The role of data leaders is shifting and here’s how to stay ahead.
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Bruh (do you have a Gen-Alpha in your life who calls you that, too?)

 

It’s chaotic out there.

 

AI’s building pipelines. Excel’s still breaking your spirit. “Semantic layer” debates are raging. We keep hearing AI will take our jobs.

 

This week’s newsletter won’t fix everything — but it will help you lead smarter, hopefully feel more confident about using AI, and maybe even laugh at the madness.

 

 

Below, you'll find: 

  • This Month's Recommended Read 
  • Data Signals: Hot Topics
  • Emerging Tech Insights 
  • Busting Data Myths 
  • LOL Moment 

Let's get to it!

 

Tracey Doyle

Chief Marketing Officer, Analytics8

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📖 This Month's Recommended Read 

 

Building Better with AI: How Tech Leaders Are Using AI to Help Their Teams Scale 

There’s a lot of talk about AI tools — but what does it take to actually build with them? In this piece, our data expert, John Bemenderfer, shares how Analytics8 is helping clients cut through the hype and build AI solutions that deliver business value.

 

💡Here's his take: 

  • Don’t start with models — start with clean, governed data. If your inputs are a mess, your insights will be too.
  • Use new frameworks to speed up impact — not reinvent the wheel. Tools are maturing, and you don’t need full-scale dev to build something useful.
  • Stay grounded in data fundamentals. AI is evolving fast, but the real differentiator is how you apply it to real business problems.

 “Everyone talks about model performance, but we focus on the part that’s often overlooked—clean, consistent, and well-defined data. That’s what makes AI actually work.” – John Bemenderfer, Managing Consultant  

📡 Data Signals: Hot Topic 

 

Let's Rethink the "Semantic Layer"  

The term semantic layer has baggage — and our data expert, Christina Salmi, says it’s time we move on.

 

In her words, the dream isn’t to make the original semantic layer universal. It’s about something more useful today:

 

A “business context layer” that stores reusable, machine-readable business definitions — and shares them across tools, from BI to AI.

 

Why it matters:

  • Context isn’t optional anymore. Without shared business context, you’re repeating work, duplicating definitions, and risking bad AI outputs.
  • It’s not about one tool to rule them all. It’s about interoperability: capturing definitions once, then reusing them everywhere.
  • AI makes it more feasible. You don’t need the business to manually build a knowledge graph. AI can fill in gaps and route definitions to where they’re needed.

As Christina puts it: “We’re not asking for one semantic layer — we’re asking for one standard for sharing business context.”

 

Check out her full thoughts on the matter!

Emerging Tech Insights 

A few tech updates on our radar: 

 

1. Agent Bricks: AI for Real Data Work 

Databricks unveiled Agent Bricks at their Data+AI Summit a couple of weeks ago, and it isn’t just a flashy chatbot. From generating pipelines and fixing errors to writing documentation, Agent Bricks allows you to build high-quality, domain-specific agents by describing the task in the language of your business.

 

“Leveraging Agent Bricks, Analytics8 achieved a 40% increase in answer accuracy with 800% faster implementation times for our use cases, ranging from simple HR assistants to complex research assistants sitting on top of extremely technical, multimodal white papers and documentation.” – Patrick Vinton, Analytics8 CTO

We were one of five orgs that got early access and put it to the test. Here’s what we learned →

    2.  Sigma Joins the Gartner Magic Quadrant for BI

    Big milestone for Sigma: it officially made the Gartner Magic Quadrant for BI & Analytics Platforms.

     

    💡 Why it matters: Sigma’s inclusion signals growing recognition for its cloud-native, spreadsheet-style approach — and its focus on enabling governed self-service at scale. It’s also one of the few platforms in the MQ leaning into agentic AI, data apps, and write-back functionality.

     

    Sigma was ALSO named BI Partner of the Year by both Databricks and Snowflake at their respective conferences this month. 🔥

    Busting Data Myths 

     🛑 Myth: "AI will replace data leaders!" 

     

    AI won’t replace you (yet)— but it will expose the leaders stuck in the weeds.

     

    Why? Because AI can now generate code, build pipelines, and spin up dashboards faster than ever. That means the value of a data leader isn’t in building — it’s in driving outcomes.

     

    ✅ Reality Check: Leadership in the era of AI isn’t about knowing every tool — it’s about scaling your impact, aligning data with business strategy, and enabling teams to make better decisions. The next generation of great data leaders will be the ones who think bigger — not just build faster.

    LOL Moment 

     

    Still uses Excel...

     

    LOL Meme

    ... automates entire data pipelines with AI 

    Have any good data memes or jokes to share with the group? Send them our way – if you get featured, we’ll send you some swag ;)

     

    Have a great week!

    Tracey

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