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5 Reasons Why ETL Professionals Should Learn Hadoop

ProjectPro

The conventional ETL software and server setup are plagued by problems related to scalability and cost overruns, which are ably addressed by Hadoop. Reason Two: Handle Big Data Efficiently The emergence of needs and tools of ETL proceeded the Big Data era.

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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’s world calls for a streaming-first approach.

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What is ETL Pipeline? Process, Considerations, and Examples

ProjectPro

ETL (Extract, Transform, and Load) Pipeline involves data extraction from multiple sources like transaction databases, APIs, or other business systems, transforming it, and loading it into a cloud-hosted database or a cloud data warehouse for deeper analytics and business intelligence.

Process 52
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61 Data Observability Use Cases From Real Data Teams

Monte Carlo

It’s hard to convince departments to launch experiments or executives to trust them if no one believes in the underlying data or the dashboards they look at every day. Oftentimes these ETL systems come under considerable pressure as all of your stakeholders want to look at every metric a million different ways with sub second latency.

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

Monte Carlo

It’s hard to convince departments to launch experiments or executives to trust them if no one believes in the underlying data or the dashboards they look at every day. Oftentimes these ETL systems come under considerable pressure as all of your stakeholders want to look at every metric a million different ways with sub second latency.