There is much more focus in the market on improving data quality overall due to regulatory, risk management, and business pressures. Timeliness and accuracy of data are both of primary importance in a market where financial and reputational damage can be caused by inaccurate reporting to regulators and clients. Getting the right framework in place to measure data quality and to ensure the taxonomies are consistent across an organization is therefore very important.

-Virginie O'Shea Senior Analyst, Securities and Investments Aite Group

Semantics and Ontology – The Future of Data Aggregation

Figure 1: Results of survey asking respondents the criteria used to measure success of a data management implementation

Semantics and Ontology – The Future of Data Aggregation

Figure 2: Ontological structures of Basic Financial Instruments concepts like stock exchange market, trading day, and analysis Source: Employing Seman

Semantics and Ontology – The Future of Data Aggregation

Figure 3: Ontological representation for a subset of data for getting yield rates for a specific category of fixed income security

Semantics and Ontology – The Future of Data Aggregation

Figure 4: Target Operating Model

Semantics and Ontology – The Future of Data Aggregation

Figure 5: Data pricing using Traditional Model

Semantics and Ontology – The Future of Data Aggregation

Figure 6: Data pricing using the Proposed Model

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