Content from Thalia Barrera

About the Author

Thalia Barrera is a data engineer and technical writer at Airbyte. She has over a decade of experience as an engineer in the IT industry. She enjoys crafting technical and training materials for fellow engineers. Drawing on her computer science expertise and client-oriented nature, she loves turning complex topics into easy-to-understand content.

Content from Thalia Barrera

About the Author

Blog

12 Things You Need to Know to Become a Better Data Engineer in 2023

Redshift Turns 10: The Evolution of Amazon’s Cloud Data Warehouse

The Evolution of The Data Engineer: A Look at The Past, Present & Future

What is Reverse ETL?: Concepts, Use Cases & Integration

Understanding Change Data Capture (CDC): Definition, Methods and Benefits

What is Data Replication: Examples, Techniques & Challenges

Data Engineering Resources

Data Quality Guide: Tools and Techniques for Data Engineers

Agentic Data Resources

Data Quality Guide: Tools and Techniques for Data Engineers

How to Fix Fragmented Agent Integrations

What Are Embedding Models and How Are They Used?

Knowledge Graphs Explained

What Is Graph RAG, and How Does It Work?

What Is Real-Time RAG?

What is AI Agent Context Management?

What is Persistent Memory for Agents?

10 Examples of AI Assistants for Finance Teams

What is an Agent Knowledge Base?

What Is Dynamic Context Retrieval?

How Does an Event-Driven Agent Architecture Work?

How to Build Embedded Integrations in SaaS

How to Handle Unstructured Data

What Is a Unified API and How Is It Used?

What Is Unstructured Data and How Is It Used?

Native Integrations vs. Unified APIs

How to Build API Integrations That Don't Break

How to Build SaaS Integrations That Scale

Building a HubSpot Agent Connector Using the HubSpot API

What Is Agent-Ready Data?

How to Connect AI Agents to Databases

What Is Agent Data Freshness?

Custom API Integration vs Platform: A Guide to Differences and Tradeoffs

How to Control AI Agent Scaling Infrastructure Costs

What Is Agent Engine? A Guide for Engineering Teams

What Is Long-Term Agent Memory?

What Is Agent Tool Calling?

What Are Parallel Tool Calls in LLMs?

What is Context Engineering for Agents?

What Do AI Agents in Production Need?

Best AI Agent Frameworks for 2026

What is RAG Architecture?

What Is an OpenAI API Key and How Does It Work?

ETL for AI: How Does It Work in an Agentic Data Infrastructure?

What Are MCP Connectors?

What Infrastructure Supports Real-Time Data Access for Production AI Agents?

LLM Agent Fundamentals and Implementation

What Are Autonomous Agents and How Do They Work?

What Is an MCP Client and How Does It Work?

What Is a Graph Database and How Is It Used?

What Is Vector Search?

LangChain Agents Explained

Webhook vs API: When to Use Each

What Platforms Provide Pre-Built Connectors for AI Agents?

Which Platforms Support MCP for AI Agent Integrations?

What Platforms Help Manage Data Access for Multiple AI Agents?

What Tools Let AI Agents Connect to Databases and APIs?

What Tools Help AI Agents Process Streaming Data in Real Time?

What Tools Help Consolidate and Manage API Integrations for AI Agents?

A2A vs MCP: A Comparison Guide to Communication Protocols

Zero Trust AI: How to Secure Your Data

A Guide to AI Enterprise Search & The Infrastructure It Requires

Real-Time Data for AI: Benefits & Implementation Guide

6 Reasons Why AI Projects Fail

Model Context Protocol (MCP) vs API: What Are the Differences?

What Is Semantic Enrichment?

What Are Multi-Agent Systems?

A Guide to Scaling Agentic AI

12 MCP Server Examples Every AI Engineer Should Know

AI Connectors: Use Cases and Benefits

What is Enterprise AI Governance & How to Implement It

5 AI Context Window Optimization Techniques

AI Agents vs RAG: What Is the Difference?

7 Legal AI Agent Examples: Tools and Real-World Use Cases

What Is KV Caching in LLMs?

What is AI Agent Observability?

MCP vs RAG: What Is the Difference?