Curium Data Quality Management
Whether as part of a broader data governance programme or simply as a key element of risk and cost reduction initiatives, data quality management (DQM) is an essential discipline for all financial services firms.
CuriumDQM is innovative because it puts the configuration and maintenance of the data quality process firmly in the hands of the business users who need access to the best possible information and features to investigate and resolve data issues. It gives Operations and Data Analysts the tools to define and maintain their data sources, build and execute business rules and establish workflows that match their process needs and management information requirements.
From an IT perspective, CuriumDQM is a small footprint and low risk solution. Deployed in the cloud or on premise, it is highly configurable and works alongside any established data architecture with minimal change or disruption and without the need to replace existing applications and databases.
Once implemented, it frees up valuable IT resources as the business users take greater control over the data management environment. This approach allows the firm to obtain all the benefits of Curium while protecting and enhancing the investment already made in existing data stores/hubs and processing systems. Alternatively, if a complete change in the data architecture is required then Curium can be used as a key component in a best of breed approach.
Inside CuriumDQM
Issue Detection
Quick and easy to use, point and click environment for the configuration and detection of all common data validation issues without the need to ‘code’ the tests. Key features include:
- Powerful click on/click off standard rule set for the most frequently required data checks
- User defined custom rules for more complex validation logic
- Easy channeling of data into appropriate validation groups or sets
- ‘What if’ (test mode) for up front data quality analysis – for on the fly investigation or pre implementation phase
Workflow and Investigation
Process control application to monitor and manage data exceptions from inception through to resolution.
Key features include:
- Management dashboard, customizable workflow and audit trails to ensure ownership, tracking and resolution of data issues
- User defined business criteria to prioritise and channel data exceptions to appropriate queues and/or users
- Sophisticated ‘noise’ suppression to ensure business stays focused on real data issues rather than background, non-critical or aged issues
- Capture of data snapshots at the point of exception detection and on-line queries for up to the minute analysis.
- Cross architecture data queries to support issue investigation and impact analysis (e.g. I have an issue with a particular Security. Which funds hold this security? When was it last traded?)
- Ability to merge exceptions for ease of investigation, manageability and efficiency
- Ad hoc creation of data exception tickets directly from an email or manual entry where no automated process exists
- Ability to import data exceptions from other systems to enable centralised issue management
- Automated notifications (e.g. emails, messages) configurable against specific events and updates
Data Amendment
Centralised initiation and control of data corrections to any target data source/system(s) within the architecture. Separate DQM module includes full audit allowing current and historic analysis of any changes made.
Key features include:
- Pick lists and ‘drag and drop’ from any identified data source (or even other applications) for ease and minimizing risk of data correction errors
- Configurable cross attribute validation and optional ’four eyes’ and supervisor release mechanisms
- Integration with external system procedures which apply the amendments and post status information back to Curium
- Full audit of activity for analysis of active amendments and amendment history
Data Visualisation
Highly configurable data exploration tools including display, report, search and export capabilities for cross architecture analysis.
Key features include:
- ‘Side by side’ displays of data attributes across any/all data sources, master data copies and target systems for a system wide view over a specific set of data attributes
- Context driven, drill across capabilities to other types of supporting data across the architecture without the need for a structured common key
- User defined enquiry layouts with configurable filters, group and sort functions
- Integration with MS Excel for further analysis of any data query/report
Management Information
Comprehensive analysis of issue activity driving department and firm wide MI. Analysis of internal and external data providers and operational processes throughout the data supply chain.
Key features include:
- ‘At a glance’ system dashboard providing instant monitoring of all issues, status and amendments with comprehensive navigation to supporting data.
- User definable, root cause capture to aid trend analysis and identification of problem sources
- ‘Time to close’ reports – MI on the effectiveness of the data quality process to match against business needs and internal SLAs
- Wide range of reports to support ongoing data quality improvement targets
- Integration with BI tools for custom MI and analysis
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