Transform raw data into strategic assets with enterprise-grade data pipelines, warehouses, and analytics platforms that power data-driven decision making across your organization.
Data is the new currency of enterprise operations, but raw data alone provides little value. The challenge enterprises face is not collecting data—it's transforming scattered, inconsistent data from dozens of systems into clean, reliable insights that drive better decisions. At Dalto Software, we build comprehensive data engineering solutions that unify data from ERP systems, production equipment, sensors, third-party APIs, and legacy databases into centralized data warehouses and analytics platforms.
Our data engineering expertise spans the full spectrum from data ingestion and storage to visualization and advanced analytics. We design data architectures that handle everything from batch processing of historical data to real-time streaming analytics. Whether you're consolidating sales data from multiple regional systems, analyzing production metrics to identify bottlenecks, or building predictive models to forecast demand, we create the foundation that makes sophisticated analytics possible.
Beyond infrastructure, we focus on making data accessible and actionable for business users. We build self-service BI dashboards that empower managers to explore data without SQL knowledge, implement data quality monitoring to ensure trust in analytics, and establish data governance frameworks that balance accessibility with security. Our solutions don't just store data—they democratize insights across your organization.
Comprehensive data solutions from ingestion to insights
Design and implement enterprise data warehouses that consolidate data from all your systems into a single source of truth. Build dimensional models optimized for analytics queries and historical trend analysis.
Develop robust data pipelines that extract data from diverse sources, transform it into consistent formats, and load it into warehouses or lakes. Handle batch processing, incremental loads, and CDC.
Create interactive dashboards and reports using tools like Power BI, Tableau, and Looker. Build self-service analytics platforms that empower business users to explore data and answer their own questions.
Implement streaming data pipelines using Kafka, Kinesis, and Spark Streaming. Enable real-time dashboards that reflect current operations. Support event-driven architectures and immediate alerting.
Build scalable data lakes that store structured, semi-structured, and unstructured data cost-effectively. Implement lakehouse architectures that combine flexibility with warehouse performance.
Establish data quality frameworks that validate, cleanse, and monitor data accuracy. Implement governance policies, data lineage tracking, and access controls that ensure compliance while maintaining usability.
Build predictive models and statistical analysis workflows that forecast outcomes, detect anomalies, and optimize operations. Deploy machine learning pipelines that continuously improve from new data.
Connect disparate systems through APIs, database replication, file transfers, and custom connectors. Handle complex data mappings, format conversions, and reconciliation between systems with different data models.
Our data engineering solutions power decision-making across diverse industrial sectors, each with unique data challenges and analytics requirements.
We leverage industry-leading data technologies and select the right tools for your specific requirements, ensuring scalable, maintainable, and cost-effective solutions.
We follow a proven methodology that ensures your data projects deliver business value through iterative development and continuous improvement.
We catalog your data landscape—identifying source systems, understanding data volumes, assessing data quality, and documenting current pain points. We interview stakeholders to understand key business questions and analytics requirements.
Based on discovery findings, we design a data architecture addressing your specific needs. We select appropriate technologies, design data models, and plan integration patterns. We create detailed technical specifications and data flow diagrams.
We build a working prototype focused on one high-value use case. This might be a dashboard for a specific department or a pipeline integrating 2-3 key systems. The pilot validates our architecture and demonstrates value quickly.
After pilot validation, we implement the complete data platform. We build ETL pipelines for all identified data sources, establish data quality checks, implement security and access controls, and create the full suite of dashboards.
We train business users on dashboard usage, self-service analytics tools, and data interpretation. We provide technical training for IT teams on pipeline maintenance and monitoring. We document data models, business logic, and procedures.
Post-launch, we monitor pipeline performance, optimize query performance, and refine dashboards based on user feedback. We add new data sources as requirements evolve and continuously improve data quality to maintain analytics accuracy.
We don't build data platforms for their own sake—we solve business problems. Every pipeline, dashboard, and model is designed to answer specific business questions or enable concrete decisions. We start with high-value use cases that demonstrate ROI quickly rather than attempting to "boil the ocean" with massive data migration projects.
Enterprises have complex, heterogeneous IT landscapes. We excel at connecting systems that weren't designed to work together—from modern cloud SaaS applications to 20-year-old on-premise databases. We have experience with ERP systems, industry-specific software, custom applications, and legacy mainframes.
We build platforms with security, compliance, and governance baked in from day one. We implement role-based access controls, data masking for sensitive information, audit logging, and lineage tracking. Our solutions meet compliance requirements for GDPR, HIPAA, SOX, and industry-specific regulations.
The best data platform is worthless if business users can't access insights. We design self-service BI experiences that empower users without requiring SQL knowledge or technical expertise. We build intuitive dashboards, implement natural language query interfaces, and create curated datasets.
Data platforms require ongoing attention as business needs evolve and data volumes grow. We provide proactive monitoring, performance optimization, and regular enhancements. We track usage patterns to identify opportunities for new analytics, optimize slow queries, and refine data models.
Let's discuss how data engineering and analytics can transform your business intelligence. Whether you're starting your data journey or looking to scale existing capabilities, our team can help you build a data-driven organization.