Data Architecture

A framework that delivers productivity, optimized operations and data quality

Most global organizations collect, store, and analyze enormous amounts of data every day – without proper management. Organizations are slowly recognizing the importance in managing business processes and information data assets with a single, strategic goal.


Simultaneously, technology advances are growing exponentially – from the way we think about a database and its relationship to the supporting infrastructure. Data architecture uses processes, systems and technology, and human performance to optimize the storage, access, movement, and organization of data.


Architecture Development Process

Client Challenges

Data architectures must take into account potentially conflicting requirements in order to be effective:

  • Transaction systems:  Fast response time
  • Business Intelligence: Large volumes of data
  • Reporting:  Wide distribution

The standards should be:

  • Binding to the whole enterprise and not redundant.
  • In place for the data architecture component to enable resource sharing, reduce equipment and operations costs.

What CDS Provides

CDS data architects have a wealth of experience working on the complex IT projects. They help you simplify and optimize your IT environment by leveraging new technologies and defining strategic roadmaps for future growth.

They work with our alliance partners to help organizations manage the large expanse associated with growing data storage requirements.

As data volume increases, data migration is necessary to move information from a transactional database to a data store.

Our data architecture approach includes components that support the vision to improve data quality, productivity, and operational efficiency as the organization grows.

We help clients define and designate the people, processes, and technologies to effectively manage data across its lifecycle. With strong hardware and software leading vendor alliances, we provide our clients an open perspective on data architecture at each stage of the data lifecycle.

Business Value

Our data architecture approach includes components that support a vision to improve the following as your organization grows:

  • Data quality
  • Productivity
  • Operational efficiency