Investment Data Quality – Still Key

Investment Data Quality – Still Key

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.

  • Test data in-situ – Avoid time, cost and risk of moving data around as a pre cursor to validating it but be able to test it where it resides
  • Exception Detection – Quickly configure and manage data quality checks
  • Exception Management Workflow - Monitor and manage data exceptions and end user queries from inception through to resolution.?
  • Management Information (M.I.) Reporting – Ensure understanding of both current and historical DQM activities, including libraries of quality checks, data volumes, frequency, and quality scores
  • Complete Data Confidence – A dashboard to provide clear understanding of data quality at a point in time.?
  • Reduced Costs of Errors – Trap errors quickly and remediate them with the help of integrated enquiry tools to underlying and related data.?Automate notifications. ?Use quality scores as a stage gate before additional processing occurs.
  • Be able to amend data to correct it, quickly – Update/create data manually where required with appropriate permissions, precedence and audit trail
  • Exception or Data Analysis modes – generate either data quality exceptions tickets or quality exception profile information in relation to datasets

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.?

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