info@vizioconsulting.com
+1 (289)-952-8845
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Get In Touch
info@vizioconsulting.com
+1 (289)-952-8845
X-twitter Youtube Linkedin Facebook Pinterest

Get In Touch

AWS
Real-Time Data Streaming

Harness the full potential of Amazon Web Services for scalable, secure, and high-throughput real-time data processing solutions

AWS Certified Experts
Streaming Data Specialists
Low-Latency Processing
Take The Journey

Introduction to
Real-Time Data Streaming on AWS

In today’s digital landscape, the ability to capture, process, and analyze data in real-time is no longer a competitive advantage—it’s a business necessity. Real-time data streaming enables organizations to make informed decisions instantly, respond to changing conditions immediately, and deliver personalized experiences that meet ever-evolving customer expectations.

Vizio Consulting specializes in implementing these technologies to help businesses unlock the full potential of their real-time data.

See in in action

Our Comprehensive Approach

  • Millisecond Latency
  • Seamless Integration
  • Enterprise-Grade Security
  • Open Sourced Models
  • Curated Dataset
  • Portfolio Building
  • Practical Courses
  • Public Database

Why Choose Vizio

Vizio enables organizations to cut storage costs by using smart tiering that adapts to changing data access needs.

  • Data streaming
  • Milisecond Latency
  • Data Security
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01

Aws

02

Architecture

03

Data

      TARGET MARKET:

  1. Technology leaders seeking data modernization
  2. Data architects designing enterprise solutions
  3. CTOs evaluating cloud transformation strategies
  4. Enterprise decision makers requiring analytics capabilities

Implementation Considerations

Key factors to consider when implementing AWS AI/ML solutions in your organization:

      COMPETITIVE ADVANTAGES:

  1. Deep AWS platform expertise and certifications
  2. Proven implementation methodologies
  3. End-to-end solution delivery
  4. Industry-specific experience
  5. Comprehensive post-implementation support
  • Strategic assessment and use case identification
  • Model development and optimization
  • On-going monitoring and model management
  • Responsible AI practices and governance
04

Deep AWS platform

05

Proven implementation

06

Analytics

Artificial Intelligence //
The impact of AI on the evolution of future technologies. //
Artificial Intelligence //
The impact of AI on the evolution of future technologies. //
Enterprise-wide reporting //
regulatory compliance //
Cross-functional analytics //
AWS //

Technical Considerations We Address

Latency Management Elastic Scalability Data Security Data Quality Fault Tolerance

Latency Management

Techniques to minimize processing delays, optimize network configuration, and handle time-sensitive data requirements across distributed systems.

Optimize data ingestion pipelines
Use edge processing when possible
Minimize network hops
Choose low-latency data stores

Elastic Scalability

Designing for dynamic workloads with auto-scaling capabilities, partition strategies, and throughput management to maintain performance during peak loads.

Implement auto-scaling on data consumers
Use shard splitting in Kinesis
Utilize AWS Application Auto Scaling
Design partitions for high cardinality

Data Security

Implementing encryption in transit and at rest, fine-grained access control, audit logging, and compliance with regulatory requirements for sensitive data.

Use KMS for key management
Encrypt all data in motion and at rest
Apply IAM roles and policies
Enable audit logs in CloudTrail

Data Quality

Schema validation, error handling, data cleansing, and stream processing strategies to ensure accuracy and consistency in real-time data flows.

Validate input schema at source
Include retry logic and dead-letter queues
Use data contracts across producers/consumers
Monitor data quality metrics

Fault Tolerance

Implementing message replay capabilities, dead-letter queues, redundancy across availability zones, and graceful degradation strategies.

Store checkpoints for replay ability
Use multi-AZ deployment strategies
Incorporate DLQs for failed events
Set retry policies with exponential backoff
Our implementation expertise spans the full spectrum of AWS’s industry-leading data streaming technologies

Core AWS Real-Time Data Streaming Services

Amazon Kinesis Data Streams

Capture and store terabytes of data per hour from hundreds of thousands of sources, with retention of up to 365 days for delayed processing or replay.

  • Unlimited throughput capacity
  • Sub-second data ingestion
  • Multi-AZ replication
  • On-demand capacity mode

Amazon Kinesis Data Firehose

Simplify data loading to S3, Redshift, Elasticsearch, and third-party destinations with automatic scaling and zero ongoing administration.

