Modernize your Datawarehouse - 2 weeks assessment

Mindtree Limited

Mindtree helps organizations build the foundation for a data-driven enterprise by moving legacy data infrastructure to a data lake on the Azure Cloud platform.

For most organizations, their data infrastructure is scattered across a multitude of operational systems including data warehouses. As both structured and unstructured data continues to grow, the existing data infrastructure is falling short of expectations in delivering accurate and timely insights. At Mindtree, we help organizations move from their legacy data infrastructure to a modern data lake using Azure Cloud.

We help you select the right operating model for Data Lake such that the existing data warehouse supports existing reporting, workload and data, while new data lake supports new analytical workload and data.

  • Complement Model where a data lake is used alongside a data warehouse. This supports new use cases such as multi-structured data analysis and predictive analytics.
  • Transform Model where a data lake progressively replaces relational-databases. This helps transform a company into a data-driven digital business with increased agility and improved efficiency.
  • Mindtree offers the following services for modernizing the data warehouse:

  • Data Strategy Definition and architecture blueprint.
  • Data Fabric for unified data management across sources and resources.
  • Data Lake Operating Model Design, Roll out, and Capability Buildout.
  • Analytics sandboxes for test and learns.
  • Managed Services.
  • Key Benefits achieved:

  • Lower costs for data warehousing, systems integration and data quality.
  • Accelerated data preparation and analytics to improve speed of business.
  • Enables customers to do rapid experimentation at lower costs.
  • https://store-images.s-microsoft.com/image/apps.39798.42bf3488-a589-4d50-b79d-6e24cc018048.1b0239b0-17c1-4e01-ba29-c7bac3825dc6.df4457f1-2f27-4f71-8bfc-d8b1f376bf60
    https://store-images.s-microsoft.com/image/apps.39798.42bf3488-a589-4d50-b79d-6e24cc018048.1b0239b0-17c1-4e01-ba29-c7bac3825dc6.df4457f1-2f27-4f71-8bfc-d8b1f376bf60

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