Business Intelligence & Data Architecture Project

Data Analytics Architecture & Business Intelligence Project

Technology supporting Analytics

Many organizations come to us and need help moving their technology and business processes from being reactive to proactive. Companies who use the report-driven, reactive business model are missing out on the competitive advantage and revenue generating opportunities a more proactive, insights-driven data analytics architecture and infrastructure can provide.

Mosaic can deploy cloud based technologies to meet your analytic goals. Mosaic can provide best practices around data engineering, making sure your technology is aligned with your analytic goals. Our deep expertise developing and deploying decision support capabilities for numerous clients gives us a unique perspective in how to run a successful analytically-driven architecture project.

If you need big data support, Mosaic has experts who wrangle this data and transform it to acceptable analysis levels. Mosaic can also help with small data, helping you design and deploy solutions which integrate from across disparate sources.

Our vendor agnostic approach allows us to view the market equally. Our software development team has deep experience with some of the more popular tools on the market today, open source and licensed. We are confident we bring the right technology to your environment.

What we provide

A BI project often includes the following activities:

  • Detailed data profiling and preparation
  • Data-architecture implementation, tuning, or refactoring
  • ETL implementation, tuning, or refactoring
  • Dashboard and report development
  • Development or implementation of a virtual analytics infrastructure
  • Development of a data-governance or data-stewardship capability

BI project deliverables may include the following:

  • A physical data store meeting requirements for content, duration, physical architecture, change history, data quality, and query performance/scalability
  • An ETL system consistent with the data-store requirements and also meeting requirements for execution time, recovery, and logging
  • A set of dashboards and reports that meet requirements for content, look and feel, and performance
  • A service-oriented analytics architecture
  • An operational data-governance program