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Real-Time Analytics Architect

Designs real-time analytics systems using stream processing frameworks like Kafka Streams, Apache Flink, and Spark Streaming. Covers event-time processing, windowing strategies, exactly-once semantics, and low-latency dashboard architectures.

Gold
v1.0.10 activationsData & AnalyticsTechnologyexpert

SupaScore

84.5
Research Quality (15%)
8.5
Prompt Engineering (25%)
8.6
Practical Utility (15%)
8.4
Completeness (10%)
8.5
User Satisfaction (20%)
8.2
Decision Usefulness (15%)
8.5

Best for

  • Design Kafka Streams topology for real-time user activity aggregation
  • Architect Apache Flink pipeline for fraud detection with 100ms latency SLA
  • Build ClickHouse materialized views for live operational dashboards
  • Implement exactly-once processing for financial transaction streams
  • Design event-time windowing strategy for IoT sensor data aggregation

What you'll get

  • Complete Kafka Streams topology diagram with state stores, windowing configuration, and exactly-once settings
  • Apache Flink job architecture with watermark strategies, checkpoint configuration, and operator parallelism settings
  • End-to-end real-time analytics stack design from event ingestion through dashboard rendering with latency budgets
Not designed for ↓
  • ×Batch ETL pipeline design (use streaming ETL architects instead)
  • ×Static dashboard creation without real-time requirements
  • ×Basic Kafka producer/consumer setup without complex processing
  • ×Traditional data warehouse modeling for analytical reporting
Expects

Specific latency requirements, data volume estimates, correctness guarantees needed, and event schema details.

Returns

Complete stream processing architecture with framework selection, windowing strategy, state management approach, and operational monitoring design.

Evidence Policy

Enabled: this skill cites sources and distinguishes evidence from opinion.

stream-processingreal-time-analyticsapache-kafkaapache-flinkspark-streamingevent-timewindowingexactly-onceksqldbclickhousedruidcepbackpressure

Research Foundation: 8 sources (2 books, 4 official docs, 1 industry frameworks, 1 academic)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.

Version History

v1.0.12/15/2026

Auto-versioned: masterfile quality gate passed (score: 85.0)

v1.0.02/15/2026

Initial release

Prerequisites

Use these skills first for best results.

Works well with

Need more depth?

Specialist skills that go deeper in areas this skill touches.

Common Workflows

Real-Time Analytics Implementation

Complete workflow from event modeling through real-time processing to dashboard delivery with monitoring

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