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DESCRIPTION:Click for Latest Location Information: http://edw2015.dataversity.net/sessionPop.cfm?confid=87&proposalid=7030\nEvery organization has more data now than they did 5 years ago. All companies have limited resources with which to manage and improve the quality of that data. Why then, do so many insist on an all-or-nothing view on data quality? Is insisting on data perfection, and then failing, the only way to approach data quality? Of course not!\nData is never going to be perfect. It’s always going to be somewhat abstracted from truth. Whether it’s another decimal point of precision, faster sampling, or more attributes, our data can always be better. The primary question shouldn’t be “how good is our data quality” but instead we should be asking “how useful is our data?” We should be thinking about the limited resources we have, and where investments in improving data quality will be most beneficial.\nThis session will go into more detail to build the case for "strategic data quality" and cover the following:\nThe role of strategic data quality in business activities and decisions\nThe concept of data sufficiency, and why too high data quality can also be problematic\nWhere technology and data intersect, and why now is a historic inflection point\nWhy getting this right may be the most important thing your business does in the next few years\nHow to get started with strategic data quality
DTSTART:20150401T083000
SUMMARY:Strategic Data Quality - Your Best Alternative to Failing at Perfection
DTEND:20150401T091459
LOCATION: See Description
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