Investment Data Quality – Still Key
Curium Data Systems
Innovations in Enterprise Data Management and Data Quality Management
As data management practices mature and evolve, I sometimes think that the end goal is being lost.?There has been significant talk and effort in the recent past regarding data management topics such of gold copy, governance, cloud, data mesh and data fabrics, ML, AI, and data science etc. ?Certainly all worthwhile. However, any of these endeavours will be considerably less successful if the underlying data quality is not established and maintained and this needs to remain a focus.?After all, garbage in, garbage out.
Firstly, identify your crucial data sets and elements.?Then measure them for data quality.?This cannot be a one-off exercise.?Ideally, it should be done as regularly as are updates to those datasets.
As part of the exercise of quality checking and measuring your data, it may also be an appropriate time to add data governance to those sets such as definitions/dictionary, stewardship, lineage etc. ?If you find that your data quality is problematic, then look to remediate your data sourcing, integration, and mastering. ?After all, “Completeness” is a data quality measure, and one that may require enhancements to fuller Enterprise Data Management capabilities such as ETL and MDM. ?However, if you start with a data quality lens, it should help ensure you target the most important data sets first and identify weaknesses.
When selecting a solution for your data quality management there are several capabilities which we felt were important in the development of CuriumDQM to provide a holistic DQM solution.
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Data Quality Management should be a cornerstone to any mature data management capability within an organisation.?If you can’t measure something, then it is difficult to improve.?
APRA’s CPG 235 provides an excellent set of best practice guidance and is a must read for anyone involved in data management in the finance industry, particularly here in Australia.?Whilst more broadly concerned with Data Risk, much of the guideline outlines expectations in Data Quality frameworks. Currently it is a guideline and not a standard!
However, if (when?) APRA regulates enforceable standards over data management, as other regulatory authorities around the world are doing, it is safe to assume that CPG 235 would be one of the bases for that standard and there will be a mad scramble for organisations to be compliant.
But why wait? CuriumDQM is a sophisticated DQM solution that provides a range of capabilities that we have developed for over a decade whilst servicing global asset managers, pensions funds and market data providers.??It is exceptionally quick to configure to your datasets, to see results and return on investment, and provides demonstrable compliance with data management best practice guidelines such as CPG235. Especially when combined with CuriumEDM for ETL, MDM and Governance. ?And that’s just good practice.?
If any of this resonates with you and you would like to discuss, please don’t hesitate to reach out to us.?