Data & Analytics

The need to manage Data and extract analytics is growing, and the leaders face escalating complexity in their data landscape. Zip Zap IT’s future-oriented data management solutions predictions acknowledge key factors in still-emerging development technologies and growing grow trends in demand for all data and cloud capabilities, connected data architectures, metadata, and the automation of routine tasks through the application of AI machine learning..


As an organization’s evolving needs change how they create and use data, IT leaders must transform how they standardize, govern, use, control, and manage increasingly distributed data assets. Modern data management solutions must become expansive, flexible and outcome-focused. Zip Zap IT works with your organization to lay out a roadmap that includes:

  • Emerging data management challenges
  • Data integration and data quality
  • Operational and analytical infrastructure
  • Metadata and master data management

Such a roadmap helps the organization overcome data challenges, leveraging our team's understanding and experience in data management solutions integrated to other systems, such as analytics and BI solutions, data and analytics programs, application development platforms, and integration architecture platforms. Our understanding helps our clients answer the following questions:

  • How can existing data solutions be modernized for strategic Enterprise solutions?
  • How do we develop data management capabilities to meet IT challenges?
  • How should we evaluate data management solutions and technologies?


Zip Zap IT works with your organization to rethink the strategies and identify key areas of innovation and modernization to meet your present and future demands. A common theme is a shift toward a more dynamic data management infrastructure that enables connecting and traversing distributed data assets, regardless of location, and with a deeper understanding of the diversity of formats, semantics, and governance requirements.

Supporting business processes that integrate data collection often proves a critical shift of focus. Balancing data connections and data collection is a foundational principle of modern data management solutions. Achieving such an infrastructure requires focusing on a core set of common capabilities and a rich backplane of metadata.

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