July Release Notes

Aunalytics is excited to announce the July 2021 release to our clients. This release will provide clients with model and site enhancement information along with any fixes to existing functionality we have included.

Daybreak

Data Builder Improvements

This month we're releasing significant improvements to the Daybreak Data Builder user interface, including grouped conditions and a column selector that now allows you to display fields from foreign tables in a query result. Learn more by reading on, or watch our feature release video.

Condition Groups

Previously, Daybreak Data Builder allowed users to build queries using the Query Wizard that had one or more filter expressions (conditions) that were combined so that all conditions had to match (i.e. using the SQL AND keyword) for a result to be included. This month, conditions can now be grouped so and those groups will be evaluated to restrict (AND the condition) or expand (OR the condition) the results that will be included when the query is run.

For example, previously you could not create a single query that would include customers whose ages were either between 18-35 or 65 or older. Now, that query can be created with two condition groups joined inclusively: results will be retrieved for any record that matches either condition.

The inclusion of condition groups has changed the look and feel of the Query Wizard, so take some time to familiarize yourself with the new look and feel.

Column Selector

Daybreak data marts employ a relational entity relationship model (ERM), sometimes called a relational database. For example, Daybreak for Financial Services includes different tables for customers, transactions, accounts, and branches. Each transaction is linked to a single account, and each customer can be linked to one or more accounts---and by extension, to the transactions for those accounts.

The Data Builder has always been able to understand these relationships in order to build complex queries, such as "Give me a list of customers whose credit card monthly balance was more than $5,000." However, when this query is run, the Data Builder's column selector could only include fields from the Customer table in the query results.

This month, the column selector has been updated to allow fields from related records in another table to be included. This feature, which required extensive logic to be applied in order to create the appropriate SQL JOIN statements, enables users to create more powerful datasets that combine data from different tables to support the generation of more comprehensive datasets drawn from multiple tables in the data mart.

Query results in the Daybreak Data Builder will now display URLs in data field results as clickable hyperlinks. This will allow Daybreak to support a new Daybreak application being developed by Qumulus Solutions for document storage and retrieval. With this change, Daybreak data marts will be able to link to data or documents stored outside of the data mart via URL hyperlinks.

Natural Language Answers Model Retrain

This month, the Innovation Lab has retrained the Natural Language Answers™ model responsible for translating natural language questions into SQL queries. This retrain has enhanced support for fields that had previously not been well integrated into the model's training:

  • ClosestBranchDistance: "Give me a list of customers that live less than five miles to the closest branch."
  • DistanceToHQ: "Give me a list of customers who live less than fifty miles from headquarters."
  • IsEmployee: "Show me customers with investment accounts who are employees."
  • IsDeceased: "List customers with mortgage accounts who are deceased."
  • ClosedCode: "Show me accounts with the closed code of BLOC"

This new addition to the training templates will provide new ways to ask questions that had previously not been well supported by the language model.

This month's model also addresses questions that have previously been flagged by users for followup.

  • Customers with wealth acct - This question has been resolved and is now understood by the model.
  • Active employee customers with a checking account - This question is problematic since "active" could modify either employee or customers, and the model cannot easily disambiguate this. A Suggested work-around would be Active customers who are employees with a checking account
  • Accounts that are overdrawn in the past week. Suggested work-around: Accounts that are overdrawn less than 7 days
  • Customers with transactions last 30 days. Suggested workaround: Customer with more than 0 transactions last 30 days

Aunsight™ Golden Record

This month, Aunsight Golden Record has a number of new enhancements to the user experience:

  • Users can now review all changes to a domain and also revert back if the changes they see are not what they intended. Previously, users had to manually change back each change.
  • Transactional workflows can now load into Exasol, Aunsight's data mart storage engine.
  • Data Profiling is now possible with transactional workflows, as it has been for Golden Records for some time.
  • Delete detection can now be turned off to enable specific use cases such as custom queries with incremental reads. When turned off, users are notified by a tooltip.