Only Data Quality turns a Business Data Warehouse (BDW) and Business Intelligence (BI) into a real competitive advantage

Incorrect, out-of-date or duplicate data - the basis for bad decisions

Incorrect, out-of-date or duplicate data from different IT systems is the biggest obstacle to comprehensive analyses, reliable evaluations and related BI solutions such as CPM. This can also mean that you do not identify potential business opportunities in good time, since the buying behaviour of the customer is analyzed incorrectly. You can only identify and assess risks inadequately and put pressure on your risk management, since your sales figures are out of date. You are also unaware of possible weak points in your company, e.g. material or supply bottlenecks, until it is too late. Poor data quality is responsible for this - with possibly fatal consequences which can range from a fall in revenue and the loss of market share to an increasing threat to competitiveness.

Business Intelligence silos prevent company-wide analyses

BI solutions are still used by departments with their own data marts or Data Warehouses in many companies and the data quality can therefore vary. The result: data is stored redundantly or in different formats. And while the data may be correct in one database, it may be incorrect or outdated in another data pool. Reliable company-wide analyses are only possible here with a considerable amount of manual correction. Not to mention the additional costs and the reduced capability of reacting to the uncertain analysis results.

Unused BI potentials through limited possibilities for evaluation

The better the data quality in the Data Warehouse, the more evaluation options are open to decision-makers and other users of the BI solutions. For example, managers should be able to define individual levels of detail in their dashboards. Staff in the finance department have to be able to prepare specific reporting themselves. Users should be able to develop analyses from different perspectives by means of OLAP analyses, e.g. sales figures according to region, product group, sales volume, etc. And warning indicators based on defined rules, e.g. too little stock on hand, should be guaranteed to reach the respective personnel.

Reduced confidence causes decisions based on gut feeling

If the provided information and analyses repeatedly lead to bad decisions on account of poor data quality, confidence in the capabilities of the BI system is reduced. This can mean that Business Intelligence functions are no longer used and are replaced by subjective assessment. More bad decisions are only a matter of time here.

Poor data quality puts adherence to your compliance requirements at risk

Inadequate data quality puts the accuracy and reliability of the BI evaluations at risk. This can have legal consequences and may entail high costs for the company.

Manual data cleansing as a brake on decisions and a cost driver

If urgently required data is not complete, error free and consistent, it has to be compiled, analyzed and prepared manually. This leads to unnecessary delays which you cannot afford, particularly in the case of time-critical business decisions. And it costs money and resources which you can use to better effect for other important projects.

Uniserv Data Quality Solutions for Business Intelligence – high data quality for improved decision-making

Uniserv Data Quality Solutions help you to make your business decisions on the basis of reliable and up-to-date data, minimize risks and design the operative and strategic business management more flexibly and more quickly.


Data Quality Explorer for BI: The Explorer enables you to determine the actual state of your data before the initial transfer to the Business Data Warehouse. Data Quality Real-Time Services for BI: For the immediate protection of your data quality during the transfer of data from the operative systems to the Data Warehouse in (near) real-time.

Data Quality Monitor for BI: This monitors the data quality according to defined business rules. It alerts you if specified threshold values are exceeded.

Our contribution to efficient Business Intelligence: 

• Profiling of new data sources before the initial transfer of the data to the Business Data Warehouse. Transfer of the data from a wide range of flat files and databases and, where necessary, conversion of the field or record format. Automatic duplicate recognition and clustering of name and address data, in order to merge e.g. customer data in the corporate group, even if the individual subsidiaries work with unsynchronized data (different customer number systems), or a single view of the household is to be formed in the Data Warehouse, but this information is not provided by the operative systems.
• The data validation, enhancing and consolidation functions and the monitoring of threshold values for specified business rules supplement the data quality tool box for BDW and BI. Uniserv DQ Explorer, DQ Batch Suite, DQ Real-Time Service and DQ Monitor are our contribution to the successful use of your Business Data Warehouse and BI system. So that reliable information is obtained from data.  

Profit from all Uniserv Data Quality Solutions for Business Intelligence including:

• Optimum data quality in the Business Data Warehouse through analysis of the data before the initial transfer from existing data sources (Data Profiling) and through regular monitoring (Data Quality Monitoring)
• Reliable revision of the data (Data Cleansing) according to defined rules and by matching it against reference data (e.g. address, bank, geodata)
• Consolidation of customer data even if there is no stable reference number, or formation of the view of the household even if this information is not maintained in the operative systems.
• Gaining new dimensions for analysis and evaluations by enhancing your customer data e.g. with geographic references, background indicators, sector codes, etc. and therefore completely new information with regard to "empty spaces" on your sales and marketing map or the potentials of the individual customer segment
• Informed business decisions and increased capability of reacting to market changes and new requirements of the specific industrial or commercial sector through the preparation of correct, complete and up-to-date data and its provision for management and staff
• High data quality as a basis for the efficient use of all analysis and display formats of the BI solution such as dashboards, cockpits, OLAP and warnings
• Faster, more flexible corporate planning through a current, reliable overview of all areas of the company
• Reliable, future-oriented forecasting through the use of additional solutions to increase the company performance such as Corporate Performance Management
• Effective risk management and reliable compliance with statutory requirements and internal regulations (governance, risk and compliance) through precise, complete and transparent reporting
• Reduced costs through automated protection of the data quality and reduced costs for merging and maintaining data stocks