Visual BI ValQ
Data Science & Engineering
New IT innovations such as the Internet of Things (IoT) or the mobile Internet increase the data volume at an enormously fast pace and also confront your company with very great challenges in terms of securing your data quality.
In times of big data, more than half of all companies consider the quality of their data to be critical for business decisions. Poor data quality leads to lower employee and customer satisfaction, but also to higher costs: manual quality assurance is about five to ten times more expensive than an automated variant.
It is difficult to measure and track success in a data quality offensive. Moreover, the result of a repetition is not always the same and the quality of the validation strongly depends on the user. IT must first create its own validation options. This creates further validation islands. Data entry checks take place in dialog, but in practice there are always cases where data has not been entered during validation, either through interfaces or alternative input options.
With our solution, you can track and evaluate errors at a central point, view them over time and show each participant their data. You can quickly and easily create rules and also access a large pool of predefined rules - without programming knowledge.
With our DQM solution...
... you always keep the overview
... pave the way to consistent data
... you can keep track of errors once they have been detected
... you can make better decisions based on correct data
... eliminate errors and reduce costs
The sentence "You can't improve without measuring" also applies to your data quality. With our solution, however, you can automatically record defects, compare them with the last analysis result and thus determine which defects are new and which were already present. This is the only way to improve your data sustainably and continuously.
Our DQM solution can be based on both SAP BRFPlus and SAP HRF. Alternatively, the rules can also be made directly from IT in ABAP. Both frameworks can be used to create complex sets of rules that make the rules transparent and readable. Simple logics such as "if then else" can be applied within the set of rules. Dashboard conversion is usually done using the SAP Lumira Designer.