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CASO DE USO | ANÁLISIS SHIFT-LEFT

Dedica menos tiempo al mantenimiento y recupera tus recursos de ingeniería

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¿Quieres eliminar proliferaciones innecesarias de datos? ¿Lo tienes todo a punto para dejar de trabajar con pipelines de datos que quieren una reparación manual? Procesa y controla los datos en su origen —tan solo unos milisegundos después de su creación— con una plataforma de streaming de datos.

Desplazar el procesamiento y la gobernanza a la izquierda —que solemos conocer como el enfoque «Shift Left»— te permite reducir los problemas de calidad de los datos en hasta un 60 %, reducir los costes de computación en un 30 % y obtener la máxima productividad de tu equipo ingeniería y el ROI del almacén de datos. Explora más recursos para dar tus primeros pasos o descarga Shift Left: Unifying Operations and Analytics With Data Products.

Why Shift Processing & Governance Left?

In data integration, “shifting left” refers to an approach where data processing and governance are performed closer to the source of data generation. By cleaning and processing the data earlier in the data lifecycle, you can build data products that give all downstream consumers—including cloud data warehouses, data lakes, and data lakehouses—a single source of well-defined and well-formatted data.

Deliver Reusable, Trustworthy Data Products

Process data and govern data once at the source, and reuse in multiple contexts. Use Apache Flink® to shape data on the fly.

Power Analytics With the Freshest, High-Quality Data

Maintain high-fidelity data that’s continuously flowing into your lakehouse, and evolving seamlessly with Tableflow.

Maximize the ROI of Data Warehouses and Data Lakes

Reduce data quality issues by 40-60% and free up your data engineering team to work on more strategic projects.

Análisis Shift Left: conoce las últimas tendencias

A diagram showing the foundational data flow of Shift Left architecture
Shift Left: un desplazamiento a la izquierda para crear productos de datos reutilizables

Conoce todos los detalles sobre los análisis «Shift Left» y descubre cómo un enfoque tan sencillo —aunque, al mismo tiempo, tan potente— para la integración de datos está ayudando a acelerar la innovación de muchísimas empresas.

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Prevent Bad Data in Streams

Show Me How: Shift Left Processing From Data Warehouses

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How to Optimize Data Ingestion Into Lakehouses & Warehouses

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Tableflow Is GA: Unifying Apache Kafka® Topics & Apache Iceberg™️ Tables

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Conquer Your Data Mess With Universal Data Products

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Acelera tu transición hacia el streaming de datos con nuestros socios

Colaboramos con nuestro extenso ecosistema de socios para facilitar a los clientes la creación, el acceso, el descubrimiento y el intercambio de productos de datos de alta calidad desde cualquier punto de su organización. Descubre cómo algunas de las empresas más innovadoras —como Notion, Citizens Bank y DISH Wireless— aprovechan la plataforma de streaming de datos y nuestras integraciones nativas con soluciones en la nube, software y servicios para aplicar un enfoque «shift left» al tratamiento y la gestión de datos que les permita maximizar su valor.

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Notion Enriches Data Instantly to Power Generative AI Features

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Citizens Bank Improves Processing Speeds by 50% for CX & More

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DISH Wireless Creates Reusable Data Products for Industry 4.0

Maximize Your Data Warehouses in 4 Steps

Maximize your data warehouses and data lakehouses by feeding them fresh trustworthy data. It all starts when you have a complete data streaming platform that lets you stream, connect, govern, and process your data (and materialize it in open table formats) no matter where it lives.

Step 1. Connect Your Operational Systems to Stream Data Instantly

  • Out-of-the-box connectors: Use 120+ pre-built connectors—with 80+ fully managed across the stack like our Oracle CDC Connector—for instant integration with existing data systems.
  • Custom connectors: Bring your own connector and run it confidently and cost-effectively on our fully managed cloud service.
  • Built-in cloud integrations: Enjoy instant access to streaming data directly within AWS, Azure and Google Cloud, so you never have to leave the tool of your choice.

Step 2. Build Data Products Once and Reuse Them Anywhere

Enterprise-grade stream governance for Apache Kafka

Step 3. Enable Self-Service Access to Trustworthy Data Products

  • Ensure data quality at the source: Build trusted, high quality data products with explicit data contracts and schema management with Stream Governance.
  • Discover reusable data products: Help data consumers securely self-serve to search and repurpose data products via Data Portal.
  • Quickly understand complex data relationships: Gain more insights with an interactive, visual overview of data flows and processing with Stream Lineage.

Step 4: Unify Streaming and Analytics With Ease

  • Seamlessly stream data into data lakes: Represent Kafka topics and associated schemas as Apache Iceberg™ and Delta Lake tables in a few clicks with Tableflow.
  • Unlock faster data value for analytics and AI: Skip the ETL and tap into fresh and trustworthy operational data to drive higher-quality data insights.
  • Better together with our partner ecosystem: Leverage strong partnerships and tight integrations with Databricks and Snowflake to meet all your AI and analytics use cases.
Ready to Shift Processing and Governance Upstream?

Learn how Confluent can help your organization shift left and maximize the value of your data warehouse and data lake workloads. Connect with us today to learn how to adopt shift-left architectures and accelerate your analytics and AI use cases.