  • Serverless data delivery
  • Automatic scaling
  • Data transformation
  • Pay-as-you-go pricing

Amazon Kinesis Data Analytics

Process streaming data in real-time with standard SQL or Apache Flink to extract insights and power real-time dashboards and alerts.

  • SQL and Apache Flink support
  • Serverless operation
  • Millisecond latency
  • Built-in functions and operators

Amazon Managed Streaming for Kafka

Fully managed Apache Kafka service that makes it easy to build and run applications that use Kafka for data processing, real-time analytics, and more.

  • 99.9% availability SLA
  • Auto-scaling capabilities
  • Native Apache Kafka APIs
  • VPC connectivity

AWS Lambda

Process streaming data with event-driven functions that automatically scale to match your throughput needs without provisioning servers.

  • Event-driven processing
  • Millisecond startup time
  • Native Kinesis integration
  • Up to 10GB memory allocation

Amazon EventBridge

Serverless event bus that connects application data from your own apps, SaaS, and AWS services in real time to simplify event-driven architectures.

  • Schema registry
  • Content-based filtering
  • SaaS integration
  • Archive and replay events
How Vizio helps convert real-time data streams into actionable intelligence that drives measurable business outcomes

Business Impact

Real-Time Decision Making

80% Faster response to market changes & 15% Increase in conversion rates

Operational Intelligence

60% Reduction in system downtime & 45% Decrease in mean time to resolution

Predictive Analytics

35% Improvement in forecast accuracy & 25% Reduction in operational costs

Enhanced Customer Experience

40% Increase in customer engagement & 30% Higher customer satisfaction scores
Powered by AWS

Real-Life
Industry Use Cases

Financial Services:
Fraud Detection

→ $4.3M annual fraud loss reduction
→ 98.7% detection rate
→ 200ms typical detection

Healthcare: Patient Monitoring

→ 23% reduction in critical events
→ 17% decrease in ICU stays
→ 27% faster response times

Manufacturing: Predictive Maintenance

→ 97% accuracy in failure prediction
→ 37% reduction in maintenance costs
→ 13% increase in production uptime

Retail: Inventory Optimization

→ 82% reduction in stockouts
→ $8.3M savings in carrying costs
→ 2.8x improved inventory turnover

Future Outlook

How real-time data streaming is evolving and what this means for your business in the years ahead

integration
Planning
Pricing

Edge Computing Integration

Edge computing is enabling real-time decisions closer to data sources, reducing latency and bandwidth usage.
Prediction: AWS will enhance edge stream processing with seamless integration to core services.

Streaming AI/ML at Scale

Real-time data is fueling continual AI/ML model training and inference.
Prediction: AWS will launch tools for adaptive, streaming ML pipelines.

Api
Cloud
Dashboard

Event-Driven Architectures

Reactive systems are built around real-time events using EventBridge and Step Functions.
Prediction: Event-driven apps will become standard, with advanced event orchestration tools from AWS.

Tuning
Performance
Scalability

Data Mesh & Streaming

Streaming is becoming integral to decentralized data architecture.
Prediction: AWS will support domain-oriented streaming within data mesh ecosystems.

Teams
Scalability
Visualisation

AWS Real-Time Streaming Roadmap

2025-2026

Enhanced Serverless Streaming

AWS will expand auto-scaling capabilities for streaming services, reducing the operational complexity of managing streams at any scale.

2026-2027

Cross-Region Streaming

Improved tools for global streaming applications with better support for cross-region replication, global consistency, and multi-region failover.

2027-2028

Streaming Governance Revolution

Advanced governance capabilities for streaming data, including real-time data quality monitoring, lineage tracking, and compliance controls.

2028-2030

Quantum-Enhanced Analytics

Integration of quantum computing capabilities with streaming analytics for solving previously intractable problems at scale.

Implementation Consideration

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Assessment & Strategy

Secure and scalable data ingestion with validation

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Development & Implementation

Infrastructure and apps built for streaming.

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Architecture Design

Scalable AWS architecture for streaming performance.

Monitoring & Optimization

Real-time insights, tuning, and improvements.

Conclusion

Analyze, and Act
on data in Real-time

  • Deep expertise in AWS
  • Real-time streaming solutions
  • Real-time data capabilities.
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