Data Warehouse vs Data Lake vs Data Lakehouse: Definitions, Similarities, and Differences
By Sara Gates
Struggling to decide whether to invest in a data warehouse vs. data lake vs. lakehouse? Here’s everything you need to know to make this decision.
5 Data Quality Tools—And Where You Should Start First
By Sara Gates
You need data quality tools. But which ones? And when? We define some of the top data quality tools, what they’re used for, when to consider one over the others, and where to start.
How Three Financial Services Data Leaders Drive AI-Readiness with Trusted Data
By Sara Gates
Learn how financial services data leaders from T. Rowe Price, Intercontinental Exchange/New York Stock Exchange, and Morningstar are navigating AI implementations in a highly regulated industry.
What is Data Completeness? Definition, Examples, and KPIs
By Sara Gates
What is data completeness? And how does this key dimension of data quality impact your data reliability strategy? We dive in with definitions, examples, and more.
Monte Carlo Recognized as the #1 Data Observability Platform by G2 for 8th Consecutive Quarter
By Sara Gates
We’re proud to celebrate 8 straight quarters as G2’s #1 Data Observability platform.
The Real Impact of Bad Data on Your AI Models
By Sara Gates
By now, most data leaders know that developing useful AI applications takes more than RAG pipelines and fine-tuned models — it takes accurate, reliable, AI-ready data that you can trust in real-time. To borrow a well-worn idiom, when you put garbage data into your AI model, you get garbage results out of it. Of course, … Continued
How Roche Built Trust in the Data Mesh with Data Observability
By Sara Gates
The team at Roche shares how they built a data mesh architecture and implemented data observability for reliability.
How WHOOP Built and Launched a Reliable GenAI Chatbot
By Sara Gates
Get a firsthand look into how the data team at WHOOP is leveraging LLMs to deliver reliable insights to stakeholders throughout the organization.
The (Ongoing) Evolution of Table Formats
By Sara Gates
Today’s table formats are so much more than collections of rows and columns. Learn how table formats have evolved and why data observability is as crucial as ever in the modern data stack.
Table-Level vs. Field-Level Data Lineage: What’s the Difference?
By Sara Gates
Learn why table-level data lineage is table stakes, and how field-level lineage can more effectively reduce time-to-resolution and speed up root cause analysis for data teams.