Practical ideas for data, web, and growth.

Conversational data agents are useful when they are grounded in a governed semantic model. Here is the sequencing we use to ship one that holds up in front of an executive audience.

Job listings have started talking about 'digital data analysts' without anyone defining the role. Here is what the role actually does day-to-day, where it fits in a mid-market org, and how to know whether you need to hire one.

Twelve DAX patterns we reach for on almost every engagement — from time intelligence to safe division to dynamic ranking — with the why behind each.

Bar charts and line charts are the right answer 80% of the time. Knowing what to reach for the other 20% is what separates an analyst from a designer of decisions.

The dashboards executives ignore aren’t bad reports — they’re bad answers to the wrong questions. Here’s the design framework we use on every engagement.

Conversational AI can answer business questions on demand. Does that mean dashboards are obsolete? After two years of running both side by side, the answer is more interesting than either side of the debate suggests.

Conversational BI is here, but every AI initiative we’ve seen succeed had one thing in common: a clean, governed semantic layer underneath.

Talk to your data tools are getting genuinely useful — for the small set of organizations that did the hard semantic-layer work first.

A redesign should not start because the site feels old. These are the operational signals that your website is limiting pipeline, trust, or speed to market.

Most companies try to grow revenue by hiring. The companies that grow margin alongside revenue use a three-layer framework to make the team they already have measurably faster.

Microsoft Fabric’s Direct Lake mode changed the modeling math in Power BI. Here’s the decision tree we use to pick storage mode per workload.

When three analysts pull the same data and get three different answers, you don't have a data problem. You have a decision problem about who owns the definition.

A BI roadmap only works if the first 90 days build trust. Here is how we sequence metrics, ownership, dashboards, and governance without boiling the ocean.

Headlines argue about whether AI replaces analysts. The more useful question is how much faster the team you already have can move with AI in the loop — and how to make the productivity gains stick.

When SEO, speed, and ownership matter, the calculus has shifted. Here’s the honest trade-off table for buyers comparing both stacks.

Companies between $50M and $500M almost always hit a moment where the data they have stops being able to support the decisions they need to make. Here is what causes it, what it looks like, and the staged path through it.

Multi-location SEO breaks when every location page looks the same. This playbook keeps local visibility, content quality, and lead tracking aligned.

Most BI maturity models are vendor-flavored fantasy. Here’s a five-stage model grounded in the engagements we’ve shipped — and the gate at each stage.

After a merger closes, leadership wants one number — the data team has three. Here is the 90-day playbook we use to ship a credible consolidated view before the integration project is anywhere close to done.

Before a leadership dashboard goes live, we review it for decision clarity, metric trust, performance, and meeting-readiness. Here is the checklist.

Most KPI lists are inherited from a deck nobody owns. Here’s the simple framework we use to write metrics that survive contact with a board meeting.

Good nurture emails do not chase every click. They teach, qualify, and create a timely reason to talk. Here is how we structure them.

The board wants risk, ROI, and time-to-value. Employees want to know whether their jobs change. Most AI strategy decks get the wrong message to the wrong audience and create both panic and skepticism at once.

Adoption is a design and product problem disguised as a data problem. Here are the five reasons reports go unread — and the fix for each.

Templated pages are how Zapier, Wise, and Notion built moats. They’re also how thousands of B2B sites built nothing. The line is narrower than it looks.