FINBOURNE's Data Quality Offering helps create high quality data by allowing you to perform data quality checks across a breadth of categories, including:
- Evaluating and quantifying the quality of the data.
- Examining existing data to collect information and statistics about it.
- Cleansing corrupt or inaccurate data.
This in turn can bring benefits of:
- Improving business process management through accuracy and timeliness.
- Increasing process speeds with automated checks and reducing manual checks, handoffs and time spent on data searches and handling duplicates.
The Data Quality Offering is activated via FINBOURNE's Workflow Service and gives you out-of-the-box access to a suite of pre-built reference checks to assist you in checking your data is defect free, conforms to specifications and is suitable for purpose. Read more about the Workflow Service here.
Currently, the following 6 reference data quality checks are available, for which you simply need to provide input parameters:
- Null check, to check values exist for all or specific properties.
- Timeseries outlier check, to detect values deviating from a set range or mean during a particular period.
- Cross-sectional outliers check.
- Full instrument representation across all asset classes check.
- Transaction type configuration, to identify non-conforming transaction types.
- Transactions must be associated with specific instruments and currencies check.
You can choose to customise the available reference data quality checks or build new ones using Luminesce, FINBOURNE's data virtualisation engine. You can then run the checks in a way that best suits you, this might be:
- Fully automating a data quality control using the Workflow Service, by encompassing the data quality check in a worker. You might, for example, set up a workflow which ensures a chain of data quality checks are automatically performed when a new data file arrives in Drive, and then handles any exceptions. See an example of setting up a data quality control to check new pricing data for outliers.
- Scheduling a job to automatically perform a data quality check at a specified time with Scheduler. You might, for example, schedule a run of a null check Luminesce query at a certain time each day to check all instruments for missing data. See how to schedule a Luminesce SQL query.
To get started with the Data Quality Offering, contact your FINBOURNE sales representative.