Streaming Analytics Specialist

Expert guidance on real-time stream processing architectures using Apache Kafka, Flink, and Spark Streaming, covering windowing strategies, exactly-once semantics, CEP, and operational best practices.

Gold

v1.0.00 activationsData & AnalyticsTechnologyexpert

SupaScore

84.6

Research Quality (15%)

8.5

Prompt Engineering (25%)

8.5

Practical Utility (15%)

8.5

Completeness (10%)

8.5

User Satisfaction (20%)

8.3

Decision Usefulness (15%)

8.5

Best for

▸Designing real-time fraud detection pipelines with sub-100ms latency requirements
▸Implementing exactly-once processing for financial transaction streams with Kafka and Flink
▸Building session-based windowing for user behavior analytics with complex event patterns
▸Optimizing watermark strategies for late-arriving IoT sensor data processing
▸Architecting multi-region streaming architectures with cross-datacenter replication

What you'll get

●Framework comparison matrix with specific use case mappings and architectural diagrams showing data flow and state management
●Step-by-step watermark configuration with code examples and late data handling strategies for specific business scenarios
●Production deployment checklist with monitoring dashboards, alerting thresholds, and operational runbooks for streaming infrastructure

Not designed for ↓

×Batch ETL pipeline design or traditional data warehouse modeling
×Real-time database replication setup or CDC configuration
×Message broker installation and basic configuration
×Basic SQL query optimization or traditional analytics reporting

Expects

Clear streaming requirements including throughput (events/sec), latency SLAs, data sources, processing guarantees needed, and acceptable complexity trade-offs.

Returns

Detailed streaming architecture recommendations with specific framework choices, windowing strategies, state management patterns, and operational monitoring approaches.

Evidence Policy

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

streamingreal-time-analyticsapache-kafkaapache-flinkspark-streamingstream-processingevent-drivenwindowingexactly-oncecepksqldbwatermarksdata-pipelinekafka-streams

Research Foundation: 8 sources (3 official docs, 2 books, 2 paper, 1 industry frameworks)

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

Version History

v1.0.02/15/2026

Initial release

Prerequisites

Use these skills first for best results.

Data Pipeline ArchitectGold

Works well with

Data Pipeline ArchitectGold Event Processing ArchitectGold Kafka Streaming ArchitectGold Observability Pipeline DesignerGold Real-Time Analytics ArchitectGold

Need more depth?

Specialist skills that go deeper in areas this skill touches.

Event-Driven Architecture DesignerGold Distributed Tracing EngineerGold Chaos Engineering PractitionerGold

Common Workflows

Real-time Analytics Implementation

Complete workflow from data ingestion design through streaming processing to real-time analytics with monitoring

Data Pipeline Architect→streaming-analytics-specialist→Real-Time Analytics Architect→Observability Pipeline Designer

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