by Blazent | Dec 1, 2016 | Data Quality
4th of a 4-part series Previous posts have provided an overview of data quality drivers and their associated dimensions. To recap, the dimensions covered include: Integrity Accuracy Completeness Duplication Currency Consistency This post presents...
by Blazent | Nov 29, 2016 | Data Quality
A recent white paper published at sapinsider, does a nice job of surfacing many of the challenges Blazent’s customers face. This blog will expand on the 5 reasons listed in the white paper, which focus on data quality implementations in the context of IT asset and...
by Blazent | Nov 23, 2016 | Data Quality
When considering the business value of good data quality, the primary purpose is to make a business more efficient and profitable. The 451 Group research that tabulated the top 5 benefits below included other downstream benefits, such as “better supplier performance”...
by Blazent | Nov 16, 2016 | Data Quality
3rd of a 4-part series A preceding blog provided an overview of the operational dimensions that are normally associated with data quality. To recap, these are: Integrity Accuracy Completeness Duplication Currency Consistency This blog post will...
by Blazent | Oct 27, 2016 | Data Quality
451 Research recently released a report titled, “The State of Enterprise Data Quality: 2016, The Role of DQM in Machine Learning and Predictive Analysis.” Its authors are Carl Lehmann, Krishna Roy and Bob Winter. A key finding from their survey of hundreds of IT...
by Blazent | Oct 25, 2016 | Blog, Data Quality
2nd of a 4-part series In the previous blog post, Blazent provided an overview of data quality and its dimensions. To recap, its dimensions are: Integrity Accuracy Completeness Duplication Currency Consistency This second part will focus on data...
