BigRio brings new perspective to the traditionally slow and error-prone ETL process. We leverage proprietary technology which accumulates schema intelligence over the history of engagements. This central schema dictionary accelerates schema matching and compartmentalizes workflow tasks. The direct effect is a streamlined engineering process and parallelization of collaborative efforts, resulting in faster completion and improved data quality.
Our engineering incorporates the latest in-memory Big Data technology, delivering high-performance execution of ETL code. This Hadoop-based technology has built-in resilience and concurrency, and can run off both directly programmed code or UI-based configuration instructions. It scales linearly on commodity nodes, and therefore meets any volume requirements no matter how gargantuan the feed.
More often than not, data integration projects fail on lack of emphasis on metadata management and executive-sponsored data governance. All data sources are backed by a rich set of metadata, which captures data context (schema, format, semantics, etc.) and data lineage (origin of data and processing steps applied during transfer).