CICERO.DataQuality
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.
CICERO.DataQuality
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.
- revenue losses, direct costs due to wrong decisions or even new risks (the tip of the iceberg);
- 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
Benefits
- 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
- on one hand by using script languages & standard tools (like Microsoft® Excel® or XML– & JSON-Tools)
- 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
