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Datometry qInsight for Teradata/Exadata Data Warehouse Analysis

Datometry

Datometry qInsight for Teradata/Exadata Data Warehouse Analysis

Datometry

Assess your Teradata/Exadata workloads for a migration to Azure Synapse (with TCO and timeline)

Move analytics to the cloud with confidence
Datometry qInsight™ is the first comprehensive data warehouse analysis used by the Fortune 500 and Global 2000 to map out the re-platforming of legacy data warehouses to the cloud. Datometry qInsight gives enterprise customers and IT leaders answers to all critical questions to prepare for a successful re-platforming initiative, including:
• Assessing difficulty and complexity of entire workloads
• Supporting sizing and capacity planning
• Identifying specific risks and obstacles
Available as SaaS, qInsight is simple to use and quick to analyze even large and complex workloads in a matter of minutes. Reports are comprehensive, easy to navigate, and provide drill-downs into advanced subjects. Based on a customer-selected sample workload, qInsight provides the knowledge IT professionals need to decide which replatforming strategy is most suitable: replatforming of the entire data warehouse, a staged approach, or the splitting off of individual workloads.

Report Highlights
Understand and quantify the anticipated effort when replatforming.
Datometry qScore™ is computed for each given workload based on usage and frequency of query features—including proprietary SQL constructs—and other parameters that affect rewriting of applications.
Make cloud choices with confidence.
Datometry qInsight is target-specific and takes into account the properties and limitations of the desired target platform and determines suitability of workloads.
Understand the system at a glance.
Beside the most critical system parameters, this summary includes the vital count of unique queries determined not by textual difference but by query structure, which is only available through an in-depth analysis of a query.
Identify workloads for prioritization, spot optimization opportunities, avoid surprises.
Statement analysis by application combines and contrasts daily query volume with actual workload complexity.
Detect infrequently used objects suitable for off-load into data lakes.
Data usage statistics show immediate capacity savings based on the time of last access.
Plan for capacity and scale with confidence.
High-resolution analysis of workload patterns with controls for interactive exploration lets customers determine the true TCO of the new target platform.
Isolate and prioritize workloads when pursuing a multi-cluster strategy.
Access analysis makes clear which data sets are shared between applications and which can be separated out—without guesswork.
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https://store-images.s-microsoft.com/image/apps.40609.71d3be56-0725-456d-97d5-4776d1b75a30.2d035292-7996-4a68-b91e-37dd38fcbab1.041b6833-9979-4d41-9b2b-e66c558a5bd6