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Industry SolutionsData Analytics Solutions

Data analytics platforms that pull data from your existing systems into dashboards, alerts and machine-learning models, so operations, marketing and finance teams work from the same numbers in real time.

Small models of a house, a shopping bag, a coffee cup and a toolbox, with a phone in front
Fiverr
5.0 · 126 reviews
Own product
Workspace369
Fixed-price offers from
$450
Real-Time
streaming data processing
FL
Based in Miami, Florida
Flutter
iOS, Android & web
50/50
Upfront & on delivery

What We Deliver

Data Analytics Solutions We Deliver

01

Business Intelligence Dashboards

Interactive, role-based BI dashboards with drag-and-drop exploration, natural language queries, and scheduled reporting.

02

Predictive Modeling Engines

ML-powered forecasting, classification, and anomaly detection models deployed as scalable microservices.

03

Data Visualization Platforms

Custom visualization libraries supporting geospatial maps, time-series charts, network graphs, and real-time streaming dashboards.

04

ETL Pipeline Development

Scalable extract-transform-load pipelines handling batch and streaming data from 50+ source types including APIs, databases, files, and IoT sensors.

05

ML Model Integration

End-to-end MLOps pipelines for model training, validation, deployment, and monitoring in production environments.

06

Real-Time Streaming Analytics

Apache Kafka and Pub/Sub-based streaming architectures for processing millions of events per second with sub-second latency.

How it works

Our Development Process

Short sprints with a working demo at the end of each one mean you see progress early and can change priorities before they become expensive.

  1. Discovery

    We analyze your vision, goals, and competitive landscape to craft a solution roadmap. This phase typically runs 1-2 weeks and defines the full project scope.

  2. Design

    Intuitive UI/UX crafted with interactive prototypes. Prototypes let you test the flow with real users before any code is written.

  3. Development

    Expert engineering using Flutter, Vue.js, Node.js, and GCP in 2-week Agile sprints with weekly milestone demos for full transparency.

  4. Launch & Support

    Reliable deployment with crash and uptime monitoring and ongoing maintenance. Maintenance plans run during business hours, Monday to Friday.

Our Technology Stack

  • Flutter
  • TypeScript
  • Node.js
  • GCP
  • Firebase
  • Vue
  • JavaScript
  • Python

Questions

Frequently Asked Questions

How do custom analytics platforms handle real-time data processing at scale?

Streaming pipelines using Apache Kafka, Google Pub/Sub, and Apache Flink process millions of events per second with sub-second end-to-end latency. Data is ingested, transformed, and delivered to dashboards and alerting systems in near real time. Our infrastructure auto-scales on GCP to handle traffic spikes without manual intervention.

What is the difference between a custom analytics platform and off-the-shelf BI tools like Tableau or Power BI?

Off-the-shelf BI tools excel at ad-hoc exploration but face limitations with custom data models, embedded analytics, white-labeling, and real-time streaming. Custom platforms are purpose-built for your data structure and business logic, enabling tighter integration and better performance. We often integrate custom analytics alongside existing BI tools for maximum flexibility.

How do you ensure data quality across multiple source systems?

Data quality frameworks include schema validation, deduplication, completeness checks, and anomaly detection at every stage of the ETL pipeline. Data contracts define expected formats and SLAs between producers and consumers. Our monitoring dashboards alert teams to quality degradation in real time, and automated reconciliation ensures consistency between source systems and the analytics layer.

Can ML models be deployed and monitored within a custom analytics platform?

Yes, we build full MLOps pipelines supporting model versioning, A/B testing, canary deployments, and performance monitoring in production. Models are containerized and deployed as scalable microservices with automated retraining triggers based on data drift detection. We support frameworks including TensorFlow, PyTorch, scikit-learn, and XGBoost.

Simon Dziak - Founder of App369

Your Development Partner

Simon Dziak

I build every data analytics solutions project myself, with Flutter and Firebase, and I personally ensure every project meets the highest standards.

Harness the Power of Your Data with Advanced Analytics Solutions