Zenlytic

How to outcompete much larger SaaS competitors? That's the question I explored in my interview with ex-VC, serial entrepreneur, and visionary leader in data analytics & AI: Ryan Janssen, CEO of Zenlytic Here are my 7 highlights: 1 - Solve the problem for the novice instead of just the specialists. 2 - Think about technology from the ground up and how it adds value at the core level instead of manipulating legacy from the top down. 3 - Balance conviction & agility - so make your bets stick to it, but don't get hung up on how you think it should be solved 4 - Stay lean. It's easier to build a high-performing small team than a high-performing big team. 5 - See every customer as a long-term partnership. Learn where you have a good fit and where there's not a good fit. 6 - Create the circumstances so you can continue focusing on the next three years rather than the next three months. 7 - Don't give up - startups don't die of starvation, they die of indigestion. Let's make this interactive: What specific question do you have in relation to outcompeting larger competitors? P.S. The link to the full interview with Ryan is in the 1st comment.

I had a fantastic chat with Paul Blankley from Zenlytic at the #SnowflakeSummit. We talked about how Zenlytic is focused on being a true ‘self-service’ BI platform. Check out our full conversation below. Discover more interviews like this in the newly launched 'DATAcated Library' at https://lnkd.in/eVsw3b2V Make sure you follow Zenlytic on all social media platforms!

50th Anniversary of SQL today.

Learn how Emily Hawkins is managing her career in data as she talks with Ryan, Paul and Drew from Zenlytic. Emily and our team talk through her experience on topics like: - Individual Contributor to Manager back to Individual Contributor - The types of problems does Emily enjoy working on - How to be flexible when modeling data - The future of analytics and data models

Ryan and Paul go into detail on the cognitive layer and how it unlocks accurate self-service analytics to business users.

Introducing the Cognitive Layer A cognitive layer combines all of the traditional semantic layer functionality that makes BI great - the same metrics definition syntax in YAML, the same run-time SQL generation. But then we've added more functionality designed around how people use data in the LLM era. For instance: Understands natural language instructions: Semantic layers always have some tribal knowledge that's emailed between the data analysts because it can't be encoded in a YAML. The Cognitive Layer combines those natural language instructions with strongly typed YAML definitions to ensure accuracy across all of the data. Fully centralized: Self-serve users get blocked when they need to pick an Explore, or a dataset. With the Cognitive layer, instead of an LLM asking you which Explore to use, you just get an answer. This is really hard because data warehouses themselves aren't centralized. We had to invent new ways of mapping multiple tables into a single logical concept that an end-user can understand. Built-in feedback for AI data agents: The key to a reliable AI Agent is providing an environment with strong feedback loops. The Cognitive Layer is constantly advising Zoë, our AI agent, which metrics can be used (and how they can be used together). So Zoë can iterate and find a solution correctly and consistently. The best part of the Cognitive Layer: it's a superset of a semantic layer, so it's fully backwards compatible. Typical YAML data modeling works the same way in a cognitive layer for delivering BI; the extra functionality is what delivers an amazing LLM experience. The cognitive layer is how Zenlytic provides reliable AI data analytics and the world's first self-serve business intelligence platform.

We are excited to meet our customers and new data people at the Data Cloud Summit by Snowflake.

The Leading 100 List takes over Times Square!  Join The Leading 100, 180+ speakers and 2,500+ innovation-minded brand and retail leaders at The Lead Summit on July 10th-11th in NYC: summit.the-lead.co A special thanks to Nasdaq for supporting The Leading 100 companies and a big congratulations to the innovative tech start-ups driving the future of brand-to-consumer!  Cristina De la Peña, CEO & Founder, Synapbox; James Theuerkauf, CEO, Co-Founder, Syrup Tech; Jeffrey Nicholson, CEO & Co-Founder, Tracer; Jake Disraeli, Co-Founder & CEO, Treet; Ella Lim, CEO, Trendsi; Alok Ahuja, CEO & Co-founder, Trexity; Greg Stevens, CEO, Turbyne; Kyle Bertin, Co-founder, CEO, Two Boxes; Sadee Gamhewa, Founder & CEO, Velou; Eddie Yang, CEO & Co-founder, Visual Feeder; Jehan Hamedi, CEO, Vizit; Evelyn Mora, CEO, VLGE; Ryan Janssen, CEO, Zenlytic; Maja Schaefer, CEO, Zowie #Leading100 #TheLead #startups #NASDAQ #retailtech #ecommerce #innovation 

At Zenlytic we are building the business intelligence platform to enable self-serve for everyone. There are some steps to enable self-serve and there might not be anyone better to articulate those steps than Murali Kallem, Head of Data Platform at Salesforce. The six steps to self-serve: 1. Solid data management and data quality 2. Provide proper tooling 3. Reusable frameworks for business teams 4. Center of enablement 5. Policies and standards for self-serve 6. Governance and audits Listen as Ryan and Drew from Zenlytic talk with Murali about discuss the history of data tooling, how to enable self-serve analytics, and things to consider when you own data at a company.

Had an absolute pleasure catching up with Paul Blankley, Founder & CTO of Zenlytic and learning more about the "world's first self-serve BI tool" as well as Zoë, their natural language chatbot. Can you guess... ...where the name Zoë came from? Until next time, let's keep putting the Lights On Data. #data #businessintelligence #genAI #analytics