Modern data architecture as a strategic lever in the competitive landscape
Data has become the life blood of businesses and properly managing that data to gain the most value is becoming ever more important as businesses seek to remain competitive. This Insights paper will address the importance of investing in the processes, practices, and technologies to maximize the value of data in an enterprise.
Board members and C-suite executives view “Inability to utilize data analytics and ‘big data’ to achieve market intelligence and increase productivity and efficiency” among the Top risk issues for their organizations over the next decade.
DataOps is an emerging process based on agile software engineering and DevOps that encapsulates many data management best practices and helps generate better quality data and larger quantities of data analytics products. DataOps can enable companies to deliver data products faster and stay ahead of their competition.
Links to modern data architecture examples by the major cloud vendors:
- AWS: A new era of data: a deep look at how JPMorgan Chase runs a data mesh on the AWS cloud — SiliconANGLE
- AWS: Design a data mesh architecture using AWS Lake Formation and AWS Glue | AWS Big Data Blog (amazon.com)
- GCP: Data Mesh on the Google Cloud — A Technical Architecture Sketch | by Sven Balnojan | Towards Data Science
- Azure: Cloud-scale analytics — Microsoft Cloud Adoption Framework for Azure — Cloud Adoption Framework | Microsoft Learn
Organizations are harnessing the power of data to improve processes, drive new business opportunities and increase competitive advantage. We provide services to design, source, transform and analyze data to empower your business by modernizing your enterprise data architecture. Using our combination of strategic vision, proven expertise and practical experience, we will collaborate with you to enable the development of a cutting edge and pragmatic data architecture.
Our capabilities to enable a modern data architecture include:
- Developing a data strategy and roadmap tailored to your organization’s specific needs and growth objectives inclusive of architecture, organizational planning and data operations
- Establishing a data governance framework with aligned data management policies, tooling and operations
- Creating best-practices-based, streaming or batch ETL/ELT frameworks on a variety of cloud platforms to ensure your data is flowing properly
- Providing high-performing storage designs and implementations for data lakes and data warehouses supporting both operational and analytical data workloads
- Establishing policy authoring and design standards that deliver high-performing design standards and implementations for data lakes and data warehouses
- Launching a data security and privacy program that incorporates the appropriate data backup and recovery testing strategies, methodologies and testing models
- Designing a master data management strategy that will carry your organization well into the future
- Delivering analytics and reporting capabilities to enable self-service reporting, real time events, data discovery and more