uArrow Documentation

uArrow – Data Reconciliation

uArrow Data Reconciliation is unique SAAS application which uses the in-built power of the cloud warehouses to perform data reconciliation.

uArrow Data Reconciliation is unique software-as-a-service application.

Data reconciliation (DR) is a term typically used to describe a verification phase during a data migration, data transformation and data transfer where the target data is compared against original source data to ensure that the migration architecture has transferred the data correctly.

uArrow has rich dashboard to analyze the Data reconciliation report with minimal effort.

uArrow Support the Data Reconciliation with several adapters.


  • Perform the Data reconciliation in two simple steps without technical skills
  • Data reconciliation captures
    1. Missing rows from target dataset
    2. Missing rows from source dataset
    3. Excess values from target dataset
    4. Excess values from source dataset
    5. Perfect matching deals
    6. Total values from source and target dataset
  • Support to table/dataset level with exclude certain data using sql filter
  • Support to SQL query dataset for single and multiple tables
  • Support to run Data reconciliation job on ad hoc or schedule for future run.

Below are some use cases which you can perform in uArrow.

Methods of Data Reconciliation

  1. Reconciliation between source and target.

Sales quantity, revenue, tax amount is the example of transactional data.

Some examples measure used for transactional data reconciliation can be

Sum of total revenue calculated from source and target

Sum of total product sold calculated from source and target.

  1. Reconciliation between source and processed target.
  2. Reconciliation between tables at different granular levels.
  3. Day on Day Reconciliation.