Dirty data embodies the saying: “Garbage in, Garbage Out”, and many businesses have taken the initiative to keep dirty data from polluting their data-stream. According to Experian,91% of U.S. organizations have invested in data-quality initiatives in the past year. As the amount of digital data we gather and utilize in everyday dealings increases, the concerns[…]
The Institute Of Internal Auditors (IIA) discusses ‘Assessing Involvement in Organizational Use of Data’ with the use of some very informative infographics and statistics. According to their study, only 29% of Chief Audit Executives are ‘Very or extremely confident in the strategic decisions their organization makes based on data it collects and analyzes’. Read the pdf here… 2016 Pulse[…]
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We occasionally get asked if we do anything with Big Data. We don’t. All our work is to do with ensuring the quality of structured data (though maybe quite a lot of it) that has to enter downstream processes and perform reliably. But we like to keep an eye on Big Data, not least for the[…]
Increasingly sophisticated methods are available for analyzing financial data and helping decision makers. But in practice the data that is used by these methods may be full of errors; it is dirty data. And it is often the more sophisticated methods that are most affected by dirty data: time series and variance models, such as GARCH, seem[…]
The Asset Management sector too has its data quality problems. This blog from Confluence highlights this as an issue for 2016: Asset Management Industry – Data Management Revolution 2016?