Building Spark Lineage For Data Lakes
By Lior Gavish
Spark lineage has been a blindspot for the data engineering industry so we set off to engineer a solution. Here’s how we did it.
Data Observability: Reliability In The AI Era
By Lior Gavish
For GenAI, data observability must prioritize resolution, pipeline efficiency, and streaming/vector infrastructures.
The Moat for Enterprise AI is RAG + Fine Tuning – Here’s Why
By Lior Gavish
To succeed with LLMs at enterprise-scale, we need to treat our data pipelines with the diligence they deserve.
Data Contracts: Silver Bullet or False Panacea? 3 Open Questions
By Lior Gavish
Three open questions data contracts still need to answer for engineering teams.
The 31 Flavors of Data Lineage And Why Vanilla Doesn’t Cut It
By Lior Gavish
4 critical reasons why your data observability solution needs to have data lineage.
Data Lakes vs. Data Warehouses: The Truth Revealed
By Lior Gavish
Data warehouse? Data lake? Data lakehouse? All of the above? Here’s what you need to know to make the right choice for your stack
How to Build Your Data Reliability Stack
By Lior Gavish
Data reliability is a critical focus for modern data teams. Here’s how to get started.
Monte Carlo Launches Insights to Help Data Teams Understand What Data Matters Most to Your Business
By Lior Gavish
Monte Carlo Insights is the first solution on the market to offer customers operational analytics about their data environment.
The Weekly ETL: Will Data Engineering Ever Be Sexy like Data Science?
By Lior Gavish
Data engineers are the backbone of the data team – so why can’t they get the respect they deserve?
The Weekly ETL: How Do You Document Your Data Assets?
By Lior Gavish
Lior Gavish, Monte Carlo’s co-founder and CTO, answers a trending question on Reddit about some of the data industry’s hottest topics.