Audience Hub: Marketer-friendly features for audience activation
Empower every marketer to build, analyze, and activate precise audiences with a no-code, warehouse-native segmentation suite.
Unifying Snowflake & Apache Iceberg in Logi Symphony via Simba's ODBC Driver
How do you connect Snowflake and Apache Iceberg to embedded analytics without adding complexity? In this video, we demonstrate:→ Setting up the Simba Snowflake ODBC driver via system DSN→ Why pushdown queries matter for performance→ Building governed, reusable metrics in Logi Symphony→ Delivering fast, interactive dashboards on live retail data The result: unified sales and inventory analytics without the ETL pipelines, Python scripts, and custom services that create support headaches.
Focal Systems: Boosting Store Performance with an AI Retail Operating System and Real-Time Data
Every second a product sits out-of-stock on a shelf, revenue quietly drains away. Customers walk out empty-handed, and businesses lose customers as well as valuable insights into what’s actually happening on the floor. At Focal Systems, we have built Shelf AI, a system that continuously “sees” store shelves, detects stockouts, and guides teams to replenish in time—so products are on the shelf when customers need them.
Data and Analytics Trends for 2026
Another year has flown by at breakneck speed. In the data and analytics space, the past year has seen an AI gold rush where BI and analytics solutions raced to offer AI-powered insights to best meet end users’ rising expectations. But despite AI being named the most important trend of the next five years in an insightsoftware survey, it isn’t an exact science as organizations contend with AI projects that fail to launch and the risk of AI hallucinations.
The Multi-Entity CFO's Financial Intelligence Guide
Your finance team wastes 14 days every month on manual consolidation. Your close stretches to 15-25 days. And you're one key person departing from chaos. The brutal math: Your "free" Excel process actually costs $850K+ annually in wasted time, errors, and missed opportunities. Meanwhile, leading multi-entity CFOs just cut their close time by 80% and freed their teams for strategic work instead of reconciliation hell.
Building AI-ready data pipelines with Snowflake and Fivetran
Enable teams to move from source systems to AI-driven insights without custom ingestion code or infrastructure management.
We Are Databox Playmakers
Culture is never something you fully design upfront. You can define values, write principles, and document behaviors, but real culture is shaped over time by people, decisions, and moments when things are not easy. At Databox, one word has followed us for years and somehow captured all of that better than anything else: playmakers. In our early days, one of our marketing leaders, John Bonini, used this phrase to describe who we are. At the time, we did not fully realize how accurate it was.
Stop Checking Clients One-by-One: Multi-Account Analysis with AI
Imagine managing multiple clients and instantly answering "Who has the lowest cost per conversion?" without opening a single spreadsheet. We're going to show you how to use Databox MCP to query multiple client accounts simultaneously and run an instant performance benchmark to compare ad spend and conversion rates side-by-side. About this series: This video is part of our "Chat with Your Data" series, where we explore the Databox MCP.
Ep 59 | The Secret to Creating the Cloud-Like Experience Anywhere with Adam Skotnicky
Data complexity is the enemy of innovation. Adam Skotnicky, VP of Engineering at Cloudera and founder of Taikun (acquired by Cloudera), joins host Paul Muller to explain how engineering teams can reclaim simplicity without sacrificing flexibility or control. Together they unpack why most teams are overwhelmed by tooling and operational overhead, how platform engineering can abstract complexity away from users, and what it really means to deliver “cloud-like” agility across hybrid environments.
How to Cut BI Ticket Backlogs with AI-ETL for Self-Serve Analysts
Your BI team didn't sign up to spend 69% of their time on repetitive data preparation tasks. Yet this is the reality for most data teams drowning in support ticket backlogs while strategic initiatives languish. Every hour spent manually updating schemas, troubleshooting failed data loads, or running ad-hoc queries is an hour not spent on the analytics that actually drive business decisions.