Apache Kafka®️ 비용 절감 방법 및 최적의 비용 설계 안내 웨비나 | 자세히 알아보려면 지금 등록하세요
사용 사례 | Shift Left 분석
정리 시간을 줄여서 엔지니어링에 투자하세요
|불필요한 데이터 확산과 수정을 수동으로 진행하는 데이터 파이프라인을 제거하고 싶으신가요? 데이터 스트리밍 플랫폼을 사용하여 데이터가 생성되는 즉시 소스에서 데이터를 처리하고 관리하세요.
처리와 거버넌스를 조기에 진행하면 데이터 품질 문제를 최대 60% 줄이고, 컴퓨팅 비용을 30% 절감하며, 엔지니어링 생산성과 데이터 웨어하우스 ROI를 극대화할 수 있습니다. 더 많은 자료를 보면서 시작하는 방법을 알아보거나 Shift Left: 데이터 제품을 통한 운영 및 분석 통합을 다운로드하세요.
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.
“Confluent helped us shift left on our data—giving teams full ownership of their data from source to output. Now it’s clean, validated, and production-ready upstream, reducing rework and accelerating delivery."
"Confluent Tableflow simplifies our data architecture, turning Kafka topics into trusted, analytics-ready tables in just a few clicks. We can now ensure a reliable data foundation for real-time customer insights and AI innovations."
Zazzle implemented Confluentʼs fully-managed Flink offering to transform their largest data pipeline. By shifting stream processing earlier in the pipeline before writing to Google BigQuery, Zazzle reduced storage and computation costs while delivering more relevant product recommendations, directly impacting revenue.
“We have 40,000+ ETL jobs today. It’s chaos…shifting data governance left would be transformational for our organization.”
“[Data cleaning] is a pricey way of pushing it down to the Delta Lake. De-duplication within Confluent is a cheaper way of doing it. We can only do it once.”
“I love the vision of [shift-left analytics]. This is how we would make datasets more discoverable. I knew that Confluent had an integration with Alation but it's awesome to hear that [with Data Portal] you have other ways of enabling those capabilities”
Shift-Left 분석 트렌드
Shift Left를 사용하여 재사용 가능한 데이터 제품을 만드는 방법
Shift Left 분석에 대한 심층 탐구를 보면서, 현대 사회의 기업 혁신에 기여하는 간단하지만 강력한 데이터 통합 접근 방식에 대해 알아보세요.
Show Me How: Shift Left Processing From Data Warehouses
Watch now
How to Optimize Data Ingestion Into Lakehouses & Warehouses
Get the guide
Tableflow Is GA: Unifying Apache Kafka® Topics & Apache Iceberg™️ Tables
Read blog
Conquer Your Data Mess With Universal Data Products
Download ebook파트너와 함께하는 데이터 스트리밍 여정 가속화
Confluent는 광범위한 파트너 에코시스템과 협력하여 고객의 조직 전체가 고품질 데이터 제품을 쉽게 구축하고 이에 접근하며 검색과 공유를 할 수 있게 합니다. Notion, Citizens Bank, DISH Wireless와 같은 혁신적인 조직들이 데이터 스트리밍 플랫폼과 네이티브 클라우드, 소프트웨어, 서비스 통합을 활용하여 데이터 처리 및 거버넌스를 전환하고 데이터의 가치를 극대화하는 방법을 알아보세요.
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 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.
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.