Together AI, Microsoft Azure, NVIDIA API Catalog and Replicate. It's also coming soon on Amazon Web Services (AWS), Lamini and Perplexity.

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I have been utilizing and maximizing Tableau containers in building my dashboards at work but I have learned and appreciated it more during today's Next Level Tableau session with Andy Kriebel. Thanks, Andy and NLT-mates for the productive learning session! 🤗🙏🏼 #NLT #Tableau #containers

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Had a great chat this morning and the thoughts around analytics intelligence came up. Wanted to bring this article back around if you are looking to evaluate your organization. https://lnkd.in/gRv9uqyW Simple scoring model to determine where you are in that journey. #data #analytics #business #rockstars

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Stakeholder: "We need this for the board deck this afternoon." Analyst: "I'm on it" Analyst thinks: Why did you wait until last minute to tell me about this? Analyst drops everything to get the data needed for the request. Next day.... Analyst: How did the board meeting go? Stakeholder: We ran out of time and never got to it. meanwhile... 3 other expectations were missed due to the urgent need. Sound familiar? Try these tactics: 1. Get the board meeting CALENDER from the CEO's EA 2. SCHEDULE a meeting with the stakeholder the week BEFORE the board meeting to go through metrics needed for the meeting. 3. LEARN what is IMPORTANT to the success of the business, not a person and build around that. 4. Be up front with the stakeholder about what expectations will be missed if you have to do urgent requests. 5. Track urgent requests so you can report these metrics to the business and its impact on productivity. Nothing is perfect, but these will help. #data #analytics #rockstar

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Data & Analytics skills rank third in the most requested types of skills, accounting for 11.8% of job postings. This underscores the growing importance of data-driven decision making across industries. How is your organization leveraging data analytics to gain a competitive edge? What challenges are you facing in building a data-centric culture? Read the full report here: https://lnkd.in/ebsD2ikj Mitchell Martin Inc. #Data #Analytics #MitchellMartin

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This was SO fun! I loved brushing elbows with other practitioners, learning about awesome generative use cases, and seeing how Databricks is making it easy and governable all on one platform! #data #databricks #genAI #dataintelligence

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For all my non-industry friends who were concerned about the Ticketmaster hack, some info and important lessons. For some background Ticketmaster wasn't hacked themselves. Their data was obtained via a data warehouse provider called Snowflake. The official stance as of multiple news outlets was it happened via "compromised user credentials" (like your logins). Impacted parties so far are believed to be Santander Bank and Live Nation / Ticketmaster, though others are expected. I'll drop a lot of resources below I've found interesting on this incident so far - and for my industry friends please point me towards better ones! At the end of the day the big thing that stood out here was that incident was accomplished through the tools these companies use. This is why it is SO SO SO important to: 1) Make sure you're setting things up for secure access using things like MFA. I know its annoying but do it! 2) You properly vet vendors and ensure their protocols are up to par - and if you have no clue what this means there is a whole industry out there of Managed Security Service Providers (#MSSP) out there ready to help you and protect your business environment. Seriously, I have a handful I will happily introduce you to if needed. Stay safe and stay curious folks, because this wasn't the first issue and it won't be the last. For my IT Services and MSSP friends - are there any other absolute must measures you would add? #MSP #ITServices #Cybersecurity

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If you're looking for a new dataset to use in data projects / demos, check out the Iowa Liquor Sales data. It has a few things missing from most public datasets: * It's granular * It's pretty big (29m rows) * It's over a long time period (starts in 2012) * Has a good mix of numeric, categorical, and geographic data (though confined to Iowa) https://lnkd.in/eJNXREwn

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I've written before that titles are meaningless in data and all that matters is your capabilities. Here's a deeper explanation... I've been a VP with zero reports. I've been a Director with 100 data people reporting to me while owning the P&L of a nine-figure data business. "Lower" title, but way more actual responsibility. There are people who get a senior data title after 12 months of work experience. I know a "Senior Manager" who ran data strategy at a >$50 billion company, after previously leading data strategy at a >$100 billion company. And countless other examples... This is why in data, anyone competent will calibrate your seniority based on your actual capabilities, achievements and impact - not based on your title.

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A letter from our Founder & CEO Tristan Handy 🤔 dbt Labs. Our goal in publishing this paper is to create a consistent, shared framework for a mature analytics workflow: the Analytics Development Lifecycle (ADLC). Link to the whitepaper here: https://lnkd.in/grEP9pNM

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I always thought Snowflake was just another data warehousing solution (what could be so different?), but it surprised me with some of its unique approaches to making ETL processes easier while maintaining efficiency and scale. It comes in handy for a current analytics project I have with one of the regional companies. I highly recommend this course!

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Tableau vs. dbt: It doesn't have to be a face-off. Just ask data leader Lindsay Murphy: Oftentimes, analytics engineers using dbt become a bottleneck for data analysts, slowing down their ability to freely experiment in Tableau. At the same time, analysts become cowboys of the ‘Data Wild Wild West’—sacrificing governance and data quality to uncover new insights and opportunities for the business. We’ve asked Lindsay to propose a framework that balances freedom of analysis with governance of business logic. And more importantly, one that helps analysts and engineers work better together ♡ → Make Tableau work with dbt: https://lnkd.in/dnDSVGiD

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The technology behind Databricks' #UnityCatalog supports a variety of business outcomes: faster innovation, cost reduction, compliance support and more.  Dive into some of the capabilities that make this possible, such as our data lineage, comprehensive monitoring + reporting, Feature Store and more.

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Time will show... Databricks acquisitions of MosaicML is like Meta's 2012 purchase of Instagram. -->Customizing LLMs on your data is like Instagram's focus on the data (photos/videos) that mattered in your timeline Databricks acquisitions of Tabular is like Meta's 2014 purchase of WhatsApp. -->Abstracting data formats is similar to unifying messaging across platforms.

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