Azure Migration Assessment for Data Warehousing and Analytics

Streamline Azure Migrations, Maximize Azure Cost Efficiency and Business Value

Minimize Time Cost

Minimizes Migration Time, Costs & Effort

Mitigate Risk

Mitigates Unexpected Azure Migration Risks

Maximize Cost

Maximizes Cost Efficiency & Business Value in Azure

Customer Case Study

Director Data Warehousing, Money Center Bank
“Teleran’s Azure Migration Assessment enabled the bank to deliver a cost-effective, low risk migration that met business expectations. “

Teleran Migration Impact

  • Reduced migration time by 2 months versus the initial plan

  • Decreased expense by 4 man-months

  • Lowered ongoing Azure consumption costs by $25,000/month

 

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Data Warehouse Migration Challenges

Data warehouses are dynamic, complex and unpredictable with many users and applications accessing large, varied data sets. Before you migrate to Azure it’s critical to establish a comprehensive profile of data warehouse usage to identify the migration inhibitors common in legacy data warehouses. These unanticipated issues, if not identified and addressed, will increase the time, cost, and risk of your migrations.

Optimizing Azure DW Costs 

Legacy data warehouses often contain inefficient applications and user querying behavior that, while tolerated on well-resourced on-premise servers, drive up costs unnecessarily in Azure. To manage and control your Azure data warehousing costs, it is critical to identify and address wasteful usage practices as you migrate to the cloud.

Matching the Right Azure Service for Your Unique Data Warehouses and Analytics

Azure offers a variety of choices for SQL Server data warehousing: Managed Instance, VM, Azure SQL, Azure Synapse Analytics, Azure Data Lake, Data Bricks and even Cosmos DB. Data warehouse size, data type variety, workload complexity, concurrency, and performance are just some of the factors that determine where you should migrate your workloads and, importantly, how to provision your data warehouse to minimize risks and costs while optimizing performance and business value.

Addressing Data Warehousing Migration Challenges

Teleran’s automated assessment software unobtrusively analyzes on premise data warehouse and business intelligence/analytics usage. It quantifies and prioritizes usage and application issues that impede migrations and impact performance, productivity and costs on Azure. It identifies the optimal Azure service for your workloads. And, it highlights opportunities to improve and modernize your business intelligence and analytical applications to optimize the business value and ROI from your Azure investment.

Automation, Speed, Accuracy

Teleran’s automated solution replaces time-consuming manual assessments, bringing scalability, transparency, speed, and accuracy to planning and executing the optimal migration.

 

Azure Migration Assessment for SQL Server Data Warehouses

Complements and Extends Data Migration Assistant

It complements and extends Data Migration Assistant (DMA). DMA identifies incompatibilities that can impact database functionality in Azure and recommends performance and reliability features that can be used in Azure. Teleran’s Assessment is designed to address the unique challenges of understanding and migrating data warehousing and analytics workloads to reduce migration time, cost and risk, while optimizing business value.

Teleran’s Expert Azure Migration Assessment Capabilities

  • Automatically captures all relevant characteristics of your data warehouse and BI/analytics usage patterns without disruption or overhead
  • Expert system-based process automatically analyzes your workloads and recommends the best set of Azure services, resources and capacity to perform to business expectations
  • Assessment analysis engine incorporates deep SQL Server and Azure migration experience
  • Identifies and guides remediation of wasteful application and user behaviors and maintenance processes to ensure your data warehouse meets business needs while minimizing your ongoing Azure costs

 

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Customer Case Study

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