About us
We are in the era of big data, where all kinds of data is being collected within the organizations. Understanding data is step number one, before we can even decide what to do with it. Data visualization is the best way to understand your data. All folks interested in data know that Data Visualization is as much of an art, as it is science! In addition, maturity in your visualizations and analyses is very much guided by the level of experience one has.
We, in Charlotte, need a neutral forum where we can learn from each other about the best practices associated with Data Visualization, share case-studies, understand how to and what results to drive, irrespective of the tools. And talking about tools, there are over 15 data visualization tools, and we should have a way to learn about what exists and what is coming in the world of data science.
Since Data Science, Machine Learning and Data Visualization are all critical to achieving the end-goal, it makes sense for us to broaden the group and make it even more exciting.
This Meet-Up group is targeted at both, experienced and aspirational data users and data scientists. We plan to meet once a month and have an opportunity to meet, greet, talk and perhaps have a sponsored beer!
Upcoming events
8
- Network event
Prototype to Production: What It Takes to Build Enterprise-Grade AI Applications
·OnlineOnline31 attendees from 11 groupsThe AI landscape is cluttered with impressive demos and promising proofs of concept—but turning those early wins into real, scalable impact is a different challenge entirely. This webinar dives deep into what it actually takes to evolve from experimentation to production in enterprise AI.
Join a panel of experts who have built and deployed AI at scale to explore the operational, architectural, and organizational requirements that separate enterprise-ready AI from pilot projects that never leave the lab. We'll cover how to navigate infrastructure decisions, design for governance and observability, and build systems that are robust, compliant, and built to last.
Key Takeaways:
1️⃣ From Idea to Impact: What separates successful enterprise AI deployments from stalled prototypes.
2️⃣ Architecting for Scale: Best practices for building AI pipelines that are modular, maintainable, and audit-ready.
3️⃣ Trust and Governance: How to bake in model observability, compliance, and responsible AI from day one.
4️⃣Collaboration Across Functions: Why cross-team alignment (ML, IT, data, product) is essential—and how to make it work in practice.
5️⃣ Lessons from the Field: Real-world insights from leaders who’ve scaled AI across industries.
Panelists to be announced soon.
Register here6 attendees from this group - Network event
AI Demo Day Q1
·OnlineOnline13 attendees from 11 groupsJoin us for AI Demo Day—an exclusive virtual event showcasing the most innovative AI solutions through concise 10-minute demos.
At DSC, we value your time and have designed this event to provide impactful demos without any unnecessary fluff. Quickly identify solutions that meet your business needs and connect directly with the founders and top leaders of pioneering AI companies.
What You'll Learn:
1️⃣ Innovative Solutions: Discover the latest advancements in AI through targeted, high-impact demos.
2️⃣ Direct Engagement: Gain valuable insights and ask questions directly to the founders and top leadership of cutting-edge AI companies.
3️⃣ Enhanced Capabilities: Explore how these technologies can enhance your organization’s capabilities and drive innovation.
Don't miss this opportunity to experience the best of AI in a focused, efficient format tailored for decision-makers like you. We understand that everyone loves discovering new solutions, but nobody likes the hard sell.
Mark your calendars and get ready to dive into the future of AI!
Register here1 attendee from this group - Network event
How AI Agents and Bots Are Breaking Your Web Analytics—and What To Do About It
·OnlineOnline2 attendees from 11 groupsAgentic browsers and AI bots are quietly reshaping how traffic flows across the web—and breaking your analytics in the process. According to HUMAN Security, agentic browsing traffic surged 6,900% between 2024 and 2025, fueled by tools like Perplexity Comet and ChatGPT Atlas. The result? A growing share of pageviews, clicks, and conversions that aren’t coming from people—and aren’t being flagged by traditional analytics tools.
In this session, we’ll unpack how AI agents distort metrics like bounce rate, CTR, and conversion funnels, and why legacy bot detection methods fall short. We’ll also show how Snowplow is tackling this challenge with a dual-layered approach: combining CDN-level server-side signals with client-side fingerprinting and behavioral pattern analysis.
You’ll walk away with a framework to distinguish human from synthetic sessions, normalize inconsistent AI attribution, and uncover where agentic traffic is helping—or hurting—your site’s performance. It's about regaining visibility, restoring trust in your data, and adapting your web strategy to an AI-browsing future.
What You'll Learn:
1️⃣ Understand agentic traffic distortion: Learn how AI browsers and bots impact core engagement metrics—and why you likely aren’t seeing it.
2️⃣ Detect invisible AI traffic: See how behavioral analysis and hybrid event collection expose agent takeovers without false positives.
3️⃣ Normalize attribution across sessions: Identify where AI platforms are routing users and distinguish between synthetic influence and genuine engagement.
4️⃣ Plan for an agent-first future: Learn how to adapt optimization and content strategies for hybrid audiences: humans, bots, and everything in between.
Register here - Network event
Five Signs Your Data Is (Actually) Ready for AI
·OnlineOnline2 attendees from 11 groupsMany enterprises believe they’re ready for AI once models are selected, platforms are deployed, and pilots are underway. But in practice, AI initiatives often stall before reaching production—or they underperform once they do. The root cause? The data isn’t actually ready.
In this thought-leadership session, Naveen Punjabi from Google Cloud and Jake Bengtson from Striim unpack five critical signs that your data foundation can actually support AI at scale. Drawing from real-world customer patterns, we’ll explore why centralized data isn’t enough, how invisible data errors derail AI outcomes, and why stale data threatens use cases like RAG and AI agents.
What we'll cover:
- What Google Cloud is seeing across enterprise AI adoption—and where data readiness tends to break down
- Five practical indicators your data is ready for trustworthy, production-grade AI
- Why validation and accuracy matter before any models get involved
- How real-time pipelines give AI access to operational truth
- How Google Cloud and Striim help enterprises move from AI experimentation to enterprise impact
This session is built for data, analytics, and AI leaders ready to move beyond AI experimentation—and build foundations that truly support scale.
What You'll Learn:
1️⃣ Spot the Warning Signs: Know when your data might silently sabotage your AI initiatives.
2️⃣ Go Beyond Centralization: Why a data lake isn’t the same as a data strategy.
3️⃣ Enable Live AI: How real-time pipelines can unlock true operational intelligence.
4️⃣ Validate Early, Scale Confidently: Why data quality must be addressed before model deployment.
5️⃣Learn from the Field: What Google Cloud and Striim have seen across real enterprise AI journeys.
Register here
Past events
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