Data Management

Effectively capturing, managing and leveraging data to derive meaningful value is a requirement for organizations today. In order to successfully guide present and future decisions, organizations must have control over this data and the metrics it creates. These challenges usually require teams to build data integration and ETL processes, with business analysts defining requirements and engineers deploying the data integration technology.

The Sherlock data management capability is based on a mature and industry leading rule based ETL product, allowing data to be captured, integrated, cleansed, rationalized and managed using established best practices and standards. It is aligned with the customer level of data maturity to provide consistent and trusted data for operational data analysis, while enriching with reference data for industry related codes, prices and geographic tagging. 

The Sherlock Data Lab platform helps transform data into information, knowledge and intelligence using a hybrid approach to data warehousing which incorporates both a top down and bottom up paradigm and design path, providing tactical and strategic level insights. The framework can readily be extended to encompass mastering data with established methodologies for Governance and Stewardship, with specific focus on data quality and metadata management.

The scope and future volume of source data will readily lend itself to deep analytics for research and exploration, burgeoning into the world of Big Data.

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