Hereunder we mean co-sourcing or nearshoring of quality assurance activities related to data warehouses (DWH) & data-based testing such as:

  • methodical test data generation

  • test management for DWH projects according to the principles of risk management & prioritization

  • analysis/optimization of data flows in the company

  • systematic review of data quality (completeness & correctness)

  • analysis of event logs (EL) & rejected rows (RR) as well as optimization

  • automated comparison of tables or data sets (actual vs. target)

  • comparison of ETL-results with their source systems

  • data quality management

The quality of your business data defines the value of your IT.


High Data Quality

  • is the most important factor for the success of information systems today;

  • leads to better decisions by people, agents & AI;

  • reduces serious errors in decision-making that work against the achievement of departmental & corporate goals;

  • prevents internal company irregularities due to missed quantitative targets & errors in reporting;

  • prevents external loss of confidence due to errors in quarterly & other reports with external impact;

  • protects against the incurrence of direct & indirect costs

    • revenue losses, direct costs due to wrong decisions or even new risks (the tip of the iceberg);

    • indirect costs, such as increased personnel costs or lost orders, which can be much higher, as the iceberg diagram illustrates.

  • nips the rapid propagation of data quality defects in complex systems in the bud;

  • protects against time-consuming & expensive corrections in systems downstream.

CICERO Data.Quality

Integration of quality assurance expertise into your DWH & BI projects on all common systems such as Oracle, Db2®, Teradata® oder MS SQL®-Server:

  • accurate analysis & testing of critical objects such as tables & ETL processes through experience-based knowledge of CICERO consultants

  • documentation of data flows

  • definition & mapping of data consistency rules

  • based on this, development of suitable checking routines with regular execution & evaluation.

  • targeted clean-up measures with a high leverage effect

  • improvement of your ETL processes


  • Rapid detection & resolution of data quality issues

  • minimize rejected rows when loading data (time/cost)

  • early detection of duplicates & optimized data merging

  • risk minimization through systematic tests

    • on one hand by using script languages & standard tools (like Microsoft® Excel® or XML– & JSON-Tools)

    • on the other hand by automated test cases built in professional test tools like CITS™, QTP™, Tosca™ or SilkTest®

    • incl. repeatable & audit-proof results

  • prevention of expensive wrong decisions & subsequent errors

  • certainty that management reports are accurate

  • certainty that your customers only get their hands on audited & correct reports