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Data Warehouse Modernization

Solutions for modernizing data warehouses and data lakes. Many organizations with data warehouses and data lakes are grappling with legacy architectures that are ill-suited to today’s agile use cases, varied data formats and unprecedented volumes. While cloud data platforms can help overcome the constraints of traditional on-premises offerings, they don’t provide the tooling and capabilities needed for easy adoption and long term success. Quest Data Warehouse Modernization solutions help ensure an agile, optimal and governed enterprise data platform.
Database Warehouse Modernization

Overview

The expanded volume and variety of data types mean that schema designed for extract/transform/load (ETL) processes can no longer cope with the range of use cases for sound analysis and strategic decision-making. On-premises data warehouses lack the scalability and adaptability of modern data platforms in the cloud. Data Warehouse Modernization solutions from Quest combine data governance, metadata management, platform automation, replication, data modeling and infrastructure monitoring to enable organizations to maximize their investment in cloud data platforms.

Empower your data warehouse

Quest’s Data Warehouse Modernization solutions enable organizations to model, migrate and govern strategic data assets in their chosen cloud data platform. They leverage the power of the Quest Data Empowerment portfolio to ensure data is available and ready to meet the changing needs of the business.
Model your new data warehouse

Model your new data warehouse

Legacy data warehouse architecture inhibits visibility into schema, data types, and movement and transformation processes. This leaves data warehouse teams in the dark when it comes to planning and redesigning a data warehouse on a modern platform. Data modeling and data intelligence tools from Quest automate the use of metadata to document the legacy system and inform the design of the new system.

  • Harvest, curate and activate metadata to understand where relevant data resides and make it accessible to stakeholders
  • Automatically document your data landscape and pipelines with visualizations of data lineage and provenance
  • Reduce cloud costs ahead of time with data profiling and comparisons, performance benchmarking and workload optimization
Migrate the data, structures, logic and processes

Migrate the data, structures, logic and processes

Organizations migrating to a modern data warehouse inevitably face increased costs, longer timelines and decreased accuracy if the work is done manually. Automating processes like redesigning schema, replicating data and verifying data accuracy can reduce costs while also enabling high availability, disaster recovery and workload distribution. Quest tools work across database platforms to ensure data is always available when and where it is needed.

  • Use productivity-enhancing data modeling capabilities to automate the transformation and redeployment of legacy schema to modern technologies
  • Provide a fast, accurate and secure environment to replicate data and move workloads across on-premises and hybrid cloud environments
  • Ensure accurate data migration with detailed data compare capabilities
Govern and automate your modern data warehouse operations

Govern and automate your modern data warehouse operations

The traditional disconnect between IT teams and business users has resulted in a lack of visibility into the rules and policies governing data classification, usage and retention of data warehouse assets. This low level of stakeholder data literacy can affect compliance as well as reduce the overall quality of enterprise data. Data governance tools from Quest ensure all teams understand data usage policies along with the business purpose of stored data.

  • Establish a data governance framework to define classification rules and regulate data usage
  • Enable architects and developers to modify schema via graphical models, automate the generation of schema alter code and ensure changes are reconciled back to business process flows via the metadata repository
  • Provide web-based, read-only access to an integrated data governance and intelligence portal that promotes self-service discovery, stakeholder collaboration and data community support

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Resources

Case Study

Health Insurance USA

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