Blog de Dataslayer

Discover how Claude, ChatGPT, and Mistral each implement the Model Context Protocol (MCP) to enhance AI agent performance. Compare their key features, deployment options, and unique advantages for your AI project.

Discover how the Model Context Protocol (MCP) empowers Mistral's AI models to seamlessly interact with external systems, offering flexibility, security, and control for businesses looking to build efficient and customizable AI agents.

Explore how the Model Context Protocol (MCP) enhances ChatGPT's capabilities, enabling seamless integration, interoperability, and control for developers. Learn about its advantages over OpenAI's plugin system and its potential for the future of AI.

Explore how the Model Context Protocol (MCP) is transforming Claude into a powerful AI agent for marketing, SEO, and content creation. Learn how it enables real-time data access, personalization, and automated workflows.

LinkedIn amplía los anuncios Thought Leader para la promoción de eventos: descubre cómo planificar, crear y medir campañas dirigidas por personas que generen una asistencia B2B creíble en 2025.

El panorama del marketing digital se encuentra en pleno punto de inflexión estratégico y tecnológico. Un análisis de las tendencias recientes muestra que los silos tradicionales de medios de pago, búsqueda orgánica y plataformas sociales están colapsando bajo la presión acelerada de la inteligencia artificial (IA), un ecosistema de búsqueda cada vez más fragmentado y un imperativo constante de priorizar la privacidad. La IA ya no es una herramienta para mejoras incrementales; es una fuerza que impulsa una doble transformación tanto en la operativa de los anunciantes como en el comportamiento fundamental de los usuarios.

Google retirará la Content API for Shopping en agosto de 2026. Descubre qué novedades trae la nueva Google Merchant API, cómo afecta a la gestión de datos de e-commerce y qué pasos seguir para una migración sin problemas.

A/B testing is one of the most powerful tools in digital marketing to improve conversions and user experience. This guide explains how to form strong hypotheses, run reliable experiments, avoid common mistakes, and use data-driven insights to create a culture of continuous optimization.

Understand the differences between ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform). This guide for marketers compares both data pipelines, their benefits, limitations, and use cases. Learn how ETL supports structured reporting and compliance, while ELT enables big data, real-time insights, and flexible marketing analytics strategies.

Explore the key differences between Data Warehouses, Data Lakes, and Lakehouses, and learn how tools like Dataslayer help marketing teams integrate and report data from platforms like BigQuery, Redshift, S3, and Snowflake.

Discover how Google Tag Manager (GTM) can streamline your marketing and analytics efforts. Learn best practices for efficient tracking, event monitoring, and data management, and see how tools like Dataslayer can enhance your reporting.

Uncover hidden data patterns using techniques like EDA and machine learning to enhance your marketing and SEO performance.

Discover how MMM, AI, and first-party data is shaping marketing measurement in 2025, optimizing ROI and driving a competitive edge.

Compare Amazon Redshift, Snowflake, and Google BigQuery to discover which cloud data warehouse best supports marketing teams in managing, analyzing, and reporting data for optimized campaign performance and actionable insights.

MCP Servers with NLP are transforming marketing by enabling real-time data analysis, automated insights, and seamless campaign optimization, helping marketers make faster, data-driven decisions.