New business intelligence methods stronger with good data quality
Business intelligence (BI) developers have found a new way to place advanced analytics applications in the hands of end users. According to a recent report by the Server Side, embedding business intelligence apps in existing enterprise systems is a growing trend among companies, one that could change firms on a fundamental level. Success with these processes, however, can hinge on data quality.
The source stated that companies need to answer several questions about the quality of enterprise data when in the process of embedding business intelligence. Adding a new BI system could be an opportunity to make sure the company's incoming data does not have any gaps or glaring inaccuracies.
The Server Side indicated that one of the keys to data quality is the presence of key performance indicators (KPIs) that could ensure that the information being collected has actual business uses and that it is being kept in a way that will avoid degradation. Data management consists of both awareness and corrective action.
According to TechTarget, many data quality problems arise in business intelligence when companies try to integrate data from multiple sources. Such information use is important for strong analytics results but must be performed carefully.
The source stated that companies need to answer several questions about the quality of enterprise data when in the process of embedding business intelligence. Adding a new BI system could be an opportunity to make sure the company's incoming data does not have any gaps or glaring inaccuracies.
The Server Side indicated that one of the keys to data quality is the presence of key performance indicators (KPIs) that could ensure that the information being collected has actual business uses and that it is being kept in a way that will avoid degradation. Data management consists of both awareness and corrective action.
According to TechTarget, many data quality problems arise in business intelligence when companies try to integrate data from multiple sources. Such information use is important for strong analytics results but must be performed carefully.