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Architecting your organization's data for success

Maximize the value of your enterprise knowledge with data architecture services meant to deliver business value.


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Helping world-class organizations architect their data infrastructure

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With a well-designed architecture, you can turn data into a competitive advantage, gaining insights that drive fast growth and innovation.

Just as a skilled architect designs a building with the user in mind, good data architecture puts the needs of your business and its stakeholders first.

With Datavid’s data architecture services tailored to your unique needs and goals, you can unlock the full potential of your data and use it to drive success.

Streamline your data workflow

Good data architecture optimizes your data processes, reducing errors and increasing efficiency. Datavid helps you develop a technical architecture that matches your business needs.

Unlock hidden insights and deep analytics

Datavid's architecture services allow you to access and analyze data from multiple sources, identify patterns and trends in your data, and extract additional context from it.

Safeguard your business from external threats

With a strong data architecture, you can defend your business by maintaining compliance, keeping your data secure from leaks, and receiving real-time updates on competitive threats.

Build a strong foundation for your business

With a solid data architecture, you have the opportunity to unlock business operations that are directly connected from the customer to all departments in your organization—increasing productivity at a massive scale. 

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Organize your data for efficient operations

Datavid helps you organize your data into a logical and consistent structure that's specific to your business model—making it easy to store, manage, and access the right information. With our data architecture services, we help you reduce data redundancy, improve data quality, and streamline data workflows, leading to increased efficiency and productivity. 

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Enable effective analysis across functions

With Datavid's data architecture services, your business can easily access and analyse data from multiple sources, allowing you to make more informed decisions faster. By identifying patterns and trends in data, your business gains valuable insights that help you improve operations, optimize performance, and identify new opportunities for growth.

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Support data security and compliance

Reliable data architecture includes measures to ensure the security, privacy, and long-term trustworthiness of data, protecting it from unauthorized access or use and keeping you safe from surprise audits. This is especially important if your business operates in highly-regulated industries where compliance with data protection laws and regulations is critical.

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Revitalizing Smith + Nephew PMPA’s data architecture

Datavid helped Smith + Nephew, a leading medical technology company, by reviewing and improving their Post Market Performance Analytics platform’ architecture, resulting in cost-cutting and faster product development.

Datavid introduced agile methodology and a multi-disciplinary team with expertise in various technologies to provide efficient support and maintenance. The PMPA platform was reprogrammed according to the best-fit technologies and continues to receive dedicated full-stack developers' support.

Read the full case study →

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Datavid's winning solution was to implement agile development methodology and software development best practices to overhaul the architecture of the Smith+Nephew Post Market Performance Analytics platform and reprogram it.

Your questions. Answered.

Data architecture refers to the design and structure of an organization's data environment. It defines how data is collected, stored, processed, and accessed, including the databases, data models, data flows, and technologies used to manage and leverage data for business purposes.

An example of data architecture is the design of a company's data warehouse, specifying how data from various sources is integrated, transformed, and stored to support reporting and analytics. This includes decisions about data models, ETL (Extract, Transform, Load) processes, and the choice of database technology.

1) Data Requirements: Understand the specific data needs of your organization, including what data is essential, how it will be used, and who will access it.
2) Scalability and Performance: Ensure that your data architecture can scale to handle growing data volumes and provide efficient data processing and retrieval to meet performance requirements.
3) Data Governance and Security: Implement robust data governance practices to maintain data quality, ensure data privacy and security, and comply with relevant regulations and policies.

Take your organization's data practices to new heights

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