Data Integration Acceleration

An organization’s pursuit of a single, consistent, and current version of information, readily accessible throughout the extended enterprise, supports one goal – maintaining a competitive advantage.  This pursuit often begins with the implementation of an enterprise data integration (DI) strategy that can include data warehouses, data marts,  DI technologies, metadata management capabilities, a metadata repository, data quality and profiling capabilities.

Even the most carefully planned and well executed data integration environments unravel under the pressure of growing data sets and shortened operational timeframes.  Performance problems occur as these variables cause severe bottlenecks and latencies in processing and accessing data, often leading to damaging business ramifications – lost revenue opportunities, increased costs, impaired decision making, and customer attrition.

Syncsort’s Data Integration (DI) Acceleration Solution enhances the existing DI environments like Informatica, IBM DataStage, Microsoft SSIS, and Ab Initio by eliminating bottlenecks that impede performance in those environments. The Solution pairs Syncsort’s high-performance data integration software, DMExpress, with professional services and training specifically tailored to implement techniques and patterns that are optimized to address performance bottlenecks.

Syncsort's solution non-disruptively complements the existing DI environment and:

• Eliminates current performance bottlenecks:
• Reducing elapsed processing times by 50% or more
• Leaves a minimal resource footprint on your existing hardware
• Efficiently utilizing 50% less memory and 60% less CPU resources
• Deploying a graphical, drag and drop development environment
• Deployment in weeks, not months and offers a 75% increase in productivity over hand-coding.

DMExpress speeds slow processes in existing environments:

• Replacing slow data transformations
• Sorting prior to joins or aggregations
• Preprocessing data prior to load
• Creating pre-stored aggregation tables for reporting
• “Changed Data Capture” processing
• Index or table sorting during database reorganizations
• And via other implementation patterns.