Latest
Lineage

Trace Your Salesforce Data, From Field to Dashboard

A native connector, now in public beta, that maps Salesforce data lineage from objects and fields to the reports and dashboards your leaders rely on.

by

Melanie Y

Updated on

September 29, 2026

Other blog articles

Data Observability

What is Data trust? Maturity Framework

Discover steps to achieve reliable data across the value chain, focusing on trust beyond tools—essential for data products and GenAI.

By

Jatin

Updated on

August 8, 2026

Lineage

Data Lineage Explained: What is it? Meaning, Benefits & Components

Explore data lineage: Understand its meaning, significance, and how it enhances data transparency and accuracy for better decision-making in businesses.

By

Jatin

Updated on

August 8, 2026

What is Retrieval Augmented Generation (RAG)?

Dive into Retrieval Augmented Generation (RAG): Discover how RAG enhances AI's understanding and response accuracy by integrating external knowledge.

By

Jatin

Updated on

May 12, 2024

Catalog

Collaborate on Data Assets with the New Feed

The new Feed feature in the Data Catalog module makes it easier than ever for users to collaborate on data assets.

By

Melanie Yong

Updated on

June 17, 2024

Data Observability

Data Validation Techniques: 9 Checks and 4 Pipeline Gates

Nine data validation techniques, what each one catches and misses, the four pipeline points where checks belong, and what to do with a failed record.

By

Jatin

Updated on

September 9, 2026

Practical Data Observability Explained

Learn about the importance of data observability in the age of big data. Discover how practical solutions can ensure data integrity and trustworthiness.

By

Jatin

Updated on

October 28, 2024

Data Observability

Data Integrity: Meaning, the 5 Types, and How to Manage It

Data integrity means data stays complete, consistent and unchanged except by an authorized change. The 5 types, what breaks each one, and the controls that hold.

By

Jatin

Updated on

September 9, 2026

Catalog

Data Catalog: Streamlining Your Data Management and Organization

Elevate your data strategy with a robust data catalog. Enhance data discoverability, improve collaboration, and boost overall business growth.

By

Jatin

Updated on

August 9, 2026

Lineage

Column Level Data Lineage: How It Works and What It Costs

What column level data lineage is, how it is derived from SQL, where parsing fails, what it costs to run, and the impact analysis it makes possible.

By

Jatin

Updated on

August 22, 2026

Data Observability

Reduce Time to Value for Data Observability

Discover how our revamped Config module speeds up data observability implementation, helping organizations achieve quick and efficient results.

By

Melanie Yong

Updated on

August 8, 2026

Governance

Data Governance for the Modern Data Stack: 4 Breaking Points

Governance breaks in four places once data spans a warehouse, dbt, BI and AI agents: ownership, policy reach, lineage gaps and uncataloged tables.

By

Melanie Yong

Updated on

September 9, 2026

What is Data Observability? Data Engineers Guide

Much is said about Data Observability, yet it is imperative to precisely comprehend what Data Observability entails and how it can enhance the productivity of data engineers.

By

Jatin

Updated on

August 21, 2025

Data Mesh: A Paradigm Shift in Managing Data at Scale

Explore Data Mesh, its workings, benefits, and challenges in transforming data management at scale. Discover the future of data

By

Jatin

Updated on

October 2, 2024

Data Observability

Mastering Spark Jobs: Comprehensive Guide for Data Engineers

Navigate big data with ease. Our guide simplifies running and managing Apache Spark jobs, offering a comprehensive overview for data engineers.

By

Jatin

Updated on

October 2, 2024

Data Observability

New: Incident Resolution with Enhanced Insights

Explore upgraded incident resolution with detailed metrics, highlighted problematic points, user assignment, downstream impact, and affected row previews

By

Melanie Yong

Updated on

August 8, 2026

Data Governance for Quality: Policies Ensuring Reliable Data

Explore how our data governance policies ensure data quality, consistency, and reliability, empowering informed decision-making for businesses.

By

Jatin

Updated on

May 5, 2024

Improving Data Team Performance through Data Observability

This article highlights enhancing data teams' efficiency by implementing observability. This approach provides insights into data systems, enabling quicker issue detection and resolution. The result is a more agile and responsive team, leading to improved performance, reliability, and overall success in data management.

By

Jatin

Updated on

January 10, 2024

Data Mesh

Data Mesh Architecture: Guide for Data Engineers

Explore data mesh architecture for decentralized data management, domain ownership, and self-serve infrastructure. Empower data engineers to innovate.

By

Jatin

Updated on

October 2, 2024

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