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The Latest Thinking On AI In Analytics, Straight From Momenta Analytics Thought Leadership HQ
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10 articles
Trust doesn't only break through a data breach. Sometimes it breaks over something far smaller.
Two dashboards. One cohort. Two different counts.
Why Analytics Needs Its Netflix Moment
Netflix didn't win because it had more movies. It won because it labeled them.
Three Platforms One Prerequisite: What It Actually Takes to Fill a Semantic Layer
Snowflake, Databricks, and Microsoft all announced AI agent products that depend on governed business definitions in a semantic layer. We wrote up what it actually takes to populate and maintain the semantic layers they depend on.
Why AI Needs Infrastructure, Not Just Intelligence
Every major tech platform is racing to own your enterprise context—because that's where AI becomes most valuable. This macro-trend, known as Context Engineering, confirms that in the age of AI, contex
Your AI agent has a dictionary. It doesn't have a childhood.
SAM from Star Trek Academy is every 'Talk to Your Data' agent being promised to the enterprise. And the trauma is the decades of ugly, uncleaned, undocumented data warehouses we're forcing them to process without experience.
The Most Important Documentation Your Analysts Ever Wrote Wasn't in Confluence
It was in their WHERE clauses — the business rules buried inside every SQL query your team has ever run. They just didn't know they were writing it.
Inside the Neuron Pipeline: What Actually Happens to Your Query History in 4-6 Weeks
From raw query export to a working context layer: a real, five-stage walkthrough of what Neuron does with 100,000 queries in 4–6 weeks.
We Scored 46 KPIs About Your Analytics Practice. Here's What They Actually Measure.
One medication, nine conflicting cohort definitions, and nobody who'd ever seen them side by side. Here's what our 46-KPI Health Assessment actually measures.
AI Readiness: What It Actually Means for Your Data
AI readiness isn't about data volume or which model you've licensed. Here's what actually determines whether your data is ready for AI, and how to measure it.
The Last Unmapped Asset: Who Owns Your Company's Brain?
Your brain your real intellectual property, and right now it is unreadable, unowned, and about to be quietly enclosed inside someone else's product.
Context 101
4 articles
What Is Query History? Definition, and Why It's Your Most Underused Data Asset
Query history is the complete, timestamped record of how your team actually uses data. Here's what's inside it, and why almost nobody reads it until something breaks.
Context Layer vs. Semantic Layer: What's the Difference, and Who Fills Them?
Semantic layers define what a metric means. Context layers add the evidence to trust it. Here's the difference, and the open question of who fills both.
Semantic Layer: The Complete Guide
A complete guide to semantic layers — what they are, the tools that implement them (dbt, Cube, Snowflake, Databricks), and why most are only partially populated with real business logic.
What Is a Context Layer? Definition, Components, and Why Most of Them Start Empty
A context layer is the machine-readable record of how your business actually defines and calculates its metrics. Here's what it includes, and why most start empty.
Whitepapers
2 articles
Natural Language Analytics: Implementation Field Guide
A practical field guide for implementing Databricks Genie and Snowflake Cortex Analyst. What each platform actually requires, where they overlap, and what neither does for you.
Getting Started with Text-to-SQL You Can Actually Trust
Natural-language-to-SQL has the potential to reshape the landscape of data analytics.
Case Studies
11 articles
The Feedback Loop
Whether the work your team does builds on itself, or starts over each time.
Standardization
Whether a multi-step method, longer than a single query, is run the same way across your team.
Reuse / Build-On
How much of your team's work stands on work it already trusts.
Key-Person Risk
How much of your team's working output comes from a single analyst.
Definition Concentration
How much of your team's shared vocabulary lives in one person's SQL.
Evaporation
How much of your team's reasoning leaves nothing behind the moment the query finishes.
Hidden-Join Rate
How much of the way your tables connect lives only in the queries, never in the schema.
Business-Rule Density
The rules your numbers depend on, and how little of that logic is written down anywhere but SQL.
Analysis Rate
How much of your query volume is real analysis, and how much is orientation and upkeep.
Intelligence Volume
Whether your team is breaking new analytical ground, or re-running the same report.
Ten Vital Signs of a Query History
The most valuable thing your analytics team produces is the record of every analysis they have designed and run. It is sitting in your query history, and nothing in your stack is counting it.