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Using Kappa Architecture to Reduce Data Integration Costs

Striim

Showing how Kappa unifies batch and streaming pipelines The development of Kappa architecture has revolutionized data processing by allowing users to quickly and cost-effectively reduce data integration costs. Stream processors, storage layers, message brokers, and databases make up the basic components of this architecture.

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Why a Streaming-First Approach to Digital Modernization Matters

Precisely

How can an organization enable flexible digital modernization that brings together information from multiple data sources, while still maintaining trust in the integrity of that data? Today, cloud data platforms like Snowflake, Databricks, Amazon Redshift, and others have changed the game.

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What is ETL Pipeline? Process, Considerations, and Examples

ProjectPro

That's where the ETL (Extract, Transform, and Load) pipeline comes into the picture! Table of Contents What is ETL Pipeline? Source-Driven Extraction The source notifies the ETL system when data changes, triggering the ETL pipeline to extract the new data.

Process 52
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61 Data Observability Use Cases From Real Data Teams

Monte Carlo

Many times this is by freeing them from having to manually implement and maintain hundreds of data tests as was the case with Contentsquare and Gitlab. “We We had too many manual data checks by operations and data analysts,” said Otávio Bastos, former global data governance lead, Contentsquare. “It

Data 52
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61 Data Observability Use Cases That Aren’t Totally Made Up

Monte Carlo

Many times this is by freeing them from having to manually implement and maintain hundreds of data tests as was the case with Contentsquare and Gitlab. “We We had too many manual data checks by operations and data analysts,” said Otávio Bastos, former global data governance lead, Contentsquare. “It