Srapsware
📊 Data & Analytics

Business Intelligence & Analytics

Transform raw data into actionable insights. Custom dashboards, real-time analytics, predictive models, and automated reporting - all in one platform.

Why Build Custom BI Solutions?

Generic BI tools show you data. Custom BI gives you answers.

❌ With Generic BI (Power BI, Tableau)

  • Per-user licensing ($15-70/user/month) gets expensive
  • Generic dashboards - not tailored to your KPIs
  • Complex learning curve for end-users
  • Limited customization and branding options
  • Difficult to embed in your apps
  • Data refresh delays (15-30 min typical)

✅ With Custom BI

  • Fixed cost - unlimited users and dashboards
  • Dashboards designed for YOUR metrics and workflows
  • Intuitive UI = instant user adoption
  • 100% customizable to match your brand and needs
  • Seamlessly embedded in existing applications
  • Real-time data updates (<1 second)
200+
BI Platforms Built
10TB+
Data Processed Daily
90%
Faster Decision Making
<1s
Query Response Time

Complete BI Capabilities

Everything you need to turn data into competitive advantage

Interactive Dashboards

Drag-and-drop widgets, drill-down capabilities, custom date ranges, filters, and real-time data updates. Mobile-responsive dashboards accessible anywhere. Role-based views showing relevant KPIs for each team. Export to PDF/Excel for stakeholder reports.

Drag & Drop
Real-time
Mobile Ready

Predictive Analytics

Machine learning models for forecasting sales, churn prediction, anomaly detection, and trend analysis. Automated alerts when metrics deviate from expected patterns.

Forecasting
Anomalies
Smart Alerts

Data Warehousing

Centralized data lake/warehouse combining data from all sources (ERP, CRM, databases)

ETL Pipelines

Extract, Transform, Load data from multiple sources with automated scheduling

Custom Visualizations

Bar charts, line graphs, pie charts, heatmaps, geographic maps, funnel charts, gauge meters, and custom visualizations specific to your industry. Interactive legends, tooltips, zoom/pan capabilities. Consistent branding and color schemes across all charts.

20+ Chart Types
Interactive
Branded

KPI Tracking

Define and monitor custom KPIs with targets, thresholds, and trend indicators

Scheduled Reports

Automated email reports (daily/weekly/monthly) with PDF attachments and Excel data

Self-Service BI

Empower users to build their own reports without IT help using intuitive query builder

React
Node.js
Python
MongoDB
PostgreSQL
Docker
AWS

BI & Analytics Technology Stack

Modern tools for building scalable data platforms

7
Expert Level
2
Advanced Level

BI Development Process

From data discovery to production deployment in 8-16 weeks

01

Data Discovery & KPI Definition

1-2 weeks

Audit all data sources (databases, APIs, files). Identify key metrics and KPIs for each department. Define data quality requirements and governance policies.

02

Data Warehouse Design

1-2 weeks

Design star/snowflake schema for optimal query performance. Set up data lake/warehouse on AWS Redshift, Snowflake, or BigQuery. Plan ETL pipelines for data ingestion.

03

ETL Development

3-4 weeks

Build data pipelines to extract from sources, transform/clean data, and load into warehouse. Schedule automated jobs for batch processing. Handle incremental updates efficiently.

04

Dashboard & Visualization

3-5 weeks

Design and build interactive dashboards with drill-down capabilities. Create custom visualizations for your specific metrics. Implement role-based access control.

05

ML & Predictive Models (Optional)

2-4 weeks

Train machine learning models for forecasting, anomaly detection, churn prediction. Integrate models into dashboards for real-time predictions and automated alerts.

06

Testing & Deployment

1-2 weeks

Validate data accuracy against source systems. Load testing for performance at scale. User training and documentation. Production deployment with monitoring.

What Our BI Clients Say

Real results from data-driven organizations

"Srapsware is best for server less and modern web application technologies. I suggest you try there services."
Blucloud
Owner at Blucloud
UK

Frequently Asked Questions

How much does custom BI development cost?
Basic dashboards (5-10 reports): $30K-60K. Mid-size BI platform (data warehouse, 20+ dashboards, ETL): $60K-150K. Enterprise BI (ML models, real-time, self-service): $150K-300K+. Compare to Power BI: 100 users × $20/mo × 36 months = $72K subscription + $50K+ implementation. Custom BI pays for itself in 12-24 months with unlimited users.
What data sources can you connect?
Databases: PostgreSQL, MySQL, SQL Server, Oracle, MongoDB, Cassandra. Cloud: AWS S3, Azure Blob, Google Cloud Storage. SaaS: Salesforce, HubSpot, Stripe, Google Analytics. Files: CSV, Excel, JSON, XML, Parquet. APIs: REST/GraphQL from any service. ERP: SAP, NetSuite, Dynamics. Custom: Any system with data export or API access.
Can you work with Power BI or Tableau?
Yes! We offer: 1) Custom dashboard development in Power BI/Tableau (if you already have licenses), 2) Data warehouse + ETL to feed Power BI/Tableau, 3) Custom connectors for proprietary data sources, 4) Embedded analytics (Power BI/Tableau embedded in your app), 5) Migration from one BI tool to another. We also build fully custom BI when Power BI/Tableau limitations are blockers.
How do you handle real-time analytics?
Real-time approaches: 1) WebSocket connections for live dashboard updates (<1 second latency), 2) Event streaming with Kafka/RabbitMQ for high-volume data ingestion, 3) In-memory databases (Redis, Memcached) for fast queries, 4) CDC (Change Data Capture) for real-time database replication, 5) Materialized views and pre-aggregated tables for instant query response. Typical latency: <1 second from source data change to dashboard update.
Do you provide data science and ML services?
Yes! We build: 1) Predictive models (sales forecasting, churn prediction, demand planning), 2) Anomaly detection (fraud, system errors, quality issues), 3) Classification models (customer segmentation, lead scoring), 4) NLP for text analytics (sentiment analysis, topic extraction), 5) Recommendation engines (product recommendations, content suggestions). Models deployed as APIs or integrated directly into dashboards with AutoML retraining.
What ongoing support do you provide?
Included: 3-month post-launch support (bug fixes, dashboard tweaks, data pipeline monitoring). Optional: Monthly retainer ($3K-15K) for: New dashboards/reports, new data source connections, ML model retraining, performance optimization, user training, 24/7 monitoring. Also offer data warehouse management, ETL maintenance, and BI consulting services.

Ready to Make Data-Driven Decisions?

Stop drowning in spreadsheets and disconnected reports. Build a custom BI platform that gives your team the insights they need, when they need them.